katholieke universiteit leuvenlib.ugent.be/fulltxt/rug01/001/789/750/rug01-001789750... · 2012. 3....

Katholieke Universiteit Leuven

FACULTY OF BIOSCIENCE ENGINEERING

INTERUNIVERSITY PROGRAMME (IUPFOOD) MASTER OF SCIENCE IN FOOD TECHNOLOGY

Option Food Science and Technology

Academic year 2010-2011

Formulation and characterization aspects of low fat whipping cream by

Water/Oil/Water technology

by Lien Vermeir

Promotor : Prof. dr. ir. Paul Van der Meeren

Master's dissertation submitted in partial fulfilment of the requirements for the degree of Master of Science in Food Technology

The author and promoters give the permission to consult and copy parts of this work for personal use only. Any other use is under the limitations of copyrights laws, more specifically it is obligatory to specify the source when using results from this thesis. Gent, June 2011 The promotor the author Prof. dr. ir. Paul Van der Meeren Lien Vermeir

Acknowledgements

I would like to thank my promotor, supervisor and mentor, Prof. dr. ir. Paul Van der Meeren,

whose guidance, insights and stimulating suggestions helped me in all the time of research.

Deep gratitude is expressed to the members of the department of Applied Physical Chemistry:

Eric, Marios, Maryam, Paolo, Quenten, Saskia and Zhu.

Lastly, I offer my regards to all of those who supported me in any respect during the

completion of my thesis: members of the lab of FTE, the staff of IUPFOOD in Gent and

Leuven and last but not least, my family.

Table of contents

Table of contents

Abstract

Chapter 1: Literature review

1.1 Water-in-oil-in-water emulsions

1.1.1 Water-in-oil-in-water technology

1.1.2 Preparation of a w/o/w-emulsion

1.1.3 Encapsulation efficiency

1.1.4 Instability of w/o/w-emulsions

1.1.4.1 Thermodynamic instability of a w/o/w-emulsion

1.1.4.2 Water transport between the w1 and w2-phase

1.1.4.3 Gravitational instability of a w/o/w-emulsion

1.1.5 Desired characteristics of a whippable w/o/w-cream

1.2 Traditional dairy whipping cream

1.3 Changes during whipping of cream

1.3.1 Three stages during whipping of cream

1.3.2 Foam stabilization by partial coalescence

1.3.2.1 Determination of partial coalescence

1.3.2.2 Distinction between partial coalescence and complete coalescence

1.3.3 Alternatives to partial coalescence

1.4 Mimicing whipping cream

1.5 Quality characteristics of whipped cream

1.5.1 Overrun

1.5.2 Whipping time

1.5.3 Textural analysis

1.5.4 Physical stability

1.5.4.1 Coarsening of foam

1.5.4.2 Drainage

1.6 Factors determining functional properties of whipping cream

1.6.1 Temperature

1.6.1.1 Tempering

1.6.1.2 Heat treatment

1.6.2 Fat content

1.6.3 Homogenization

1.6.4 Miscellaneous factors

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Table of contents

Chapter 2: Materials and methods

2.1 Commercial butters

2.1.1 Preparation of butter samples

2.1.2 Analysis of butter samples

2.2 Water-in-oil emulsions

2.2.2 Materials needed for the preparation of w/o-emulsions

2.2.3 Composition of the w/o-emulsions

2.2.4 Preparation of the w/o-emulsions

2.3 Quantitative particle size analysis of water in w/o-emulsions

2.3.1 Pulsed field gradient-Nuclear Magnetic Resonance

2.3.2 The pfg-NMR experiment

2.3.2.1 Calibration procedure

2.3.3 Restricted diffusion in w/o emulsions

2.3.3.1 Data procesing by the Droplet Size application

2.3.3.2 Data processing by Excel

2.3.3.3 Data processing by Matlab

2.3.4 Statistical methods

2.3.5 Important issues during pfg-NMR analysis

2.3.5.1 Temperature of the emulsion during pgf-NMR analysis

2.3.5.2 Assumption of a lognormal size distribution

2.3.5.3 Advantages of pfg-NMR analysis for determination of water droplet size

2.4 Qualitative particle size analysis of water in w/o-emulsions

2.4.1 Fluorescence microscopy

2.4.2 Fluorescence

2.4.3 EosinY

2.4.4 Fluorimetric analysis of w/o emulsions

2.4.4.1 Fluorimeter

2.4.4.2 Determination of a suitable concentration of eosinY

2.4.4.3 Determination of maximum excitation and emission wavelength

2.4.5 Confocal laser scanning microscopy


2.5.1 Composition of the w/o/w-emulsions

2.5.2 Preparation of the w/o/w-emulsions

2.5.2.1 Method A

2.5.2.2 Method B

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2.5.2.3 Method C

2.5.2.4 Method D

2.6 Quantitative analysis of the enclosed water volume and yield of water-in-oil-in-water

emulsions

2.6.1 The CPMG-experiment

2.6.2 Determination of the enclosed water volume

2.6.3 Determination of the yield of a double emulsion


2.7 Fat globule analysis by laser diffraction

2.8 Profilometric analysis of double emulsions

2.9 Whipping of a commercial dairy cream and w/o/w-emulsions

2.9.1 Commercial dairy cream

2.9.2 W/o/w emulsions

2.9.2.1 First attempt to prepare whippable double emulsions

2.9.2.2 Second attempt to prepare whippable double emulsions

2.9.2.3 Third attempt to prepare whippable double emulsions

2.9.2.4 Fourth attempt to prepare whippable double emulsions

2.9.3 Determination of the whipping time

2.9.4 Determination of the overrun of a whipped emulsion

2.9.5 Physical destabilization (drainage) of whipped emulsions

Chapter 3: Results and discussion

3.1 Optimization of wayer droplet size analysis

3.1.1 Temperature experiment by using a thermocouple

3.1.2 Repeatability experiment

3.2 Quantitative particle size analysis of water droplets in commercial butters

3.3 Quantitative particle size analysis of water droplets in w/o-emulsions

3.3.1 Analysis of emulsions with composition H0/1, H0.5/1, M0/1 and P0/1

3.3.2 Analysis of emulsions with composition H0/1. H0.5/1, M0/1, P0/1, P0.5/1 and

P0.5/2

3.3.2.1 Statistical analysis of emulsions H0/1, H0.5/1, P0/1, M0/1, P0.5/1 and

P0.5/2

3.3.2.2 Difference between different data processing methods

3.3.2.3 Influence of the type of fat on the mean water droplet size

3.3.2.4 Influence of the emulsifier on the mean water droplet size

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Table of contents

3.3.3 Elevation of the water fraction of emulsions based on Hozol

3.3.4 Effect of the decrease of the homogenization pressure of the Microfluidizer M110S

on the water droplet size in a w/o emulsion

3.3.5 Analysis of emulsions with the hydrophilic surfactant whey protein isolate

3.4 Qualitative particle size analysis of water droplets in w/o-emulsions by fluorescence

microscopy

3.4.1 Preliminary investigation of eosinY-solutions by fluorimetry

3.4.2 Determination of the maximum excitation and emission wavelength of eosinY

(5µg/mL) in water


(5µg/mL) in an aqueous phosphate buffer (pH6.7)


(5µg/mL) in aqueous phosphate buffer (pH6.7) with sodium azide (0.02%, w/v)


(5µg/mL) in aqueous phosphate buffer (pH6.7) with sodium azide (0.02%, w/v) and

sodium caseinate (1.25%,w/v)

3.4.6 Selection of the filter block in the fluorescence microscope

3.4.7 Fluorescence microscopic images of water droplets in a w/o-emulsion

3.4.8 Imaging of water droplets in water in oil emulsions by confocal laser scanning

microscopy

3.5 Determination of the enclosed water volume and yield of w/o/w-emulsions

3.5.1 Method optimization

3.5.1.1 Optimization of the preparation method

3.5.1.2 Finding an appropriate concentration of MnCl2

3.5.1.3 Investigation of the permeability of the oil phase by a temperature

experiment

3.5.1.3.1 Analysis of the area under the curve at different temperatures

3.5.1.3.2 Analysis of the signal amplitude at different temperatures

3.5.1.3.3 Analysis of the relaxation time at different temperatures

3.5.1.4 Variation of the duration of mixing of the double emulsions

3.5.1.5 Effect of the reduction of the duration of mixing with an Ultraturrax S25-

10G

3.5.1.6 Effect of quick cooling on the percentage of enclosed water volume

3.5.2 Method application

3.5.2.1 Variation of the composition of the fat phase

3.5.2.1.1 Effect of the fat composition on the enclosed water volume and

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Table of contents

yield of double emulsions made by Method B

3.5.2.1.2 Effect of variation of the fat phase on the T2-distribution of

double emulsion made by Method B


yield of double emulsions made by Method C

3.5.2.1.4 Effect of the variation of the fat phase on the T2-distribution of

double emulsion made by Method C


yield of double emulsions made by Method D

3.5.2.2 Effect of the concentration of the hydrophilic emulsifier in the external

water phase on the enclosed water volume

3.6 Fat globule analysis by a Malvern Mastersizer S

3.7 Visualization of double emulsions by light microscopy

3.8 Research on the thickness of the separated cream layer of double emulsions

3.8.1 Determination of the thickness of the separated creamy layer with a ruler

3.8.2 Profilometric analysis of double emulsions

3.9 Whipping of a commercial dairy cream

3.9.1 Whipping time of a whipped commercial dairy cream

3.9.2 Overrun of a whipped commercial dairy cream

3.9.3 Physical destabilization (drainage) of a whipped commercial dairy cream

3.10 Whipping of w/o/w-emulsions

3.10.1 First attempt

3.10.2 Second attempt

3.10.3 Third attempt

3.10.4 Fourth attempt

General conclusions

List of references

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Abstract

1

Abstract

A proper foundation is established with the prospect of manufacturing a food grade

recombined whipping cream by water/oil/water technology. The w/o/w technology can offer

the opportunity to produce a cream in which the oil droplets are filled with water droplets and

hence a low-energy-dense cream can be created.

In this thesis three main parts can be distinguished. In the first section, as a water-in-oil-

in-water emulsion requires an appropriate water-in-oil emulsion, research was performed on

w/o-emulsions. The composition of an emulsion is determined by the type of fat, the

emulsifier and the water content. The water droplet size was affected by the type of fat, the

emulsifier concentration and the driving air pressure during preparation. Visualization of

water droplets might be possible by light microscopy and the use of the fluorescent dye

eosinY. In the second section, the manufacturing of w/o/w-emulsions is optimized by various

ways of manufacture and characterized by T2-analysis, laser diffraction and profilometry. A

yield of about 42 to 62% could be obtained if the double emulsion was made by intensive and

less intensive homogenization during the first step of the preparation of double emulsions,

respectively. Moreover the homogenization intensity during the second step needed to be

sufficiently small. The duration of mixing in the second step and the concentration of sodium

caseinate in the external water phase affected the yield. In a third section, whipping of w/o/w-

creams was attempted. Although by the use of xanthan gum in the external water phase a

gravitational stable cream was obtained, the desired textural change during whipping was not

observed.

In the whole process, due attention is paid to proper characterization techniques, with

special focus on low-resolution NMR as a non-invasive and non-destructive method. This

technique not only enabled water droplet analysis in the primary w/o-emulsion (based on

diffusometry), but also allowed the discrimination between internal and external water in the

multiple emulsion (based on T2-analysis) and determination of the thickness of the separated

cream layer and its water content in double emulsions (based on profilometry).

Overall, it was shown that multiple emulsions with about 30wt% of dispersed phase could

be obtained with only 20wt% of fat using food-grade emulsifiers (i.e. PGPR and sodium

caseinate). In order to ensure good whipping properties, further research will be needed.

Hereby, the composition of the interfacial layers, as well as fat crystallization will be

important issues.

Chapter 1 Literature review

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Chapter 1

Literature review


1.1.1 Water-in-oil-in-water technology

A w/o/w emulsion, which is a double emulsion, consists of two non-miscible liquids, water

and oil. Small water droplets are dispersed in larger oil globules, which are themselves

dispersed in an aqueous continuous phase. Three potential benefits are the possibility of

lowering the fat content, entrapping (and releasing) therapeutic, nutritional or odourous

compounds in the internal water droplets and separation of incompatible substances (Márquez

and Wagner, 2010). In this thesis, emphasis lies on the potential of w/o/w-emulsions to reduce

the fat content. The accelerated increase in the incidence of cardiovascular diseases at

worldwide level has led consumers demand healthier low-fat food that reduces or helps to

maintain triglyceride blood levels (Lobota-Calleros et al., 2009).

Most double emulsions are very polydispersed. The range of the size of double emulsion

droplets can be quite extensive: the size of multiple droplets can be between 2-5 µm and 15-

50µm, containing respectively a few and 50-100 water droplets. In this regard, three classes

can be distinguished: type A, B and C (Figure 1.1), which differ from each other in the

amount of water droplets entrapped in the multiple droplet (Garti and Bisperink, 1998).

Figure 1.1 Three different types of entrapment of water droplets in the multiple droplet (Garti and Bisperink, 1998).


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1.1.2 Preparation of a w/o/w-emulsion

Multiple emulsions can be produced in a one-step or a two-step process. With regard to food

applications, a two-step process (Figure 1.2) is more common and consists of a first

emulsification step at higher shear forces than the second step, resulting in a w1/o-emulsion

and w1/o/w2-emulsion, respectively.

The second emulsification step is a critical step. A too high homogenization pressure results

in swelling and rupture of the internal water droplets (w1) and coalescence of the w1-droplets

with the outer water phase (w2) (Hindmarsch et al., 2005). A lower homogenization pressure

might result in more coalescence in virtue of too large multiple emulsion droplets.

Besides the homogenization pressure, the amount of homogenization cycles and the

temperature are important. High temperatures and a high amount of homogenization cycles,

assuming sufficient emulsifier, result in smaller multiple droplets, which might compromise

the encapsulation of water (Lindenstruth and Müller, 2004).

Figure 1.2: Scheme of the preparation of a w/o/w- emulsion (Remon & Vervaet, 2003)

Mostly, the mixing of the w1/o-emulsion and the w2-phase is done at a lower temperature than

the preparation of the w1/o-emulsion. Water-in-oil emulsions are made at 50 to 70°C, whereas

w/o/w-emulsions are prepared at room temperature (Min et al., 2010; Lutz et al., 2009) or in

an ice bath (Frasch-Melnik et al., 2010b). O’Regan and Mulvihill (2010) prepared the w/o/w-

emulsions at 60°C.


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Emulsification can be performed by homogenization, membrane emulsification and micro-

channel emulsification.

Evaluation of the type of double emulsion can be done by dilution with water. Water will not

be miscible with an o/w/o-emulsion, whereas the reverse is true for an w/o/w-emulsion.

Alternatively, a water-soluble compound, e.g. methylene blue, can be added to the double

emulsion, followed by visual evaluation of the miscibility and/or microscopical investigation.

Methylene blue in an w/o/w-emulsion makes the sample turn blue, whereas in an o/w/o-

emulsion, this won’t have a profound effect on the color (Tirnaksiz and Kalsin, 2005).

An overview of different compositions of double emulsions in literature is given in Table 1.1.

1.1.3 Encapsulation efficiency

The encapsulation efficiency is determined by the conditions during emulsification (e.g.

homogenization pressure and temperature) and the factors affecting the release of internal

water. Regarding the latter, shear action or the presence of a concentration gradient influences

the encapsulation of the w1-phase. Depending on the direction of the osmotic gradient

swelling or shrinkage of the internal water droplets can occur (Lutz et al., 2009).

The yield of encapsulation after emulsification can be determined by the entrapment of a

marker compound in the w1-phase and its detection in the w2-phase. An overview of markers

and their detection is given in Table 1.2. For example, the entrapment or yield percentage can

be determined by conductometry and is determined by the formula:

Yield percentage= (Ci-Ct)100% / Ci

where Ci and Ct are the conductivity of the internal aqueous phase and of the multiple

emulsion at a given time t (Tirnaksiz and Kalsin, 2005).

The release of marker compounds from the inner to the outer water phase depends on its

diffusion coefficient, its initial concentration, the sphere radii (surface area of oil globule), the

viscosity of the oil phase and the solubility of the marker in the oil phase (Sela et al., 1995).


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Table 1.1: Overview of compositions of double emulsions in literature.

Reference

Oil phase

Lipophilic surfactant in the oil-phase

Concentration of lipophilic surfactant in the oil phase

Compounds in the w2-phase

Concentration of the hydrophilic surfactant in w2-phase

Compounds in the w1-phase

Concentration of compounds in the w1-phase

Ratio of the w1/o/w2- emulsion

Muschiolik et al., 2006 Sunflower oil PGPR 4%(w/v) WPI 1%(w/v) NaCl or gelatin 0.6 or 3%(w/v) 3/12/85

Su et al., 2006 Soybean oil PGPR 2%(w/v) Na caseinate 0.5%(w/v) Na caseinate 0.5%(w/v) 4/16/80

O'Regan and Mulvihill, 2010

Median chain triglyceride (MCT) PGPR 2wt%

Na caseinate/ Na caseinate-maltodextrin 1wt% protein gelatin and NaCl 5wt% and 0.6wt% 8/32/60

Lutz et al., 2009 Median chain triglyceride (MCT) PGPR 10wt% WPI and pectin

4% and 0.5wt% - - 12/18/70

Frasch-Melnik et al., 2010 Saturated MG, tripalmitate and 0.44wt%+0.88wt% Na caseinate 1wt% - - 3/17/80

Sunflower oil PGPR 0.35wt%

GMO and PGPR 2.2wt% and 8.9wt% WPI 6.7wt% Glycerol 3wt% 4/16/80 Benichou et al., 2007

Median chain triglyceride (MCT)

WPI and xanthan (4/0.5)

6.7wt%

Glycerol

3wt%

Mun et al., 2010 Soybean oil PGPR 4; 6; 8wt% WPI 2/4/6wt% - - 8/32/60

Márquez and Wagner, 2010 Sunflower oil PGPR 0.5 to 2wt% xanthan gum in soy milk 0.2wt% CaCl2 0.38-1.5wt% 8/32/60

CaCO3 1.5wt%

Ca lactate 1.5wt%


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Table 1.2: Overview of different markers and techniques of detection

Reference Marker Measurement

Sela et al., 1995 2wt% NaCl/NaF/NaBr/NaI in w1-phase

1wt% ephedrine HCl in w1-phase

2wt% KNO3 in w1-phase

Conductometry of serum phase

Lutz et al., 2009 4.4wt% NaCl in w1-phase

15wt% Na ascorbate in w1-phase

Conductometry of the serum phase

Lindenstruth and Müller, 2004 0.5%(w/v) Na diclofenac in w1-phase HPLC after ultrafiltration

Frasch-Melnik et al., 2010b 1.6wt% KCl in w1-phase Conductometry of the serum phase

Benichou et al., 2007 2wt% glucose in w1-phase Glucometry

0.33-3g/100g emulsion vitamine B1 Differential pulse polarography

Tirnaksiz and Kalsin, 2005 1.5wt% caffeine + 0.03wt% NaCl Spectrophotometry (271nm) after dialysis

0.3wt%NaCl in w1-phase Conductometry of the serum phase

Wolf et al., 2009 0.02wt% vitamin B12 in w1-phase

Spectrophotometry (361nm) after centrifugation

and filtration of the serum phase

1.1.4 Instability of w/o/w-emulsions

1.1.4.1 Thermodynamic instability of a w/o/w-emulsion

Applicability of multiple emulsions is limited by their thermodynamic instability

(Ursica et al., 2005), which is caused by the large surface free energy between fat and

water. Hence, emulsions will strive to lower the interfacial free energy by

minimization of the contact area between the phases until water is completely

separated from the fat (Jiao and Burgess, 2008; Goff, 1997). Destabilization of a

double emulsion can occur by coalescence of internal water droplets or multiple

droplets and water diffusion between the two water phases, as represented in Figure

1.3.

Muschiolik et al. (2006) defined long–term stability of double emulsions as a period

of at least 12 months. A high yield of the w1-phase, no phase alteration and no phase

separation during 8 month at +7°C are the characteristics of a high storage stability

emulsion.


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Figure 1.3: Overview of the possible destabilization mechanisms in w/o/w emulsions (Mezzenga et al., 2004)

Coalescence involves rupture of the film between two adjacent water or oil droplets: a

hole is formed that grows under the action of surface tension and results in the fusion

of two adjacent droplets. Rising the temperature might activate coalescence and

decrease the entrapment of water in the multiple droplets. Larger inner water droplets

promote coalescence between the interfaces of the inner water droplets and the

multiple droplets (Bibette et al., 1999). The kinetics of coalescence of inner water

droplets with the multiple droplet interface is related to the concentration of the

hydrophilic surfactant in the w2-phase phase, whereas the kinetics of the coalescence

between inner water droplets is related to the type of hydrophilic emulsifier in the w1-

phase (Garti and Bisperink, 1998).

Coalescence can be measured by measuring the turbidity. Since the larger droplets

scatter light less effectively than smaller ones, the emulsion may appear less turbid. It

can also be measured by particle size analysis. A more time consuming method is the

following method: an oil droplet can be released from a capillary tube, placed on the

bottom of an aqueous phase with at the top a planar oil-water interface. The droplet

moves upwards, reaches the oil-water planar interface and the time to merge with the

planar oil-water interface is determined with an optical microscope (McClements,

2007).

Water diffusion or Ostwald ripening from the outer to the inner water phase can result

in a bigger average inner water droplet diameter (coarsening) and a reduction in

number and is due to diffusion of water molecules across the oil layer in both

directions, which doesn’t disrupt the interfacial film (Bibette et al., 1999).


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The composition of a double emulsion can affect its stability. Garti and Aserin (1996)

reported that stable double emulsions are obtained by the use of an inner hydrophobic

emulsifier in great excess (10-30wt% of the w/o-emulsion) and an external

hydrophilic emulsifier in lower concentrations (0.5-5wt%). Increasing the latter

concentration above a certain threshold concentration resulted in a lower

encapsulation efficiency, due to an excess of osmotic pressure in the outer water

phase and the formation of reversed micelles that pumps the hydrophobic surfactant

outside into the w2-phase (Shima et al., 2004; Bibette et al., 1999). Consequently, the

w/o/w-emulsion turns into a o/w-emulsion. However, absence of hydrophilic

surfactants in the w2-phase, might not be able to prevent flocculation and coalescence

(Shima et al., 2004).

Other approaches to influence the stability of a double emulsion are the increase of

the viscosity of the inner water or oil phase, strengthening and rigidifying the

interfaces with polymeric emulsifiers and reduction of the inner water droplet size

(Garti and Aserin, 1996; Leal-Calderon et al., 2007). The viscoelasticity of the film

can be the result of the interaction between surface active lipids and folded and

unfolded proteins at the (w/o)/w-interface (Rousseau, 2000). Addition of sodium

caseinate to the w1-phase improves the stability of PGPR-based double emulsions,

which might be due to its effect on the water-oil interface (Hindmarsch et al., 2005).

The combination of a polymeric surfactant (BSA) and monomeric lipophilic

surfactant (Span 80) formed a thick interfacial layer w1/o, which improves its

elasticity and resistance to rupture (Garti, 1997).

Stability testing of a multiple emulsion can be performed by video microscopy,

whereby multiple emulsions are covered on micro slides, which makes the inner

water droplets to coalesce inside the oil droplet. This results in a dimpled structure

(Figure 1.4), because inner water droplets are pushed to the edge of the multiple

droplets, whereby the inner water droplets are still separated from the oil phase by a

thin film as long as the interfacial film is strong enough. Hence, a double emulsion is

more stable if there is a larger resistance to coverslip pressure (Jiao et al., 2002).


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Figure 1.4: Schematic representation of typical changes occurring to a multiple droplet on application of a cover slip pressure (Jiao et al., 2002).

1.1.4.2 Water transport between the w1 and w2-phase

Benichou et al. (2004) reported three mechanisms of water transport in double

emulsions: transport through thin lamellae of surfactants, transport in reverse micelles

and transport via hydrated surfactants (Figure 1.5).

Reverse micelles are formed in the oil phase of a w/o/w-emulsion in the presence of

monomeric hydrophobic and hydrophilic surfactants, such as Span and Tween,

respectively, whereas for polymeric surfactants (e.g. BSA) this is unknown in

literature as they serve as a mechanical barrier for the transport of solutes (Sela et al.,

1995; Benichou et al., 2007). Hence, the release can be slowed down by the complex

formation of biopolymers and hydrophobic surfactants at the inner w/o-interface,

which reduces the rate of solubilization by reverse micelles (Bibette et al., 1999).

Reverse micelle formation can occur without the presence of an osmotic gradient and

doesn’t disrupt the emulsion, whereas transport through thin layers of oil destroys the

interfacial films and releases entire inner water droplets (Garti, 1997; Lutz et al.,

2009). Especially when there is an osmotic pressure difference between the two

aqueous phases, thin layer transport of water happens (Florence and Whitehill, 1982).

The stability of the oil film can be improved by increasing the concentration of the

hydrophobic surfactant (Bibette et al., 1999).

Transport via hydrated surfactants occurs by slow emulsification of water droplets in

the oil phase (Wen and Papadopoulos, 2000).


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Figure 1.5: Schematic representation of three transport mechanisms of water in double emulsions. (a) transport via reverse micelles. (b) transport through thin lamellae. (c) water transport via hydrated surfactants (Benichou et al., 2004).

Transport rates can be reduced by increasing the viscosity of the oil phase, by

polymerization of the interfacial adsorbed surfactant molecules, by gelation of the oil

or water phases and by the presence of the right concentration of surfactants

(Schmidts et al., 2009). For example, the water permeation through the oil layer has

been reported to decrease if the oil-soluble surfactant Span 80 was present in high

concentrations (10 to 50wt% of the oil phase) in virtue of the high viscosity in the oil

phase (Wen and Papadopoulos, 2000). Complex formation between proteins and

polysaccharides in the w2-phase decreases the release rate (Muschiolik, 2007).

Addition of gelled gelatin to the w1-phase slowed down the movement of the w1-

phase to the w2-phase (Muschiolik et al., 2006). In the study of Muschiolik et al.

(2006) about multiple emulsions, an increase in PGPR concentration had a reducing

effect on the release of components from the w1-phase. Limited release was obtained

with 4%(w/v) PGPR. This concentration could be reduced to 2%(w/v) by addition of

0.5%(w/v) sodium caseinate in the w1-phase (Muschiolik, 2007).


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1.1.4.3 Gravitational instability of a w/o/w-emulsion

Regarding gravitational instability, according to the law of Stokes, creaming depends

on the density difference between the multiple droplets and the external water, the

multiple droplet size and the viscosity of the w2-phase. The density of the oil phase

can be changed by altering the type of oil or by adding fat crystals (McClements,

2007). However, sub-micron fat crystals can stabilize a w/o-emulsion, but regarding

an o/w or a w/o/w-emulsion, the control of the concentration of these fat crystals is

crucial. A scraped surface heat exchanger can be applied to selectively bring the

crystals at the w1/o-interface and not at the o/w2-interface. If they would be located at

the latter position, aggregation and coalescence might occur. In order to render fat

crystals amphiphilic or adsorbable at the interface, surfactants (monoglycerides,

lecithin) are needed. On addition of PGPR, the crystals are displaced and the interface

consists of mainly PGPR and some crystals, which increases the permeability of the

interface and allows rapid swelling when an osmotic gradient is applied. Hence, the

presence of crystals become superfluous (Frasch-Melnik et al., 2010b).

Monoglycerides and diglycerides will form the membrane around the fat globule and

can increase the density depending on the adsorbed amount, which can decrease the

rate of creaming (Goff, 1997).

The viscosity of the w2-phase can be increased by the use of polymeric compounds

(Lutz and Aserin; 2008).

Creaming can be monitored by measurement of the separation of the serum and cream

layer (Figure 1.6). At time zero, the multiple droplets are homogeneously distributed

in the sample and characterized by a concentration Co. After a while, the emulsion

separates into three distinguishable layers: a serum layer with a lower droplet

concentration than Co, an emulsion layer with a multiple droplet concentration equal

to Co and a cream layer with a larger multiple droplet concentration than Co. Besides

visual observation of the boundary of the layers, also light scattering measurement

can be applied, although in a concentrated emulsion (>10% droplets) this does not

change greatly with increasing droplet concentration. Alternatively, creaming can be

studied by the physical sectioning method, which is a destructive method that requires

freezing of the emulsions. As such the droplet concentration in each frozen section is

measured. The sample can also be divided into pieces by collecting successive

aliquots of the emulsion stored in a burette or separation funnel. When the creaming is


12

monitored as a function of time, e.g. by video imaging or by making photographs over

time, the creaming rate can be determined (McClements, 2007).

Figure 1.6: Schematic representation of creaming as a function of time in a (w/o)/w emulsion (McClements, 2007).

1.1.5 Desired characteristics of a whippable w/o/w-cream

A whipping cream should be quiescently or perikinetically stable prior to whipping

and unstable when sheared during whipping. The resistance against shear induced

destabilization is defined as orthokinetic stability (Goff, 1997; Davies et al., 2001).

In view of sensory resemblance to whippable dairy cream, the size of multiple

droplets of a w/o/w-emulsion should be similar to the oil globules of the dairy cream

(Frash-Melnik et al., 2010).

1.2 Traditional dairy whipping cream

Dairy cream, an oil-in-water emulsion can be defined as the part of milk that is rich in

fat, separated from raw milk by centrifugation at speeds of 4700-6500 rpm, resulting

in cream and skimmed milk (Hoffmann, 2002). Besides a heat treatment, the cream

can be homogenized at a low pressure, which prevents it from creaming and thus


13

destabilization. Non-homogenized fat globules are surrounded by a milk fat globule

membrane (MFGM), which prevents them from coalescing (Mulder and Walstra,

1974). The MFGM consists of approximately 25 to 60% of proteins (e.g.

butyrophillin and xanthin oxidase), lipids (e.g. phospholipids) and other compounds,

which results in a thickness between 10 and 50nm (Hui et al., 2007). A

homogenization process disintegrates the MFGM and the fat globules will be

surrounded by mainly caseins.

In the absence of stabilizing additives, the process of whipping of cream is usually

performed in situ by the consumer with a domestic electric mixer. After whipping, the

cream already collapses after 24 to 48h (Allen et al., 2008; Leal-Calderon et al.,

2007).

With regard to the legal aspect of defining cream as a whipping cream, the minimum

fat content matters and differs across countries (Table 1.3).

Table 1.3: Different national agreements of the definition of whipping cream. Country Fat % Law

Belgium Min 40% Regulation trade of cream, Royal Decree May 23rd, 1934.

The Netherlands Min 30% Commodities Act Decree of dairy products, Article 16, 1994

United Kingdom Min 35% Food Labeling Regulations, Cheese and Cream Regulations, No. 52, 1996

1.3 Changes during whipping of cream

Whipping and the introduction of air destabilize the oil-in-water emulsion, because

the coalescence of fat globules is favored by agitation (Leal-Calderon et al., 2007).

The resulting foam is an emulsion in which the dispersed phase is a gas, from which

the air-water interface is stabilized by fat globules (Schmitt et al., 2005). However,

also in absence of air, cream can be whipped.

1.3.1 Three stages during whipping of cream

Three stages can be distinguished during whipping of cream. In the first stage, most of

the air is incorporated and the foam is protein-stabilized. In the second stage, the

bubbles are coated by a layer of fat globules. The high packing density of fat globule-


14

coated gas bubbles inhibits further incorporation of gas. A simultaneous disruption

and coalescence of air bubbles take place. However, the result is a reduction of bubble

size (mostly 10-100 µm in diameter) and distribution (van Aken, 2001; Mulder and

Walstra, 1974) until maximum foam strength is achieved (Stanley et al., 1996).

During air bubble coalescence, the adsorbed fat globules are pushed together at the

bubble surface, flocculate and partially coalesce in clumps at the air-water interface

(Allen et al., 2008b) (Figure 1.7 and Figure 1.8).

Figure 1.7: A floccule and a clump of fat globules. Note that the identity of the original globule in the clump is still retained (Mulder and Walstra, 1974).

In the third stage, on prolonged whipping, the formed aggregates of fat globules

become so large that they are expelled into the continuous phase and hence the gas

bubbles are quickly destabilized, which results in a bimodal bubble size distribution

(Jakubczyk and Niranjan, 2006). The consequence is a rapid loss of air and a

phenomenon called churning, which is the formation of butter grains present in a

phased inversed emulsion (van Aken, 2001). The rate and efficiency of beating

determine the balance between whipping and churning. If beaten too slowly, the

cream may churn before a satisfactory foam has been formed. Vigorous beating leads

to high overrun and a foam with small air bubbles (Mulder and Walstra, 1974).


15

1.3.2 Foam stabilization by partial coalescence

As discussed in section 1.2.1, partial coalescence of fat takes place in the second stage

of whipping. It results in a rigid network in which bubbles are linked to one another

and liquid is entrapped (Mulder and Walstra, 1974). It prevents the full coalescence

into bigger fat globules that are not capable of structure-building (Mulder and

Walstra, 1974). The fat crystals break and penetrate the interfacial layer around the fat

globules in the emulsion, allowing globules to clump irreversibly together into a

network, whilst the identity of the original globule is retained (Allen et al., 2008a)

(Figure 1.8).

Figure 1.8: (Left) Rigid network due to partial coalescence of fat globules (Goff, 2011). (Right) Fat droplets flocculate and partially coalesce into clumps (A) at the protein-covered air bubble. If the air bubble bursts, a partially coalesced fat clump remains (C). If the air bubble remains stable, fat clumps from the bulk may partially coalesce with the adsorbed fat clump (B) (Hotrum et al., 2005a).

Hereby, the presence of partial crystalline fat, which is of a needle or platelet shape in

milk fat, is a crucial factor. The shape of the fat crystals is related to the cooling rate.

A slow cooling rate, e.g. 0.1°C/min, creates a small number of irregularly shaped

crystals, which are characterized by poor coverage of droplet interfaces and are

beneficial for partial coalescence. Rapid cooling, e.g. 10°C/min, promotes the

formation of a lot of fine crystals which are able to form a rigid dense coverage of the

interface and to stabilize the emulsion against coalescence (Frasch-Melnik et al.,

2010a).


16

However, almost completely solid fats, e.g. 80%, are not able to practice a spreading

function at the air-water interface, nor can form clumps and hence are not efficient at

stabilizing foam (Dalgleish, 2006; Mulder and Walstra, 1974). Davies et al. (2000)

concluded that partial coalescence of fat droplets is maximized when the solid fat

content is approximately 10-50% (Figure 1.9). Besides the amount of crystalline fat,

also the fat volume fraction is of importance. The rate of partial coalescence is

proportional to the squared fat volume fraction (Fredrick et al., 2010).

Figure 1.9 (Left) rate of partial coalescence as a function of solid fat content (McClements, 2007). (Right) Correlation between whipping time (emulsion stability) and solid fat content of a 30% fat emulsion as a function of storage time (ageing time) at 10°C. Black dots refer to the liquid fat content and white dots refer to whipping time (Darling, 1982).

The fat globule-stabilized air bubble layer (Figure 1.10) will remain intact as long as

the crystals don’t melt. A partial liquid part of fat globules is needed to make adhesion

and partial wetting of the air bubble surface possible. A too high liquid fraction of fat

is characterized by too rapid churning during whipping. Moreover, the excessive

spreading of the liquid fat over the air bubbles prevents the formation of sufficiently

small air bubbles (Mulder and Walstra, 1974).


17

Figure 1.10: Scanning electron micrograph of an air bubble which is stabilized by fat droplets in whipped cream. The scale bar represents 20 µm (Dalgleish, 2006).

1.3.2.1 Determination of partial coalescence There are different methods to determine partial coalescence. Firstly, partial

coalescence can be measured by a dye solution absorbance method. It comes down to

the determination of the change in absorbance of a lipophilic dye solution due to the

dilution by free fat. During partial coalescence aggregates of fat globules, which are

considered as free fat, are formed. The Palanuwech method uses the dye Oil Red O

(0.0015wt% in oil), which absorbs maximally at 520nm. Pure oil phase is taken as

blank. The dye solution is poured onto the surface of the emulsion under

investigation, gently mixing and allowing the colored oil to float at the surface under

gentle centrifugation. The free fat in the emulsion will be dissolved in the colored oil,

but the emulsified fat remains in its droplets. After transfer of the diluted-dye solution

fraction from the surface, its absorbance is measured. Out of the change in

absorbance, the free fat fraction in the emulsion can be calculated (Palanuwech et al.,

2003).

Secondly, turbidity can be measured to investigate the aggregates of fat globules

(Kiokas et al., 2004).

Thirdly, partial coalescence can be investigated by measuring the size of clumped fat

droplets. In a study of Kiokas et al. (2004) this was done with pfg-NMR and

supplemented with scanning electron microscopy imaging.

1.3.2.2 Distinction between partial coalescence and complete coalescence

Regarding completely coalesced fat globules, the identity of original fat globules is no

longer retained. Partial coalescing results in an increase of volume fraction and hence


18

viscosity, whereas the viscosity doesn’t increase when two droplets coalesce

completely. Another difference lies in the fact that an applied velocity can increase

the rate of partial coalescence without affecting the rate of complete coalescence

(Fredrick et al., 2010).

1.3.3 Alternatives to partial coalescence

Like stated above, stabilization of the foam structure can be done by partial

coalescence of semi-crystalline fat globules, though this is not the only mechanism

(Allen et al., 2008a). An alternative foam-stabilizing method concerns fat globule

aggregation induced by acidification in the presence of a small molecule weight

lipophilic surfactant LACTEM (lactic acid esters of monoglycerides)(0.25wt%). In

protein-stabilized emulsions, a reduction of pH towards the protein’s IEP, diminishes

the electrostatic stabilization and enhances protein-protein interactions. This results in

a protein-stabilized fat globule network, in which the fat droplets are not partially

coalesced but occur as distinct entities, which is similar to the production of yoghurt.

The addition of an emulsifier partially displaces the adsorbed casein at the oil-water

interface, which induces the formation of strong interdroplet crystal–crystal

interactions and fat droplet aggregates upon whipping. The advantage of this method

is that the amount of solid fat enabling whipping can be reduced. Still, its presence is

essential in terms of achieving a similar rigidity as traditional whipped cream (Allen

et al., 2008a).

Márquez and Wagner (2010) concluded that an unwhipped w/o/w emulsion based on

liquid oil, PGPR and 0.12wt% CaCl2 or calcium lactate in the primary emulsion and

0.2wt% xanthan gum in soybean milk as an external water phase, offers an alternative

for whipped dairy cream because of its creamy texture obtained directly after

preparation, which is similar to whipped dairy cream. This is explained by the

swelling of the internal water droplets in the presence of soluble calcium salts in the

w1-phase and the increase of consistency due to the osmotic gradient and by the

interaction of released calcium with soybean proteins at the o/w2-interface, which

results in the flocculation of w/o droplets.


19

1.4 Mimicing whipping cream

Recombined cream is an emulsion of butterfat or a higher melting fat stabilized by

skimmed milk products (Hotrum et al., 2005a). If a reconstituted cream contains other

non-dairy sources of fat, it is denoted as a filled cream (Hui et al., 2007).

In order to mimic a whipping cream, partial coalescence can be influenced by the type

and amount of emulsifier in the formulation. For example, proteins in a certain

concentration can reduce the susceptibility of the emulsion to partial coalescence by

formation of a thick layer around the fat globules, which increases the repulsive forces

and the resistance to penetration of fat globules by fat crystals (McClements, 2007).

Segall and Goff (1999) reported a too high stability against whipping for WPH or

SMP-stabilized emulsions. Hydrolysis of whey proteins (WPH) exposes previously

buried hydrophobic sites, which increases its surface activity in comparison to WPI.

SMP consists of large casein micelles which result in a thick layer of surface

coverage, which makes it more resistant to shear. A similar change in surface activity

can be noticed by denaturation of whey proteins. Consequently, an increased fat

membrane integrity and hence, increased stability against partial coalescence can be

observed (Goff, 1997). WPI and sodium caseinate-stabilized emulsions resulted in a

larger susceptibility to partial coalescence than SMP-stabilized emulsions (Goff,

1997; Leser and Michel, 1999). However if more than 0.5% WPI was present, a too

strong film around the fat globules was formed and partial coalescence was impaired

(Leser and Michel, 1999).

Van Lent et al. (2008) investigated the differences between recombined creams made

of different protein sources: skimmed milk powder (SMP) and cream residue powder

(CRP) (Table 1.4). In SMP-creams casein micelles act as surface active material,

whereas in CRP-creams small molecular weight surfactants and whey proteins

stabilize the interface of the o/w emulsion. Moreover, more stabilization by CRP-

surface material per unit weight emulsifier is achieved than casein micelles do in

SMP-cream. With regard to fresh cream, smaller fat droplets and a larger whipping

time were observed than for SMP-creams and the freeze thaw serum leakage was

smaller than for SMP- and CRP-creams. It was concluded that CRP-creams mimicked

fresh cream better than SMP-creams.


20

Table 1.4: Differences in characteristics between recombined creams made of skimmed milk powder or cream residue powder (Van Lent et al., 2008) Characteristics SMP-cream CRP-cream Fat droplet diameter > Free protein content < Whipping time < Freeze-thaw serum leakage > Air phase fraction < Apparent viscosity > Creaming rate >

Scott et al. (2003) proved that the separation temperature in obtaining the emulsifying

components, skim milk or sweet buttermilk and butter derived aqueous phase, which

are generated after churning cream that is obtained by separation at 49 or 55°C,

mattered. Mimicked creams manufactured from components at a 55°C separation

temperature were more stable than those coming from a 49°C separation temperature,

perhaps because of the more efficient separation and inactivation of agglutinins that

might cause cold agglutination. Regarding the sensory analysis, the flavor of creams

formulated with sweet butter milk or butter derived aqueous phase were said to be

rich and creamy (Scott et al., 2003).

Besides the type and concentration of protein in the emulsion, the presence of small

molecular weight surfactants influences the susceptibility to partial coalescence.

Examples of small molecule surfactants are monoglycerides, diglycerides, and

polysorbates. Also phospholipids such as soy lecithin, exceeding a minimum

concentration, can render an emulsion more susceptible to partial coalescence upon

shearing action. Small molecule surfactants act as protein displacers, due to their

better surface active properties than proteins, which results in preferential migration to

the fat-water interface (Dalgleish, 2006). Consequently, the fat globules are no longer

covered by a thick stabilizing layer, break easier during whipping and more extensive

partial coalescence takes place (Segall and Goff, 2002). In conclusion, the fat globule

membrane should not be too strong because the aim of whipping is to destabilize the

emulsion (Van Lent et al., 2008; Mulder and Walstra, 1974), which can be obtained

by addition of small molecule surfactants, which are potential destabilizers of the

emulsion.

Small molecule surfactants might also act on the morphology of the fat crystals, e.g.

mono-olein (unsaturated MAG), which doesn’t show much protein displacement, but

it results in a cream that is more susceptible to partial coalescence (Fredrick et al.,


21

2010). Hotrum et al. (2005b) noticed shorter whipping times upon addition of small

molecule surfactants. In comparison to non-isolated whey products, caseins are more

readily displaced by surfactants, whereby water soluble surfactants are more effective

in doing this than oil-soluble surfactants (Cornec et al., 1998).

Instead of the application of small molecule surfactants, Goff (1997) promoted partial

coalescence by preparing an emulsion stabilized by milk proteins in such a

concentration that a weak yet sufficient interfacial layer stabilized the emulsion

during storage, which could be destabilized during a whipping process (Goff, 1997).

Additionally, additives that act on the properties of the continuous phase can be

added. Carrageenan in a concentration of 0.02% can prevent creaming by increasing

the viscosity. It reduces the drip volume in whipped creams without affecting the

whipping properties (Kováčová et al., 2010). Xanthan gum, an anionic

polysaccharide, increases the viscosity of the emulsion. In a concentration of 0.1% it

doesn’t affect the overrun (Zhao et al., 2009).

Concerning the stability of mimicked creams, Parkinson and Dickinson (2007)

suggested that the change of a 3wt% beta-lactoglobulin stabilized emulsion (45vol%

n-tetredecane, o/w-emulsion) into a 2.97wt% beta-lactoglobulin stabilized emulsion to

which 0.03wt% sodium caseinate was added, can improve the shelf-life of imitation

cream. The researchers observed an enhancement of long-term (up to 1.5 years)

stability, which was measured by looking at the phase separation.

1.5 Quality characteristics of whipped cream

Quality parameters of whipped cream are the increase in volume or overrun, the

whipping time or whipping rate, the texture of the whipped cream, its physical

stability (i.e. the extent of drainage and coarsening), and the chemical and

microbiological stability (De Meulenaer et al., 2009; Templeton and Sommer, 1932;

Lampert, 1975). An overview of the changes of some quality parameters during

whipping of cream is given in Figure 1.11.


22

Figure 1.11: Changes of some quality parameters during whipping of cream. The parameter of firmness is related to the time needed to lower a weight into the product. Leakage is the amount of liquid drained from a certain volume in a certain time. Between the broken lines the product is acceptable. Curves are approximate (Mulder and Walstra, 1974).

1.5.1 Overrun

Overrun depends on the effectiveness of the introduction of gas during the first stage

of whipping. According to Graf and Müller (1965) a well whipped cream should have

an overrun of approximately 50-60%. Overrun can be determined after a fixed time

period or the cream can be whipped until maximum overrun. Maximum overrun

corresponds with maximum stability and stiffness of the foam, and all air bubbles at

this point are encapsulated by coalesced fat droplets which adsorbed at the air-serum

interface (Jakubczyk and Niranjan, 2006).

The amount of emulsifier can affect the overrun, e.g. in a study of Zhao et al. (2008)

the highest overrun was obtained with 0.7% sodium caseinate in a recombined cream

that consisted of hydrogenated palm kernel oil, stabilizers, proteins, sucrose esters and

sugar slurry. As soon as the concentration exceeded 0.9% sodium caseinate, the foam

of the cream collapsed and hence the overrun decreased. Adding stabilizers, e.g.

0.05wt% λ-carrageenan or 0.1wt% locust bean gum (LBG) to a casein based dairy

cream decreases air incorporation capacity of the cream in comparison to creams

without these stabilizers. Despite this disadvantage, they also increase the serum

phase viscosity and interact with proteins in the cream, leading to a decrease of the

serum drainage and whipping time (Camacho et al., 1998).


23

1.5.2 Whipping time

The whipping time depends on the rapidity with which the partially coalesced

network of fat globules can be built up. Shorter whipping times are achieved when the

cream is whipped at higher rate (rotational speed of the whisks) (Hotrum et al.,

2005b). Templeton and Sommer (1932) defined the whipping time as the time needed

until desired stiffness, which was determined by observing the torque (load) on the

drive shaft of the whipping apparatus. In van Aken’s (2001) experiment, the endpoint

of whipping was set at the maximum of a peak in the electrical current, related to a

maximum of stiffness. Whipping time in the study of Van Lent et al. (2008) was

based on visual inspection, until a maximum overrun was reached. Ihara et al. (2010)

defined the endpoint of whipping as when a certain cone penetration depth was

reached.

A clear correlation exits between the whipping time (emulsion stability) and the solid

fat content of the emulsion (Darling, 1982) as shown in Figure 1.9.

Just like for overrun, the whipping time can be affected by the type and concentration

of emulsifier and stabilizer in the cream. In a study of van Hotrum et al. (2005b),

shorter whipping times were obtained with 1wt% whey protein isolate stabilized

emulsions than with 1wt% sodium caseinate. The mimicked cream consisted of

40wt% fat. Whey protein isolate (WPI) consists of mainly beta-lactoglobulin, which

forms brittle adsorbed layers at the air-water interface, whereas beta-casein forms

more fluid like layers. Addition of 2.7mM and 5.5mM Tween 20 to the mimicked

cream reduced the whipping time to such an extent that it was similar to the whipping

time of natural cream at the same rotational speed. The lower concentration of Tween

20 resulted in a higher overrun than the higher concentration (Hotrum et al., 2005b).

The lowest whipping time was obtained without locust bean gum or λ-carrageenan in

dairy cream, suggesting that these stabilizing additives cause kinetic hindrance to the

cream foaming, which could be due to not only the increase in the viscosity of the

liquid phase, but also to stabilizer-protein interactions that could partially inhibit the

foaming properties of milk proteins (Camacho et al., 1998).


24

1.5.3 Textural analysis

Whipping converts the viscous liquid emulsion into a stiff aerated viscoelastic solid

(Allen et al., 2008b). The viscoelastic behavior can be analyzed by measuring

rheological properties, the storage (G’) and loss modulus (G”), which both increase

when air is introduced (Jakubczyk and Niranjan, 2006). Also the viscosity,

cohesiveness and consistency are texture parameters. A back extrusion test and a flat

base plate rheometer can be used to study the structure of semisolid food and to

quantify the shelf life of whipped creams (Piazza et al., 2009; Allen et al., 2008b).

Differences in firmness and viscosity can exist between creams made of different

proteins. Zhao et al. (2008) found that creams with whey proteins were characterized

by a smaller increase in viscosity during whipping and a lower firmness after

whipping than sodium caseinate-whipped creams. The foam structure of dairy cream

can be better preserved during chilling when higher concentrations (>0.05%) of

additives such as λ-carrageenan or locust bean gum are applied. Higher cream

viscosities can be obtained with λ-carrageenan in comparison to locust bean gum, due

to protein-polysaccharide interactions (Camacho et al., 1998).

1.5.4 Physical stability

Just like emulsions, foams are never thermodynamic stable, the destabilization can

only be kinetically slowed down. Two (physical) destabilization processes can take

place: coarsening and drainage (Indrawati et al., 2008; Butt et al., 2006).

1.5.4.1 Coarsening of foam

During Ostwald ripening, which is a thermodynamically favourable process, diffusion

of gas through liquid films from small to large compartments is taking place, which is

driven by the pressure difference between them (Butt et al., 2006; Dalgleish, 2006).

The resulting phenomenon of coarsening or disproportionation can be slowed down

by having equally sized air bubbles, but this is not feasible with normal kitchen

equipment. Other options are increasing the viscosity of the liquid phase with


25

hydrocolloids or strengthening the interfacial layer around the gas bubbles with

surface-active proteins. Although globular proteins favor foam formation and stability

due to interfacial unfolding, the most successful way is to coat air bubbles with semi-

crystalline fat globules, undergoing partial coalescence at the air-water interface

(Dalgleish, 2006; Schmitt et al., 2005; Indrawati et al., 2008).

Coarsening can be studied by measuring the increase in transmitted intensity in a laser

light scattering-CCD camera experiment (Saint-Jalmes et al., 2005). Coarsening can

also be evaluated by microscopical image analysis, facilitated by low T (for

preservation of the original foam structure), scanning electron microscopy (SEM) and

computer assisted quantitative stereology (Smith et al., 1999).

1.5.4.2 Drainage

According to Belitz (2009), no serum separation should occur at 18°C after 1h in

order to have qualitative whipped cream. Due to the pressure difference between the

inside of a bubble and the liquid film, serum drainage or syneresis occurs. The

pressure inside the liquid film is significantly smaller than in the air compartments,

resulting in liquid being sucked into the ‘Plateau border’, which is the channel at the

contact line between liquid films (Figure 1.12).

Figure 1.12: Plateau border in foam (Butt et al., 2006)


26

Once the liquid reaches a Plateau border, the downward flow, driven by gravity,

becomes substantial (Butt et al., 2006). Liquid flow can be slowed down by increasing

the viscosity of the liquid, e.g. by adding xanthan gum, or by keeping the temperature

low (Mulder and Walstra, 1974; Indrawati et al., 2008).

In Table 1.5 a summary of different drainage analysis methods mentioned in literature

is given.

The serum leakage can also be determined after a freeze-thaw experiment, which is an

example of an accelerated stability test. In Van Lent et al. (2008) cups with whipped

cream were frozen at -18°C for 24h and placed upside-down on an aluminum dish at

16-18°C. After 15 min, the cup was removed and the cream weight was determined.

The serum was poured out and weighted after 150 minutes and the serum leakage

(ftSL) was determined as the mass of serum over the mass of whipped cream, times

100% (Van Lent et al., 2008).

Table 1.5: Overwiew of drainage analysis methods in literature Reference Drainage analysis method Allen et al., 2008b Serum drainage stability is the amount liquid drained under gravity from 10 g

sample over 5h period.

Templeton and Sommer, 1932

The drainage time is the time between placing the cream in a funnel and the first

drop of serum falling from the end of the glass stem of the glass funnel. The drain

amount is gravimetrically determined.

Van Aken, 2001 Serum loss was measured by placing 30g whipped cream on a sieve and measuring

the volume of serum leaking that passes through the sieve during 2h at 20°C.

Shamsi et al., 2002 40g whipped cream is immersed into a warm water bath at different temperatures

for 6h. Measurement of separated serum in mm.

Van Lent et al., 2008 The drainage stability was determined by placing 50g whipped cream on a sieve

with openings of 1mm. After 1h, at 16-18°C, serum leakage (SL) was determined

as the mass serum over the mass whipped cream, times 100%.

1.6 Factors determining functional properties of whipping cream

1.6.1 Temperature

During whipping of cream, the presence of a certain proportion of fat solidification is

crucial for partial coalescence of fat globules and firmness of the whipped cream,

hence, temperature is important (Figure 1.13).


27

Milk fat is a mixture of many different triacylglycerols (about 98%) with individual

melting points and thus it has an extensive melting range of -40°C to 40°C (Smet,

2010). Generally the fat should be partially solid at 5°C, solid enough at ambient

temperature and melt at temperatures below 37°C (Shamsi et al., 2002). Prior to

whipping, it is advised to keep cream, metal bowl and beaters below 7.2 °C (Lampert,

1975).

Figure 1.13: Effect of whipping temperature (in °C) on the firmness (yield stress, g/cm2) of whipped cream of different fat contents (%) (Mulder and Walstra, 1974).

1.6.1.1 Tempering

The stability of whipped cream, based on crystallizable oils with a large melting

range, can be enhanced by a process called cycling or tempering. This treatment

implies a temperature increase of the whipped cream to 25-30°C immediately after

whipping and subsequently the cream is cooled down. A clearly stiffened foam,

storable at 4°C for several weeks without any visible structural change (no fat or gas

segregation) can be observed, especially for native dairy creams with 20-40wt% fat

(Leal-Calderon et al., 2007). By contrast, non-tempered whipped cream collapses

already after 48h (Gravier et al., 2006).

In detail, the increase in temperature and a holding time of 5 minutes doesn’t melt all

of the crystals, hence the foam will not be collapsed. Upon cooling, the remaining

crystals serve as catalytic impurities, which results in a controllable nucleation and

increase in crystal size, which can be achieved without deep supercooling (Fredrick et

al., 2010). Drelon et al. (2006) could not relate tempering with polymorphism of fat

nor with an increase of the solid fat content. Though they could report a higher

increase of partial coalescence of whipped tempered creams upon whipping in

comparison to non-tempered whipped creams, which was measured by laser


28

diffraction after application of a heating step to transform the partially coalesced fat

globules into fully coalesced spherical fat globules (Drelon et al., 2006).

1.6.1.2 Heat treatment

The thermal treatment might have an effect on the whipping properties of cream.

Higher temperature pasteurization denatures whey proteins, which become unfolded

and interact with kappa-casein on the fat globules in order to form a complex that

makes the fat globules stable against partial coalescence (Bruhn and Bruhn, 1988;

Smith et al., 1999). Regarding gravitational stability, the complex formation is related

to a decreased creaming rate due to an increase of the density of the fat globules

(Parkinson & Dickinson, 2007).

UHT-treated cream exhibited larger fat globules than HTST-treated creams. The

former was associated with lower overrun and lower foam stability (Smith et al.,

2000).

1.6.2 Fat content

Whipped dairy cream should not contain less than 30% fat in order to form a stable

network capable of enclosing air bubbles. As illustrated in Figure 1.14, an increase in

fat content results in a shorter whipping time, a higher firmness and less serum

leakage (Mulder and Walstra, 1974), but a fat content of more than 38% decreases the

overrun and doesn’t improve the foam firmness any longer (Lampert, 1975). Whipped

creams with less 30% fat are characterized by a long whipping time and an increase of

the rate and extent of serum drainage (Templeton and Sommer, 1932).

1.6.3 Homogenization

During whipping of homogenized dairy cream, the fat globule membrane is

disintegrated twice. The first time happens when the cream is homogenized, resulting

in a newly formed membrane, the second time occurs when the cream is whipped.


29

The newly formed membrane gradually disintegrates and the liquid fat is released and

cements the remaining fat globules.

Figure 1.14: Properties of whipped cream. From left to right: whipping time (minutes), overrun (%), firmness, leakage of liquid (ml) as a function of fat content for conventional whipping cream ( ____ ) and for a cream with surfactants ( ----). Data are approximate (Mulder and Walstra, 1974).

Apart from the beneficial effect on the color (more white) (Hui et al., 2007) and the

creaming rate of cream by reduction of the fat globule size, homogenization impairs

whipping properties, particularly for a low fat cream: whipping time is much longer

and the foam is less firm. The clumping tendency of the homogenized fat globules is

probably too low, so more fat globules are needed to form a clump (Mulder and

Walstra, 1974).

Two-stage homogenization is used for the manufacture of recombined creams. The

first stage at higher pressure creates smaller fat globules, increases the rate of fat

globules collision and promotes the formation of heat-stable clusters (Figure 1.15),

which are more pronounced with increasing fat content and will separate much

quicker than non-aggregated fat globules (Mulder and Walstra, 1974). In the second

stage at lower pressure fat globules clusters are broken up, while avoiding the

destruction of the single fat globules.

1.6.4 Miscellaneous factors

Aging affects the rearrangement of the composition of the protein membrane in

homogenized cream (Darling, 1982) and it allows time for fat crystallization (Segall

and Goff, 2002).


30

Figure 1.15: Homogenization clusters in homogenized cream (Mulder and Walstra, 1974)

Chapter 2 Materials and methods

31

Chapter 2

Materials and methods

2.1 Commercial butters

Two types of commercial butters with a fat content of 82% were analyzed with the

Maran Ultra 23 spectrometer: an organic churned butter, Bio Karneboter (Delhaize)

and a cream butter, (Zachte) Ardense Roomboter (Carlsbourg), as illustrated in Figure

2.1. Bio Karneboter contains less than 0.1% salt and on the package of Ardense

Roomboter nothing is mentioned about the salt content. The salt content of salted

butters ranges from 0.5 to more than 3%, so the commercial butters used in this

experiment can be assumed to be non-salted.

Figure 2.1: Analyzed commercial butters: Ardense Roomboter and Bio Karneboter

2.1.1 Preparation of butter samples

Calibration of pfg-NMR requires a pure fat sample and a dispersed phase sample. The

separation of the phases was obtained by melting 125g of butter in an oven at 45-50°C

and by centrifugation at 2800g for 20 minutes, resulting in clarified butter oil at the

top and serum at the bottom of the recipient. Two glass NMR-tubes were filled to the

marked line (8mL) with fat and dispersed phase respectively, by using a syringe with

long needle to reach the separated phases.


32

Three glass NMR-tubes of each commercial butter were filled to the marked line

(8mL) with butter samples by using a cheese trier.

2.1.2 Analysis of butter samples

The samples at 5°C were analyzed in a Maran Ultra 23 spectrometer, which was set at

-7°C in order to get +5°C in the probe of the spectrometer. Water droplet size was

obtained with the software Droplet Size application (Resonance Instruments Ltd),

Excel and Matlab (see 2.3.3).

2.2 Water-in-oil emulsions

2.2.1 Materials needed for the preparation of w/o-emulsions

The materials used are a lipophilic emulsifier (polyglycerol polyricinoleate,

Palsgaard® 4150, Palsgaard A/S, Denmark), a hydrophilic emulsifier (sodium

caseinate, kindly provided by Armor Protéines, Saint Brice en Cogles, France), high

oleic sunflower oil (Hozol, Contined B.V., Bennekom, The Netherlands), soft-

palmitine mid fraction (Figure 2.2) (soft PMF, Unigra Sp., Conselice, Italy), a buffer

solution and an anti-microbial agent (sodium azide, Acros Organics, Geel, Belgium).

The buffer solution was made, according to the Henderson-Hasselbalch equation and

an aimed pH of 7, by mixing KH2PO4 (Merck KGaA, Darmstadt, Germany) and

K2HPO4 (Alfa Aesar, Karslruhe, Gemany) solutions of equal molarity (0.1M) in a

volume ratio 1:0.63. This pH avoids flocculation of sodium caseinate in the water

phase (I.E.P. is 4.6). By means of a pH-meter, the pH of the buffer solution at room

temperature was measured and amounted to 6.7. The difference in measured and

intended pH might be explained by the applied calibration liquids. Some emulsions

were made with whey protein isolate (WPI, BiPro, Davisco, Le Sueur, USA) instead

of sodium caseinate.


33

2.2.5 Composition of the w/o-emulsions

Different emulsions were obtained by varying the concentration of hydrophilic

emulsifier, lipophilic emulsifier, the composition of the oil phase and the water-to-oil

ratio.

Figure 2.2: Fractionation scheme of palm oil

The composition of different emulsions with 20% water (w/w) is represented in Table

2.1. In Table 2.2 shows the composition of emulsions with water to oil-ratios (w/w)

varying from 20% to 60%. The codes of the emulsions start with a letter,

corresponding to the first letter of the composition of the oil phase, followed by two

numbers, separated by a slash. The first number refers to the percentage (w/v) of

sodium caseinate in the water phase and the second refers to the percentage (w/v) of

PGPR in the oil phase.

The water phase was made by weighing sodium azide (all emulsions) and sodium

caseinate (some emulsions) in a volumetric flask and was filled with buffer solution to

the marked line. The oil phase was made by weighing PGPR in a volumetric flask and

filling with Hozol (at room temperature) or soft PMF (heated to 60°C) or both (at

60°C) to the marked line.

Palm Oil

Stearin fraction

Olein fraction

Hard stearin

Soft PMF

Super Olein

Hard PMF

Mid olein


34

Table 2.1: Composition of the 20% (w/w) W/o-emulsions (components in %, w/v)

W/o-emulsion H0/1 H0,5/1 P0/1 P0,5/1 P0,5/2 M0/1

Water phase

Sodium azide (%) 0.02 0.02 0.02 0.02 0.02 0.02

Sodium caseinate (%) 0.00 0,50 0.00 0,50 0,50 0.00

Buffer solution (pH 6.7) (%) ad 100 ad 100 ad 100 ad 100 ad 100 ad 100

Oil phase

PGPR (%) 1 1 1 1 2 1

Hozol (%) 99 99 0 0 0 49.5

Soft PMF (%) 0 0 99 99 98 49.5

Table 2.2: Composition of w/o-emulsions with different water to oil ratios. The oil phase consists of Hozol. The water phase contains sodium azide (0.02%, w/v) and a phosphate buffer (pH 6.7). Percentage water (%, w/w) in the w/o-emulsion 20 30 40 50 60 Water phase Sodium caseinate (%,w/v) 0.50 0.75 1.00 1.25 1.50 Oil phase PGPR (%, w/v) 1.00 1.50 2.00 2.50 3.00

2.2.6 Preparation of the w/o-emulsions

An Ultraturrax (type TV45, IKA) and a Microfluidizer (type M110S, Cobra

Engineering NL) (Figure 2.3) were used to premix and homogenize the emulsion at

60°C, respectively. To comply with the demands from good practicing when using the

Ultraturrax, about 75mL of emulsion was prepared, which comes down to weighing

52g oil phase and 13g water phase in a beaker. The Ultraturrax was set at position 1 to

2 and the emulsion was premixed for 1 minute. The emulsion was homogenized in the

Microfluidizer at an air pressure of 6bar for 1.5minutes. All emulsions were analyzed

in triplicate with a fresh emulsion prepared for each replicate.

When preparing an emulsion containing soft PMF or a mix, special care should be

given to preheat the Microfluidizer with boiling water, in order to prevent obstruction,

as presented in Flow chart 2.1.


35

Figure 2.3: Schematic representation of the Microfluidizer M110S: premixed emulsions (A) were filled into the reservoir (B) and cycled through the dissipation zone (C), cooled by passing the heat exchange coil (D) and then collected at the outlet by opening the valve (E) .

To assure that the ratio of water to oil in the very first collected emulsion samples

(after preheating), was 1:4, an oven test was conducted. The first six weighted

collected samples in weighted metal recipients with coverage were kept overnight at

105°C in an oven, by this removing the water phase. The difference in weight before

and after placing the samples in the oven, made it possible to calculate the w/o-ratio.

The outcome of the oven test suggested to start collecting the sample after preheating

and executing the first four steps of the Flow chart 2.1, followed by repeating twice

the third and fourth step. In other words, just after preheating, the first three collected

samples should be rejected. The next emulsions of the same and different composition

were collected by operating as illustrated in the Flow chart 2.1. The collected samples

in glass NMR-tubes (18mm outer diameter) were kept in the refrigerator for 24h and

covered with parafilm. After 24h all transport processes occurring are under

equilibrium conditions (Hindmarsch et al., 2005). Some hours before analysis, the

samples were kept at 5°C in a water bath (Julabo F12) filled with a mixture of glycol

and water.

Piston


36

Flow chart 2.1: A procedure for handling the Microfluidizer M110S

To collect samples with a different composition, execute STEP 1*:Fill the reservoir with 10mL premixed emulsion-> empty by opening the valve until the liquid level in the reservoir is ~1 cm,

then let the piston move to the right, stop circulation and suck the remaining liquid out of the reservoir with a syringethen execute STEP 2, 3 and 4*

To collect next samples with the same composition, execute STEP 2, 3 and 4*:

To collect the first sample: execute STEP 3then STEP 4* :

Fill the reservoir with 20mL premixed emulsion -> circulate for 1.5 min -> collect the sample from the second stroke of the piston onwards(reject the liquid from the first stroke of the piston)

Repeat twice STEP 3 and 4

STEP 4Fill the reservoir with 20mL premixed emulsion -> circulation for 1.5 min -> empty, by opening the valve until the liquid level in the reservoir is ~1 cm,

then let the piston move to the right, stop circulation andsuck the remaining liquid out of the reservoir with a syringe

STEP 3Fill the reservoir with 10mL premixed emulsion -> empty without circulation, by opening the valve until the liquid level in the reservoir is ~1 cm,


STEP 2Fill the reservoir with 20mL premixed emulsion -> circulate for 1.5 min -> empty by opening the valve until the liquid level in the reservoir is ~1 cm,


STEP 1Fill the reservoir with 20mL oil phase -> empty without circulation, empty by opening the valve until the liquid level in the reservoir is ~1 cm,


Preheat with boiling deionised water -> circulate -> empty by opening the valve until the liquid level in the reservoir is ~1 cm,then let the piston move to the right, stop circulation and

suck the remaining liquid out of the reservoir with a syringe

2.4 Quantitative particle size analysis of water in w/o-emulsions

2.4.1 Pulsed field gradient-Nuclear Magnetic Resonance

In order to characterize a w/o-emulsion, its particle size distribution was determined

by pulsed field gradient-Nuclear Magnetic Resonance (pfg-NMR). Pfg-NMR

measurements were conducted with a Maran Ultra 23 spectrometer. In the next

paragraphs, essential highlights of this method are given, clarifying its application to

determine the water droplet size distribution through its ability to measure restricted

molecular self-diffusion, as described by Packer and Rees (1972), Lönnqvist et al.

(1991), Lönnqvist et al. (1997), Johns (2009), Voda and van Duynhoven (2009), van


37

Duynhoven et al. (2002), Balinov et al. (1994) and Calliauw (2009). Reference is

made to the latter study for more detailed information about pfg-NMR.

Besides information with regard to characterization of the emulsion, one should notice

the relationship between water droplet size and sensorial properties and microbial

activity. The microbial activity is bigger in larger droplets, because more nutrients are

present. Further elaboration of this aspect is beyond the scope of this thesis.

2.3.2 The pfg-NMR experiment

NMR-spectrometry detects the emission of electromagnetic radiation by nuclei. The

nucleus of an atom absorbs energy of an applied magnetic field. Here, the nucleus of

the proton is studied for determination of the water droplet size distribution.

Pfg-NMR consists of a 90° and 180° radio frequency pulse and two pulsed field

gradients, as illustrated in Figure 2.4. Applying a 90° radio frequency pulse, which is

a rotating magnetic field, supplies energy to be absorbed, with a continuous spectrum

of frequencies. The pulse results in the fact that protons resonate at their Larmor

frequency, which isn’t the same for each nucleus, due to the difference in chemical

environment. The obtained NMR-signal will decrease as signals of protons dephase.

The 180° radio frequency pulse reverses the direction of the rotation of the protons,

which is called rephasing, which will be followed by dephasing. Together, the

rephasing and dephasing signal are called the spin echo signal. If protons resonate at

the same frequency before and after the 180° radio frequency pulse, the NMR-signal

will be maximum. Diffusion of protons attenuates the echo signal, because their

frequency changes due to the different perceived magnetic field. The application of

pulsed field gradients is needed to influence the spin echo signal, due to the diffusion

of protons, more pronounced. The gradients enlarge the differences of perception of

magnetic field and fasten up the dephasing. The stronger the gradients, the greater the

reduction in echo intensity. If there wouldn’t be any diffusion, after the second pulsed

field gradient, protons rephase at time 2τ, resulting in a maximum echo signal,

identical to the signal without gradient pulses. Hereby, τ represents the time between

the 90° and the 180° radio frequency pulse. Pulsed field gradients (Figure 2.4) are

characterized by a duration δ (s) and a strength g, which was fixed at 1.73953

Tesla/meter.


38

Figure 2.4: Schematic representation of the pfg-NMR diffusion experiment (Hindmarsh et al., 2005).

In the RINMR-software the δ-value was varied in 17 or 18 steps, which was done by

using the DSD.RIS.tif script and DSD_Lien.RIS.tif script. The latter script is an

adapted version of the DSD.RIS.tif script, from which the Droplist is altered. In the

Droplist of DSD_Lien.RIS.tif originally 19 δ-values (µs) were contained, but only for

18 values an output was given, because at δ=10000 µs, the duration of the gradient

pulse was too long with regard to the time interval of the two radio frequency pulses.

Hence, the δ-value of 10000 µs was dropped out of this Droplist. Running the script

with 18 δ-values takes about 10 minutes.

Droplist of DSD.RIS.tif script with 17 δ-values in µs: 400; 600; 800; 1000; 1250;

1500; 1750; 2000; 2250; 2500; 2750; 3000; 3250; 3500; 3750; 4000; 4500

Droplist of DSD_Lien.RIS.tif script with 18 δ-values in µs: 500; 750; 1000; 1250;

1500; 1750; 2000; 2250; 2500; 2750; 3000; 3250; 3500; 4000; 4500; 5000; 6000;

8000

Samples in glass NMR-tubes with outer diameter 18mm were filled until the marked

line (8mL) and analyzed at an aimed temperature of 5°C in the Maran Ultra 23

spectrometer. In the performed experiments the time between two gradient pulses (∆)

(Figure 2.4) amounted of 0.2s. As discussed in 2.3.3, two other parameters are needed

to calculate the water droplet size: the magnetogyric or gyromagnetic ratio (γ), which

for H-atoms is equal to 267518000 T-1s-1, and the bulk diffusion coefficient of water

in the dispersed fluid (D) at 5°C, which differs among different composed water


39

phases of the w/o-emulsion and was experimentally determined in the calibration

procedure.

2.3.2.1 Calibration procedure

Before analysis, a calibration procedure is needed, which is included in the mentioned

scripts in the RINMR software. First, a pure fat sample (without emulsifier) is used in

order to suppress NMR-signals coming from the fat phase. Secondly, pure deionized

water is used to be able to calculate the magnetic field gradient strength (g) from the

known bulk diffusion coefficient of deionized water (Dw=1.3253E-09 m2/s at 5°C)

and different values of δ. This is based on a pfg-NMR diffusion experiment that

acquires a set of data for each δ-value. Thirdly, a dispersed phase sample is used to

determine the bulk diffusion coefficient of water in this environment at 5°C, which

may be smaller than the diffusivity of pure water due to the presence of dissolved

molecules, such as emulsifiers and salts. Hereby D is calculated from the obtained

gradient strength (g) and a pfg-NMR diffusion experiment that results in a set of data

for each δ-value.

2.4.3 Restricted diffusion in w/o-emulsions

With regard to w/o-emulsions, the water molecules inside the dispersed phase are

characterized by restricted diffusion. This means that the mean displacement of the

liquid molecules inside the emulsion droplets is of the same order of magnitude or

larger than the diameter of the droplet. There is a limit to the amount of diffusion and

hence to the echo intensity reduction. If the movement of a molecule over relatively

short times is observed, the diffusion will be unrestricted. Observations over a longer

time, will result in a restricted diffusion because the molecule cannot move further

than the droplet diameter. By measuring the attenuation ratio of the NMR-signal at

different times, it is possible to identify when the diffusion becomes restricted and

estimate the droplet size distribution.

A function of the ratio (E) of the intensity of the echo signal I (with gradient pulses)

to I0 (without gradient pulses) has been described by Murday and Cotts (1968). The


40

function contains the following parameters: δ (duration of the gradient pulse), γ (the

magnetogyric or gyromagnetic ratio), ∆ (time between two gradient pulses), g

(gradient strength), D (bulk diffusion coefficient of water in the dispersed fluid) and

additional parameters λm (the mth-square root of a Bessel function) and R (the radius

of the water droplet):

2)2(

))(2exp()2exp(2)2exp(2))(2exp(222

1*

2)222(

1)222(

exp)E(R,

+∆−+−−∆−−−∆−+−

∑∞

= −−

=

Dm

DmDmDmDm

Dm

m mRm

g

λ

δλδλλδλ

λ

δ

λλγ

δ

Equation 2.1

The echo attenuation is smaller as the droplet size decreases (Figure 2.5). The use of

the bulk diffusion coefficient D of the dispersed phase is justified by the fact that only

two or three layers adjacent to the emulsion droplet interface have altered properties

as compared to the bulk.

0,0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

0,9

1,0

0 0,001 0,002 0,003 0,004 0,005 0,006 0,007 0,008 0,009

δ δ δ δ (s)

Ech

o at

tenu

atio

n ra

tio E

p (-

) 0.25µm

0.75µm

1.25µm

1.75µm

2.25µm

2.75µm

3.25µm

3.75µm

4.25µm

4.75µm

sample1H0.75/1.50 free H2Odiffusion

Figure 2.5: Calculated decay of the echo intensity of w/o-emulsions characterized by an R-value, δ (0s to 8ms) and D=1.30E-09 m2/s, and obtained from Equation 2.1 assuming γ=267518000T-1s-1, g=1.73953T/m and �=0.2s. Experimental decay of the echo intensity versus magnetic gradient pulse width of pure deionized water (Dw=1.3253E-09 m2/s) and of a w/o-emulsion (H0.75/1.5, sample 1) (D=1.289E-09 m2/s), both measured at 5°C (γ, g and � are identical as for pure deionized water).

Depending on the applied method of data processing, different equations are used in

order to get the water droplet size distribution, based on the measured echo intensities.


41

The three methods that are used, are the data processing method by the Droplet Size

application (Resonance Instruments Ltd), by Excel or by Matlab.

2.3.3.1 Data processing by the Droplet Size application

This method gives directly the volume-weighted arithmetic mean radius R43 (denoted

in the software as R33), the number-weighted arithmetic mean radius R10 (denoted in

the software as R00), the median radius Rmed of the number-weighted distribution

(denoted in the software as R0) and the distribution width σ. Assuming a lognormal

number-weighted distribution, Pn(R) is introduced, which is the probability

distribution of each droplet radius:

Pn(R) = (Rσ√(2π))-1exp[-(lnR-lnRmed)2/(2σ2)] Equation 2.2

where R is the radius (µm), σ is the distribution width and Rmed is the median radius

considering a lognormal number-weighted distribution, which equals the number-

weighted geometric mean radius. In addition, the distribution width σ corresponds to

the natural logarithm of the geometric standard deviation σg of the particle radius

distribution:

σ = lnσg Equation 2.3

In order to determine the droplet size distribution, the measured echo attenuation

ratios (I/I0), which are denoted as Ep(δ), are compared to the calculated echo intensity

ratios (Equation 2.4). This is done for each magnetic gradient pulse width δ, and by

means of a least-squares analysis the best estimates for Rmed and σ are obtained.

Ep(δ) = ( ∫(0-∞)R3Pn(R)E(R,δ) dR) /( ∫(0-∞) R3Pn(R) dR ) Equation 2.4

where Ep is the total attenuation of the NMR-signal of the population of possible

spherical droplet radii and E(R,δ) can be calculated by using Equation 2.5.


42

))(2

exp(2)2

exp(2))(2

exp(2)2

exp(22)2

(2

1*

)22(4)

222(

exp)E(R,

2222

2

4

+∆−+

−−

−∆−+

∆−−−

∑∞

= −−

=

R

Dm

R

Dm

R

Dm

R

Dm

Dm

R

m mm

R

D

g

δλδλδλλ

λδ

λλ

γ

δ

Equation 2.5

2.3.3.2 Data processing by Excel

This method gives the volume-weighted geometric mean diameter D33 and uses the

exported data from the Droplet Size Application and consists of 6 steps.

Firstly, echo attenuation ratios are calculated by implementing a certain droplet

radius, a δ-value, a set of λm values as well as values for D, γ, ∆ and g in Equation 2.1.

This is repeated for all δ-values that were used in the analysis, while keeping the

droplet radius constant.

Secondly, the echo attenuation ratios are calculated for another droplet radius for the

different δ-values, obtaining attenuation ratios as function of the droplet radius and δ.

This yields curves as shown in Figure 2.5, in which the relative positioning of the

measured and the calculated data can be observed. In the Excel file, the set of radii is

0.25; 0.75; 1.25; 1.75; 2.25; 2.75; 3.25; 3.75; 4.25 and 4.75 µm. Choosing a different

set of radii is possible, but time consuming. In Appendix A, a part from a data sheet in

Excel that represents the calculated echo attenuation ratios as a function of the radius

and δ of the emulsion H0.75/1.50 (sample 1) is represented.

Thirdly, in prospect of expressing the water droplet size in diameter and since the

lognormal volume-weighted probability distribution as a function of droplet radius is

equal to the lognormal volume-weighted probability distribution as a function of

droplet diameter, the latter will be used in the next equations. The relative frequencies

(P(ɸ)) for each droplet diameter ɸ are calculated and normalized

(Pnorm(ɸ)=Pnorm(Rx2)) by dividing it by the sum of the relative frequencies by using

Equation 2.6.


43

∑∑===

))((P )]/(2x2)ln(R -)exp[-(ln( )2 (

(R))(P (R)P

normv,normv,v

2233

-1

v

v )(P (R)P φ

σφπσφφ

Equation 2.6

Hereby, Pv represents the lognormal volume-weighted distribution and the following

parameters are brought in: the distribution width (σ), whose starting value is directly

obtained from the Droplet Size application, and the volume-weighted geometric mean

diameter D33 (or R33x2), whose initial guess is calculated by putting the number-

weighted geometric mean radius (Rmed) in Equation 2.7 and converting it to diameter.

The radius Rmed is directly obtained from the output of the Droplet Size application.

Equation 2.6 also needs an arbitrary diameter (ɸ).

R33= Rmed exp(3σ2) Equation 2.7

Fourthly, the echo attenuation ratios (Ep(δ)), that will be compared to the ones

measured, are obtained by multiplying the matrix consisting of rows with E values

corresponding to different δ-values and columns with E values corresponding to

different droplet radii (Appendix A) by the vector consisting of normalized relative

frequencies for the different droplet diameters (or radii). This operation boils down to

executing Equation 2.8, which is a modified version of Equation 2.4. The main

modification is the replacement of a number-weighted distribution in Equation 2.4 by

a volume-weighted distribution in Equation 2.8.

Ep(δ) = Σ [Pv, norm(ɸ) E(R,δ)] Equation 2.8

Fifthly, the sum of the squared differences between the calculated and the measured

echo attenuation ratios is calculated.

Sixthly, through ‘solver’ of Excel, the best fitting volume-weighted geometric mean

diameter D33 (or R33x2) and the distribution width (σ) are determined, so that the sum

of squared differences between the calculated and experimental echo attenuation ratio

is the smallest. The volume-weighted arithmetic mean diameter D43 is obtained by

using Equation 2.9. Also here, the distribution width (σ) is converted to the geometric

standard deviation (σg) by using Equation 2.3.


44

R43= R33 exp(σ2/2) Equation 2.9

Figure 2.6 illustrates relative normalized frequencies of a lognormal volume-weighted

distribution of the emulsion H0.75/1.50 (sample 1) as a function of particle diameter

class, which are obtained by calculation in Excel and by usage of R43 from the output

in the Droplet Size application, which is first converted to R33 by Equation 2.9 and

then included into Equation 2.6. A discrepancy between the lognormal volume-

weighted distribution by Excel and the Droplet Size application can be observed,

which might be due to the difference in Equation 2.1 and Equation 2.5.

Figure 2.7 illustrates the experimental and the best fitting calculated echo attenuation

ratios versus magnetic gradient pulse width (δ). To get a better fit, the product of

calculated normalized relative frequencies and calculated echo attenuation ratios is

multiplied by a factor (the multiplication factor MF (Equation 2.10)) which is also

included as a freely adjustable parameter in the solver.

Ep(δ) = Σ (MF)[Pv, norm(ɸ) E(R,δ)] Equation 2.10

The highest measured echo intensity at the smallest value for δ is considered as Io (the

echo intensity without gradient). This results in the fact that the ratio (E) of the echo

intensity I relative to Io, associated with the smallest δ-value, is allocated a value of

unity. As it is not possible to have an experimental point corresponding to a δ-value of

0µs, the measured relative echo decay data (Ei) are slightly overestimated, which can

be compensated by multiplication of the calculated data by a multiplication factor,

which is generally slightly larger than unity.

A major drawback of the Excel approach is that it includes only a limited number of

particle size classes, which are quite broad (especially in the low size region). This

will surely be problematic for samples with a rather narrow particle size distribution.


45

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

Relative normalized frequency

0 - 1

µm

1 - 2

µm

2 - 3

µm

3 - 4

µm

4 - 5

µm

5 - 6

µm

6 - 7

µm

7 - 8

µm

8 - 9

µm

9 - 1

0 µm

Particle diameter class

Excel

DSA

Figure 2.6: Relative normalized frequencies of the lognormal volume-weighted distribution of the emulsion H0.75/1.50 (sample 1) measured at 5°C as a function of particle diameter class, obtained by calculation in Excel according to section 2.3.3.2 and by inclusion of the output (σ and the R43) of the Droplet Size application (DSA) in Equation 2.6 after conversion of R43 to R33 via Equation 2.9 (γ=267518T-1s-1, g=1.73953T/m, �=0.2s, D=1.289E-09 m2/s).

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 0.001 0.002 0.003 0.004 0.005 0.006 0.007 0.008 0.009

δ (s)

Ep

(-)

Ep calculatedEp measured

Figure 2.7: Measured and calculated (using R33=3.0277µm, σ=0.0782 and MF=1.0448) echo attenuation ratio versus magnetic gradient pulse width (δ) of the emulsion H0.75/1.50 (sample 1) at 5°C (γ=267518T-1s-1, g=1.73953T/m, �=0.2s, D=1.289E-09 m2/s).


46

2.3.3.3 Data processing by Matlab

Also this method uses the exported data from the Droplet Size Application. The

difference between applying the Droplet Size application or Excel, lies in the fact that

this method is less cumbersome in terms of time consumption to result in an outcome.

Data processing by Matlab is based on the ‘inverse’ approach. Instead of calculating

the (lognormal) probability for a certain droplet size, which is done in Excel and the

Droplet Size application, a set of radii is calculated from the cumulative probability

(Figure 2.8), which ranges from 0.01 up to 0.99 with a fixed interval width of 0.01

units so that each radius has the same probability. In contrast, as stated in 2.3.3.2,

Excel uses only ten droplet diameters to calculate the lognormal probabilities (starting

from 0.5 µm in steps of 1 µm up to 9.5 µm diameter). This limitation results in the

fact that in Figure 2.8 only a few diameters out of ten are represented. For the sake of

clarity of Figure 2.8, only interval widths of 0.1 units are represented and to allow

comparison with Excel, the probability as a function of diameter instead of radius is

given.

In order to calculate the water droplet size, three files are used: Simulation_data.m,

Fitlien.m and Minim_Lien.m (Appendix B), where the latter actually refers to

Fitlien.m. The values for the free diffusion coefficient of water in the dispersed phase

and the gyromagnetic constant (γ), the reference to the Excel file, which contains the

values of the magnetic gradient pulse width (δ), the magnetic field gradient (g), the

measured intensities I and I0, are used in Simulation_data.m.

Firstly, the echo intensities I(δ,R) (where I refers to the echo intensity and R refers to

the radius that corresponds to the cumulative probability of a lognormal distribution),

are calculated by multiplying Equation 2.1 by I0. As initial guess for the parameter I0,

the experimental echo intensity obtained at the smallest δ is used. The radius is

calculated (and not arbitrarily chosen as in Excel or the Droplet size application) by

means of the inverse approach (Figure 2.8), based on the natural logarithm of the

geometric mean radius R33 of the lognormal volume-weighted particle radius

distribution (µ) and the natural logarithm of the geometric standard deviation σg of the

particle radius distribution (σ), according to Equations 2.11 and 2.12.

µ = ln(R33) = ln[R432/√(stdev2+ R43

2)] Equation 2.11

σ = ln(σg) = √[ln(stdev2/ R432 +1)] Equation 2.12


47

Thereby, stdev and R43 represent the arithmetic standard deviation and arithmetic

mean radius of the volume-weighted particle radius distribution.

Figure 2.8: Cumulative distribution of the diameter in micrometer (assuming a median diameter of 1.62µm and stdev of 0.2µm) with graphical representation of the two approaches: the horizontal arrows illustrate the inverse approach (used in Matlab) and the vertical arrows illustrate the direct approach (used in Excel).

Secondly, the echo intensities (Raccum(δ)) are obtained by the transformation of the

I(δ,R).

Thirdly, the file Fitlien.m calculates the best fitting volume-weighted arithmetic mean

radius (R43) (which is denoted as ‘mean’ in the Matlab file) and the arithmetic

standard deviation of the particle radius distribution (which is denoted as ‘stdev’ in

the Matlab file), so that the squared difference between the experimental echo

intensities I(δ) and calculated echo intensities (Raccum(δ)) is the smallest. Figure 2.9

is a graphical representation of the experimental and best fitting calculated echo

intensities versus magnetic gradient pulse width (δ). A logarithmic transformation of

the least squared difference results in the so-called maximum likelihood (MLH).

Matlab examines the possible combinations of means and standard deviation and

ceases its action when the lowest MLH is found.

The best fitting arithmetic standard deviation of the particle radius distribution is

converted to σg by using Equation 2.12.


48

0 1 2 3 4 5 6 7 8 9

x 10-3

1000

2000

3000

4000

5000

6000

7000

8000

Small delta (s)

Ech

o in

tens

ity

I(small delta)

Raccum(small delta)

Figure 2.9: Experimental (I) and best fitting calculated (Raccum) echo intensity (assuming R33=1.5596µm, σg= 1.0860 and I0= 7,72E+03) versus magnetic gradient pulse width (δ) of the emulsion H0.75/1.50 (sample 1), measured at 5°C. (γ=267518T-1s-1, g=1.73953T/m, �=0.2s, D=1.289E-09 m2/s).


It is assumed that water droplet sizes in w/o-emulsions are characterized by a

lognormal distribution. Whether a confidence interval of the mean of three volume-

weighted geometric mean diameters of three samples can be constructed, depends on

the distribution of the volume-weighted mean diameters. A small scale experiment

(Kolmogorov Smirnov-test, S-Plus) of replica’s with the same composition revealed

no rejection of the hypothesis of a normal distribution of the volume-weighted

geometric mean diameters on the 5% significance level. Hence, the construction of a

95% confidence interval of the mean of three volume-weighted mean diameters of

three samples is possible. The average of three samples for an emulsion, the 95%

confidence interval of the mean and the standard deviation of three samples are

calculated with Excel (Microsoft Office 2003).


49

Furthermore, parametric tests, which rely on the normal distribution, can be applied.

In order to compare the values of D33 between the three data processing methods or

compositions of emulsions, two-sample paired and two-sample independent sample t-

tests (Excel) are used, respectively. A significance level of 5% is applied. If more than

two groups need to be compared simultaneously, a Bonferroni correction (S-Plus) was

applied.

R-squared values are calculated in Excel and indicate the variability in a measured

data set that is accounted for by the calculated data set. For the Droplet Size

application and Excel, the calculated and measured echo attenuation ratios are

compared, whereas for Matlab, the echo intensities are compared. Whenever multiple

outcomes for the same sample were obtained, the outcome characterized by the

highest R-squared value was used in the statistical analysis.

2.4.5 Important issues during pfg-NMR analysis

2.3.5.1 Temperature of the emulsion during pgf-NMR analysis

Measurements should be done at a stabilized temperature, because diffusion data are

highly temperature sensitive. The Stokes-Einstein equation shows the connection

between temperature and diffusion coefficient:

D=kT/6πηR

where k is the Boltzmann constant, T is temperature, η is the viscosity and R is the

radius of a spherical particle. The diffusion coefficient increases at higher

temperatures because of the temperature effect on the viscosity. Samples are analyzed

at 5°C for having a maximum microstructural stability of the sample. At this

temperature, interdroplet water diffusion is minimized and only intradroplet diffusion

results in the attenuation of the NMR-signal (Van Lent et al., 2008a; Price, 1997;

Voda & van Duynhoven, 2009). Fourel et al. (1994) noted that as temperature

decreases, the standard deviation is approximately constant, but there is a large

decrease in mean diameter of the distribution, because then the condition of restricted


50

diffusion is better obtained. At higher temperatures, the continuous phase becomes

more permeable for the water and interdroplet diffusion becomes more interfering.

In conclusion, as long as the temperature is around 5°C and the calibration step is

performed at the same temperature, then the exact temperature is of less importance

than the stability of the temperature due to the adaption of the output to the

calibration.

2.3.5.2 Assumption of a lognormal size distribution

Systematic deviations between results of the fit and the experimental data can be due

to random errors or to the not completely appropriate assumed size distribution,

namely the lognormal size distribution. A way to cope with the fact that the

assumption of log normality cannot hold, is by modification of the equations. In a

study of Fourel et al. (1994) an unrestricted diffusion term was added to the equation

of Ep (Equation 2.4) to get better results in the case of no perfect lognormal

distribution of droplet size or in the case of existence of possible unrestricted

diffusion due to poor emulsification.

2.3.5.3 Advantages of pfg-NMR analysis for determination of water droplet size

In comparison of other methods, pfg-NMR has the advantage that the same samples

can be tested repeatedly, and dilution and centrifugation are not necessary. This non-

invasive technique is fast (about 10 min) and able to test opaque emulsions in which

the continuous phase is not conducting. However, there is a lack of a reference for

validation (Peña and Hirasaki, 2006).


51

2.5 Qualitative particle size analysis of water in w/o-emulsions

2.4.1 Fluorescence microscopy

Water droplets of w/o-emulsions are visualized with the water-soluble fluorescent

agent eosinY (MP Biomedicals Inc., Illkirch, France) and a fluorescence microscope

(Leitz Diaplan Incident light fluorescence 3-λ Ploemabak illuminator, Wild Leitz,

Germany) (Figure 2.10) equipped with Cell-software (Olympus Soft Imaging

Solutions GmbH, Germany).

Figure 2.10: Incident light fluorescence 3-λ Ploemabak illuminator. 1: lamp housing; 2: lamp housing mount; 3: BG38 red-absorption filter; 4: excitation light blocking slide; 5: field diaphragm; 6: filter block interchange control; 7: stop for twin wavelength study; 8: 3-lambda Ploemabak; 9: localization of the camera.

In this fluorescence microscope, light from a mercury lamp is filtered by an excitation

filter in the filter block, which reflects the light under an angle of 90° through the

objective lens on the sample. The excitation filter selects the incoming light or

excitation wavelength range. EosinY absorbs the light and emits fluorescent light. The

latter passes through the same objective and straight through an emission filter of the

same filter block towards the camera or binocular tubes. The emission filter selects

the emission wavelength range. The choice of filter block depends on the maximum

excitation and emission wavelength of the applied fluorescent agent. The applied filter

block (I2/3) passes excitation wavelengths between 450 to 490nm (BP450-490 or

band pass filter) and emission wavelengths above 520nm (LP520 or long-pass filter).

Depending on the settings, the microscope can be used as a fluorescence or polarized


52

light microscope. The fluorescence mode requires opening of filters nr.4 in Figure

2.10 and centration of the mercury or metal halide light by adjustment of the lamp

housing. Filter nr.3 (BG38) is a short-pass filter that passes excitation wavelengths

around 500nm, hence this resembles the excitation filtration of filter block I2/3.

2.4.2 Fluorescence

The fluorescence process comprises three steps (Figure 2.11). Firstly, the fluorescent

molecule is excited by absorption of a photon, which comes from the light source in

the fluorescence microscope or fluorimeter, by which the molecule moves from the

ground state to one of the vibrational levels of the exited state in 10-15 to 10-16s.

Secondly, vibrational relaxation (or internal conversion) occurs towards a lower

energy vibrational excited state without emission of light. This step takes

approximately 10-12s. Thirdly, by emission of a photon, the fluorescent molecule

returns to one of the levels of the ground state, which results in different emitted

photon energies. As a consequence, light is emitted over a range of wavelengths in a

time span of 10-9s.

Figure 2.11: The fluorescence process. S0, S1 and S2 stand for ground singlet state, first excited singlet state and second excited singlet state, respectively. Wavy arrows denote that the timescale is larger than for straight arrows.

The emitted light is characterized by a smaller energy and hence in accordance to the

law of Planck (E = hʋ = hc/λ), a longer wavelength than the light that leads to


53

excitation of the molecule. The difference in energy or wavelength between the

absorbed and emitted photon is called the Stokes shift. A large Stokes shift is

beneficial with regard to the sensitivity of the detector, because in this way by the

usage of filters, the excitation light that reaches the detector can be limited.

2.4.3 EosinY

EosinY or tetrabromo fluorescein is a red dye. Besides the usage as a coloring agent

in histological research and as a pharmaceutical product that dehydrates varicella-

blisters, eosinY can be used as a fluorescent agent (Figure 2.12). The letter Y is an

abbreviation of ‘yellowish’ due to the slightly yellowish shade. In contrast, eosin B

has a blue shade and is a dibromodinitro fluorescein derivate.

Figure 2.12: Chemical structure of eosinY (tetrabromofluorescein)

Although the aqueous solubility is 400g/L, the dissolution rate is quite low. Therefore,

a magnetic stirrer was used.

Repeating the analysis of the same sample in the fluorimeter or illumination by UV

and visible light results in repetitions of the excitation and emission cycle until the

fluorescent agent is destructed or photo bleached. Illumination decreases both

absorption and fluorescence. In a study of Kola (2010), within one day, fluorescence

of eosinY-solutions, which were stored in colorless glass in a light room, was found to

be destroyed for 98% and completely after 2 days. Even when the eosinY-solutions

were stored in brown colored flasks in a light room, 92% of the fluorescence intensity

is gone after 3 days. When the aqueous solutions were kept in brown flasks in the

shade, only 15% reduction of the fluorescence of eosinY was observed after 3 days


54

(Kola, 2010). Hence, the investigated eosinY-solutions in this study are covered with

aluminum foil.

Above pH 5.58, the fluorescence intensity is constant and higher than below this pH.

Regarding temperature, Kola (2010) demonstrated that the fluorescence intensity is

stable within the studied temperature range of 10°C to 41°C.

Stockert et al. (1994) found that the addition of sodium azide to eosinY-solutions

might create new absorption (520nm) and emission (478nm) peaks. Seema and

Babulal (2009) reported on the interaction between eosinY and some surfactants other

than sodium caseinate. Therefore, the spectrofluorimetric behavior of eosinY in the

presence of sodium caseinate was investigated.

2.4.4 Fluorimetric analysis of w/o-emulsions

2.4.4.1 Fluorimeter

A fluorimeter (Varian fluorescence spectrophotometer, Cary Eclipse) was used to

perform preliminary investigation of aqueous eosinY-solutions in the presence of

different agents. As such, the influence of addition of a phosphate buffer, sodium

azide and sodium caseinate to the aqueous solution on the maximum excitation and

emission wavelength of eosinY was examined.

2.4.4.2 Determination of a suitable concentration of eosinY

A suitable concentration of eosinY in distilled water that is associated with high

fluorescence intensity was looked for. This concentration is used in the water phase of

the w/o-emulsion (50:50, w/w) for fluorescence microscopic investigation. The

software tool ‘Concentration’ of Cary Eclipse was applied. The limitation that the

fluorimeter becomes saturated at very high fluorescence intensities must be taken into

account and forces the quest for a suitable concentration of eosinY to be done at sub

maximum excitation and emission wavelengths. On the basis of Figure 2.13, an

eosinY concentration of 10µg/mL was chosen for the water phase in emulsions.

Linear regression on the first nine data points results in y=537277x-11 and R2=0.93.


55

0.1

1

10

100

1000

1.0E-08 1.0E-07 1.0E-06 1.0E-05 1.0E-04 1.0E-03 1.0E-02 1.0E-01 1.0E+00

Eosin Y concentration (g/100mL)

Flu

ores

cenc

e in

tens

ity (

a.u.

)

Figure 2.13: Fluorescence intensity as a function of the logarithm of eosinY concentration in water. Excitation wavelength=514nm. Emission wavelength= 564nm.

2.4.4.3 Determination of maximum excitation and emission wavelength

By application of the 3D Mode and selection of the Excitation or Emission-button in

the software tool ‘Scan’ of Cary Eclipse, the maximum excitation or emission

wavelength can be determined, respectively. During the scan, the fluorescence

intensity, which is related to a predetermined range of excitation wavelengths for a

predetermined range of emission wavelengths, is recorded. At an emission

wavelength of 480nm the intensity is measured for excitation wavelengths from 480

to 600nm. The next scan measures the intensity at an emission wavelength of 482nm.

Scanning is proceeded until the emission wavelength of 600nm. The highest recorded

intensity corresponds to the scan at the maximum emission wavelength. An example

of an excitation spectrum scan is represented in Figure 2.14, in which excitation and

emission range from 480 to 600nm in steps of 2nm. Fluorescence intensity is

indicated by different colored regions, which is defined as the y-axis of the spectrum.

High fluorescence intensity (or red colored regions) gives an idea about the range of

the maximum excitation and emission wavelength and can be read from the x-axis

and z-axis, respectively. The z-axis represents the number of steps between the lowest

and highest analyzed emission wavelength. In this example, the maximum unit on the

z-axis is 60, since the difference between 600 and 480nm amounts of 120nm and the

size of the steps is 2nm. Conversion of units on the z-axis to the emission wavelength

in nanometer is done by Equation 2.13. Analogously, in an emission spectrum, the


56

excitation wavelength can be calculated from the units on the z-axis. Hereby, the x-

axis and y-axis represent the emission wavelength and fluorescence intensity,

respectively.

Emission wavelength (nm) = [(Z-axis units)(size of the steps to go from the first to the

last selected emission wavelength) + lowest analyzed emission wavelength (nm)]

Equation 2.13

480 500 520 540 560 580 6000

200

400

600

800

1000

W avelength (nm)

Inte

ns

ity

(a

.u.)

51

8.0

5 ,

13

2.5

12

Z A

xis

Wavelength (nm)

5.00

10.00

15.00

20.00

25.00

30.00

35.00

40.00

45.00

50.00

55.00

60.00

480.00 490.00 500.00 510.00 520.00 530.00 540.00 550.00 560.00 570.00 580.00 590.00 600.00

962.92888.75814.58740.41666.24592.07517.91443.74369.57295.40221.23147.0772.90-1.27

Figure 2.14: Contour plot of the scan for excitation and emission wavelength ranging from 480 to 600nm in 60 steps of 2nm. X-axis: excitation wavelength (nm). Z-axis: number of steps that are used to go from 480 to 600nm emission wavelength. Red color denotes high fluorescence intensity, green color denotes low fluorescence intensity. Eosin concentration in distilled water is 5µg/mL.

Concerning the determination of the maximum excitation and emission wavelength, a

concentration of eosinY in water of 5µg/mL was used and can be performed in two

ways. In the case that the maximum excitation wavelength must be determined, the

first method consists of narrowing down the emission wavelength range which lies

symmetrically around the maximum emission wavelength. However for determination

of the maximum excitation and emission wavelength, Sometimes a lower

concentration of eosinY must be analyzed to avoid approaching the maximum

recordable fluorescence intensity. The second method comprises the measurement of

the fluorescence intensity by shifting the narrowed range of emission wavelengths to

sub maximum regions. Hence, the maximum recordable fluorescence intensity is not

reached. The eosinY-concentration is left unchanged. In the case that the maximum


57

emission wavelength must be determined, the same reasoning applies, but now the

excitation wavelength range must be narrowed down.

An example of such an excitation spectrum is given in Figure 2.15, for which the

maximum excitation wavelength matches 517nm. As the emission wavelength was

located at sub maximum regions, this is an example of the second method. Eleven

different cultured lines can be observed because the emission wavelength is elevated

from 554nm to 564nm in steps of 1nm.

Figure 2.15: Graphical representation of the determination of the maximum excitation wavelength of eosinY at a concentration of 5µg/mL. Excitation wavelength range: 490-540nm. Emission wavelength range: 554-564nm.

In order to demonstrate that the maximum excitation or emission peak at different

suboptimal emission or excitation wavelengths, respectively, is located at the same

wavelength, the maximum emission was recorded at different ranges of sub maximum

excitation wavelength as depicted in Table 2.3. No deviating trends could be

observed. The average and standard deviation of the nine maximum emission

wavelengths is 547nm and 0.7nm, respectively. Hence, identical outcomes can be

achieved at excitation wavelengths that are 67nm (527nm minus 460nm) lower than

the maximum excitation wavelength.

In order to test the repeatability of the fluorimetric analysis, the same sample was

repeatedly analyzed at the same excitation wavelength range of 480 to 490nm. The

average maximum emission wavelength and standard deviation of ten repetitions was

547.2nm and 0.7nm, respectively.


58

Table 2.3: Recorded maximum emission wavelengths at different excitation wavelength ranges of eosinY (5µg/mL) in aqueous phosphate buffer (pH6.7) with sodium azide (0.02%,w/v) and sodium caseinate (1.25%,w/v). Excitation range (nm) Max. emission wavelength (nm)

500-510 547 495-505 548 490-500 548 485-495 547 480-490 547 475-485 546 470-480 546 465-475 547 460-470 547

2.4.5 Confocal laser scanning microscopy

Two major differences between fluorescence microscopy and confocal laser scanning

microscopy (CLSM) are the depth selectivity and the applied light source. Whereas

fluorescence microscopy detects fluorescence of all layers in the specimen, images by

CLSM can be taken of a selected layer or depth of the specimen. This is achieved by

focusing the laser beam, which is the light source, by an objective lens into a certain

volume of a certain layer of the specimen whereby the emitted light from other layers

does not reach the detector due to the presence of a detector-aperture (Figure 2.16).

Figure 2.16: Schematic representation of the principle of confocal laser scanning microscopy


59


2.9.3 Composition of the w/o/w-emulsions

Depending on the preparation method, 70g or 100g of w/o-emulsion (50:50, w/w) was

prepared. Addition of the external water phase to a w/o-emulsion in a ratio 40:60

(w/w) gave rise to a w/o/w emulsion.

The water phase of the w/o-emulsion contained 1.25% (w/v) sodium caseinate, 0.02%

(w/v) sodium azide, 0.001% (w/v) eosinY and a phosphate buffer (pH6.7). The fat

phase consisted of 2.5% (w/v) PGPR in soft PMF or a mix of soft PMF and Hozol.

Here, eosinY is added to ameliorate the visualization of the internal and external

water phase. Unless stated differently, the external water phase only differs from the

internal water phase in the concentration of sodium caseinate (1%, w/v) and the

absence of eosinY.

2.9.4 Preparation of the w/o/w-emulsions

Four manufacturing methods were attempted, which differed in the utilized apparatus

and the modus of sampling.

2.9.4.1 Method A

This method entails subsequent application of an Ultraturrax TV45 (until visual

satisfaction) and a Microfluidizer M110S (at 6bar for 1.5 minutes) in order to

fabricate 100g of w/o-emulsion (50:50, w/w) with soft PMF as the fat phase. W/o-

emulsions were kept in a water bath of 50°C before mixing of the external water

phase with an Ultraturrax (for 0.5 minutes) and Microfluidizer (at 1bar for 1.5

minutes) in prospect of making a double emulsion. The samples were collected in

glass NMR-tubes with an outer diameter of 18mm, filled for 40mm height (or 8mL),

covered with parafilm and cooled in an ice bath. Prior to NMR-analysis, samples were

vortexed and meanwhile maximum 100µL 10mM MnCl2 (Normapur,

VWRinternational, Fontenay sous Bois, France) was added to 8mL emulsion.


60

2.9.4.2 Method B

This method comprises the generation of 70g w/o-emulsion by an Ultraturrax TV45.

Fourty grams of w/o-emulsion were blended with 60g of external water phase with an

Ultraturrax S25-10G (Figure 2.17) at 24000rpm for 2 minutes, unless stated

differently. In a few samples, the concentration of sodium caseinate was 1.25% (w/v)

instead of 1% (w/v) (2.5.2) in the external water. The type of fat phase is mentioned

for each experiment. Afterwards, double emulsions were further mixed with a

continuous Ultraturrax DK25 (Figure 2.17) at 24000rpm for a specified time. The

advantage of the latter type of Ultraturrax is the reduction of foam formation and

hence higher availability of surfactant to stabilize the emulsion instead of air. Unless

stated differently, samples were cooled in an ice bath. For NMR experiments, the

samples were filled in NMR-tubes up to 40mm with an outer diameter of 18mm and

received MnCl2 directly after production or just before NMR-analysis. The latter

required vortexing.

Figure 2.17: Construction of a continuous Ultraturrax DK25 flow chamber (bottom) and an Ultraturrax S25-10G (top)


61

2.9.4.3 Method C

The third method differs from the previous methods only in the filling of the NMR-

tubes. NMR-tubes with an outer diameter of 18mm, were filled in such a way that the

detection zone of the spectrometer with a length of 25mm (Zhu, 2011) (Figure 2.18)

comprises the complete sample. It is chosen to fill the tube for 15mm, which means

that it needs to be elevated for 27mm in the spectrometer by means of wrapping a

rubber band around the tube. Right after production, 28µL 10mM MnCl2 is added to

3mL of emulsion and vortexed. In this manner, errors owing to improper

homogenization of the creamy layer by vortexing are avoided.

Figure 2.18: The detection zone (red) of a Maran Ultra 23 spectrometer lies between 22mm and 47mm height (Zhu, 2011). Hence, incompletely filled tubes (e.g. considering 15mm of sample) must be elevated (e.g. over 27mm) to enable the detection of their whole contents. Regarding the effect of the elevation of a tube in the Maran Ultra 23 spectrometer on

the T2-distribution, Figure 2.19, 2.20 and 2.21 illustrate the location of the detection

window. Elevation for 0cm, 0.75cm, 1.5cm, 3cm, 4cm, 5cm and 6cm of an NMR-tube

in the Maran Ultra 23 spectrometer was realized by means of a rubber band. To a

double emulsion with P1.25/2.5/1, 75µL of 10mM MnCl2 was added to a 4cm height

filled NMR tube (about 8mL) right after production. Twenty four hours later, analysis

was performed on the phase separated sample, that was not vortexed.


62

According to Zhu (2011), the detection window of the Maran spectrometer is situated

between 2.2 and 4.7cm above the bottom. As long as the sample is located in the

detection zone of the spectrometer and the signal is maximized by optimization of the

receiver gain, the total area under the curve stays constant. Upon elevation, the area

under the curve that is related to the fat phase and internal water decreases, whereas

the area under the curve of external water increases. The fat globules with internal

water are enriched at the top of a phase separated sample, whereas the external water

content is higher at the bottom of a tube.

Figure 2.19: Schematic representation of the experiment concerning the elevation of the NMR-tube in the Maran Ultra 23 spectrometer. P1.25/2.5/1 with 75µL of 10mMMnCl2 in a 4cm filled (about 8mL) NMR-tube of 1.8cm diameter, added directly after production. (P/A 1-3/03/11)

The fact that at an elevation of 5cm a signal could still be received, might be due to

the inaccurate elevation by means of the rubber band or a broader detection window

than 2.5cm. In order to assess the detection zone a small experiment was performed.

An NMR-tube of 18mm outer diameter was gradually filled with water from 0 to

12mL with a pipet. For each water volume the area under the curve in the T2-

distribution was plotted versus the water volume in the tube (Figure 2.22). By linear


63

regression it was found that the area under the curve linearly increases with a water

volume of 3.7 to 9.2mL, which can be converted to a detection window of 20.5 to

50.5mm (5.51mm/mL). Based on this experiment, the width of the detection window

is 3.0cm, which can explain the recorded signal at 5cm elevation in Figure 2.21.

However, close to the detection window margins, more inaccuracy can be noticed

(Zhu, 2011), hence the detection zone of 2.2cm to 4.7cm can still be applied.

0

200

400

600

800

1000

1200

1400

1600

1800

1 10 100 1000 10000

Time (ms)

Sig

nal a

mpl

itud

e

0cm elavation

0.75cm elavation

1.5cm

3cm elavation

4cm

5cm elevation

6cm elevation

Figure 2.20: T2-distribution of samples at different heights in the Maran Ultra 23 spectrometer. Black arrows denote the direction of change upon elevation. P1.25/2.5/1, 75µL of 10mM MnCl2 after production. (P/A 1-3/03/11).

0

2000

4000

6000

8000

10000

12000

14000

16000

0 1 2 3 4 5 6

Elevation of the NMR-tube (cm)

Are

a un

der t

he c

urve

Fat phase

External water

Internal water

Total AUC

Figure 2.21: Area under the curve for different relaxation modes and elevation of the NMR-tube. P1.25/2.5/1 with 75µL of 10mM MnCl2 directly added after production. (P/A 1-4/03/11)


64

02000400060008000

1000012000140001600018000

0 2 4 6 8 10 12

Water volume (mL)

Are

a un

der t

he c

urve

Figure 2.22: Area under the curve in the T2-distribution versus water volume in an NMR-tube of 18mm outer diameter. Receiver gain of the spectrometer was kept constant (RG=1.64). 2.9.4.4 Method D

Method D is a combination of Method B and C. This method is similar as Method B

regarding the preparation of a w/o-emulsion, but besides an Ultraturrax TV45 (until

visual satisfaction), also a Microfluidizer (at 6bar for 1.5 minutes) is utilized in order

to make a w/o-emulsion. The w/o/w emulsion is made exactly like in Method B. The

filling of the NMR-tube is done as in Method C.

2.10 Quantitative analysis of the enclosed water volume and yield of water-in-oil-in-

water emulsions

2.10.1 The CPMG-experiment

The enclosed water volume was estimated by transverse relaxation time constant (T2)

distribution measurements via CPMG-experiments (Carr Purcell Meiboom Gill) in the

presence of MnCl2 with a Maran Ultra 23 spectrometer. The temperature of the

samples was +5°C and the Set Temperature of the spectrometer was -7°C. One radio


65

frequency pulse of 90° is applied and N radio frequency pulses of 180°, which results

in N spin echoes or CPMG spin-echo trains (Figure 2.23).

Figure 2.23: The CPMG-experiment The basis of an NMR experiment is the change of the total magnetic moment or

magnetization of a sample, which can be represented in a xyz-space. Without pulses,

the magnetization vector is aligned with and precesses about the static field B0 or z-

axis. Application of a 90° pulse (radio frequency pulse or B1) puts the magnetization

vector (M0) into the xy-plane (Figure 2.24). All spins experience the same applied

pulse and are in phase along the y-axis.

Figure 2.24: Change of the magnization by a 90°pulse, without 180°pulses. The magnetization vector aligns back with the static field B0 over time scales of T2. Without subsequent 180° pulse, the magnetization vector is completely restored along

the z-axis. More into detail, over time scales of T2, the spins lose phase coherence in

the xy-plane due to differences in magnetic field in the sample (spin spin interactions)

or inhomogeneity in the magnetic field. Because the dephasing is measured in the xy-

plane, which is perpendicular to the z-axis, this is called a transverse magnetization

experiment. Alternatively, the loss of coherence can also be observed along the z-axis,


66

which happens over time scales of T1 and is denoted as the recovery of the

longitudinal magnetization.

Application of a 180° pulse flips the magnetization vector around the y-axis (Figure

2.25). The so-called spin isochromats are bundles of spins that experience the same

magnetic field. The sum of the spin isochromats is equal to M0 or magnetization

vector at equilibrium, which is equal to the magnetization vector M when aligned with

the static field B0. As each spin isochromat continues to precess with its frequency, all

isochromats will rephase. This rephasing removes the influence of inhomogeneity of

the magnetic field on the spins, hence the change of magnitude of the echo will be due

to the spin spin interactions only.

Application of multiple 180° pulses, results in multiple echos, from which the

magnitude further decreases as more pulses are applied (Figure 2.23). The amplitudes

of the decaying spin echoes as a function of time yield an exponentially decaying

curve, which is characterized by a time constant T2.

Figure 2.25: A 90°x pulse puts M0 into the Y-direction (a). Spin isochromats fan out with time (b). A 180°y pulse rotates the spins around the Y-axis (c). Rephasing of the spins results in an echo (d). The difference of magnitude of M in (d) and (a) is a direct measure of T2.

After running a script (Appendix C), this (experimental) relaxation time curve (Figure

2.23) is recorded by the software RINMR. Unless stated differently, the receiver gain

(RG), which is a parameter that maximizes the signal, is optimized automatically prior

to analysis. The calculated NMR is obtained after uploading the experimental data in

the software WinDXP and exporting them to Excel (Appendix D). The x-axis or time-

axis of the relaxation time curve (Figure 2.26) increases from 403.95µs in steps of

400µs to 3276804µs. The y-axis, which represents the relaxation magnitude, differs


67

among samples. The decay can be mono or bi-exponential, depending on the different

water phases present and their differentiation with the paramagnetic agent MnCl2. A

stock solution of 10mM MnCl2 in water was prepared. This compound reduces the T2-

relaxation time of water in contact with it and therefore decays faster. In a double

emulsion, MnCl2 will only end up in the external water phase, on the condition that

there is no exchange of water between both water phases through the fat phase. If no

distinction between the internal and external water phase of a double emulsion is

made, e.g. in the absence of MnCl2 (Figure 2.26, red curve), or if only an internal

water phase is present, e.g. in w/o-emulsions, then a mono exponential decay is

acquired. A bi-exponential decay is achieved for w/o/w emulsions after addition of

MnCl2. The fast and slow decaying part of the bi-exponential curve (Figure 2.26,

black curve) are associated with the external and internal water of the double

emulsion, respectively.

0

2000

4000

6000

8000

10000

12000

14000

0 500 1000 1500 2000 2500 3000 3500

Time (ms)

Rel

axat

ion

mag

nitu

de Experimental NMR data+ MnCl2

Calculated NMR data + MnCl2

Experimental NMR data- MnCl2

Calculated NMR data - MnCl2

Figure 2.26: CPMG T2-relaxation decay profile of a w/o/w emulsion P1.25/2.5/1. Before (-MnCl2) and after (+MnCl2) addition of 100µL 10mM MnCl2. to 8mL sample, P/A: 25-26/02).

By means of illustration, the CPMG T2-decay for various emulsions is represented in

Figure 2.27. Fast decays are associated with T2-analysis of the fat phase. Irrespective

of the fat phase, a bi-exponential decay is obtained for double emulsions upon

addition of 75µL 10mM MnCl2 to 8mL sample. A mono-exponential decay can be

observed for w/o/w emulsions with an insufficient amount of MnCl2, which comes

down to an addition of less than 75µL 10mM MnCl2 to 8mL sample.

Contin analysis of the relaxation time curve creates a T2-distribution (Figure 2.28)

time scale goes up from 100µs to100s, where the increase occurs in steps of (t3-


68

t2)=(t2-t1)*1.056. A T2-distribution can be constructed directly with the raw data from

the relaxation time curve in the software WinDXP or can be rebuilt by exporting the

data from WinDXP to Excel (Appendix D). Irrespective of the volume of the sample

in the NMR-tube, the total area under the curve is approximately constant.

Figure 2.28 (red curve) reveals that without MnCl2, only one peak associated with

water is observed at a T2 of about 1s. This peak comprises both the external and the

internal water. By addition of MnCl2 the water peak is split into two peaks

corresponding to the external and internal water (Figure 2.28, black curve): the

transverse (T2) relaxation time will be longer for water molecules within the fat

droplets of the double emulsions than when present in the external water phase to

which MnCl2 is added.

0

2000

4000

6000

8000

10000

12000

14000

16000

0 200 400 600 800 1000 1200 1400

Time (ms)

Rel

axat

ion

mag

nitu

de

W/o (P1.25/2.5)

Fat phase: soft PMF+2.5%(w/w) PGPR

W/o/w, insufficient MnCl2(P1.25/2.5/1)

W/o/w, no MnCl2(P1.25/2.5/1)

W/o/w, MnCl2(M1.25/2.5/1)

W/o/w, MnCl2(P1.25/2.5/1)

1

10

100

1000

10000

100000

0 200 400 600 800 1000 1200 1400

Time (ms)

Rel

axat

ion

mag

nitu

de

W/o (P1.25/2.5)

Fat phase: soft PMF+2.5%(w/w) PGPR

W/o/w, insufficient MnCl2(P1.25/2.5/1)

W/o/w, no MnCl2(P1.25/2.5/1)

W/o/w, MnCl2(M1.25/2.5/1)

W/o/w, MnCl2(P1.25/2.5/1)

Figure 2.27: CPMG T2-decay profiles for various emulsions on a linear scale (Top) and a logarithmic scale (Bottom). A w/o/w emulsion with insufficient MnCl 2 signifies an addition of less than 75µL 10mM MnCl2 to 8mL sample. In w/o/w emulsions P1.25/2.5/1 and M1.25/2.5/1 (ratio (soft PMF/Hozol)=3/1), 100µL and 28µL 10mM MnCl2 was added to (vortexed) 8mL and (non-vortexed) 3mL, respectively.


69

Typical T2-relaxation times for water in the absence of MnCl2 amount to 1s, whereas

the relaxation time of the water in contact with MnCl2 can be found at about 100ms.

An additional peak at about 10ms embodies the hydrogen atoms in the liquid part of

the fat phase. Hence, a T2-distribution of a double emulsion is defined as a trimodal

distribution, which is characterized by three modal relaxation times (small, medium

and large) and a signal amplitude of the modes.

0

100

200

300

400

500

600

700

1 10 100 1000 10000

Time (ms)

Sig

nal a

mpl

itude

W/o/wwithoutMnCl2

W/o/wwithMnCl2

Figure 2.28: T2-distribution of a w/o/w emulsion (P1.25/2.5/1) with and without addition of 100µL 10mM MnCl 2 to 8mL sample (or filled for 40mm) (P/A: 25-26/02).

Figure 2.29 shows the T2-distributions of the emulsions shown in Figure 2.27. A w/o-

emulsion and a w/o/w emulsion in the absence of MnCl2 are characterized by a

similar T2-distribution. Considering the former emulsion, the relative ratio of the peak

associated with fat to the peak associated with water is larger than in the latter

emulsion, which is in accordance to their difference in mass ratio of the mixed fat

phase to water phase. As discussed in section 2.2.3, the mass ratio could be

determined by an oven test. Extraction of the mass ratio from the T2-distribution is

more cumbersome in terms of the requirement of additional information and could be

assessed in two ways. Firstly, the area under the peak that is associated with fat in the

T2-distribution of a w/o-emulsion can be divided by the area under the peak in the T2-

distribution of only fat phase. For example, the data of the w/o-emulsion exhibited in

Figure 2.29 render a mass ratio fat/water of 40%, whereas in theory this would be

50%. The discrepancy might be explained by the difference in solid fat content

between a pure fat sample and a w/o-emulsion at the same temperature. Secondly,

calculation of the fat fraction can be performed on the basis of one T2-distribution,


70

whereby the knowledge of the percentage of relaxing protons in the fat and water

phase is required.

Also from Figure 2.29, the T2-distribution of the w/o/w emulsion with insufficient

MnCl2 can be regarded as a transition between the T2-distribution of w/o/w emulsions

in the absence and MnCl2 and w/o/w emulsions with sufficiently added MnCl2.

0

100

200

300

400

500

600

700

800

1 10 100 1000 10000

Time (ms)

Sig

nal a

mpl

itude

W/o (P1.25/2.5)

Fat phase: softPMF+2.5%(w/w)PGPR

W/o/w,insufficientMnCl2(P1.25/2.5/1)W/o/w, no MnCl2(P1.25/2.5/1)

W/o/w, MnCl2(M1.25/2.5/1)

W/o/w, MnCl2(P1.25/2.5/1)

Figure 2.29: T2-distribution for the various emulsions shown in Figure 2.27. A w/o/w emulsion with insufficient MnCl 2 signifies an addition of less than 75µL 10mM MnCl2 to 8mL vortexed sample. In w/o/w emulsions P1.25/2.5/1 and M1.25/2.5/1 (ratio of soft PMF to Hozol=3/1), 100µL and 28µL 10mM MnCl2 was added to (vortexed) 8mL and (non-vortexed) 3mL, respectively. 2.10.2 Determination of the enclosed water volume

From the peak areas in the T2-distributions, the enclosed water volume can be

estimated:

Estimated enclosed water volume (%) = [AUC(s) 100%] / [AUC(s) + AUC(f)]

Equation 2.14

where AUC (s) and AUC (f) stand for Area Under the Curve for the peak of the water

that is characterized by a slow and fast T2-relaxation time, respectively. Adding

MnCl2 dilutes the sample. Sabatino et al. (2011) showed that when this extra volume


71

was taken into account, no significant effect of the added MnCl2 was observed. The

percentage enclosed water volume is expressed as:

emulsion double in the water totalof 100mL water internal of mL (%) lume water voenclosed Estimated =

Equation 2.15

where the volume can be replaced by the mass on account of the equal densities of the

two water phases.

2.10.3 Determination of the yield of a double emulsion

The yield (%) of a double emulsion is expressed by the equation:

%100 waterinternal ofamount maximum lTheoretica

waterinternal ofAmount (%)emulsion double a of Yield =

Equation 2.16

The amount of water can be either expressed in volume or mass units. Bearing in

mind that the theoretical maximum enclosed water percentage is equal to 20g (w1-

phase) per 80g water (w1 and w2-phase) in w1/o/w2 emulsions that are prepared in a

weight ratio of 20:20:60, then the inclusion of the estimated enclosed water volume

revises Equation 2.16 of the yield of a double emulsion into Equation 2.17:

%100(%) water enclosed maximum lTheoretica

(%) water enclosed Estimated (%)emulsion double a of Yield =

%10025%

(%) water enclosed Estimated =

Equation 2.17


72


Assumptions were checked prior to application of parametric tests, such as the two

sample t-test and ANOVA. If they didn’t hold, non-parametric tests were used, such

as Wilcoxon rank sum test and Kruskal Wallis (S-Plus). Three repetitions of one

sample of each condition were analyzed, 24h after production. Hence, the standard

deviation associated with the three values per sample corresponded more to the

variation in measurement than to the variation in production. If more than two groups

need to be compared simultaneously, a Bonferroni correction (S-Plus) was applied.

2.11 Fat globule analysis by laser diffraction

The size of multiple droplets in a double emulsion was analyzed by a Mastersizer S

(Malvern Instruments) with settings 3PDD and breaking indices 1.596 and 1.33.

2.12 Profilometric analysis of double emulsions

One dimensional pulsed field gradient NMR profilometry is introduced in this thesis

as a novel technique to analyze the extent of creaming of a double emulsion and to

calculate the water content in the creamed layer of a sample. The advantage of this

method lies in its fast and nondestructive behavior. Besides the extent of creaming,

also the creaming rate could be determined by repetitive measurements at fixed time

intervals. Regarding double emulsions, profilometry offers the advantage over the

determination of the creaming rate by creaming accelerated measurement of the

transmission in a LUMiFuge apparatus, in terms of avoidance of possible detrimental

centrifugal forces on the enclosed water percentage. Profilometric analysis was

performed with a Maran Ultra 23 spectrometer, using a script in the RINMR software

(Appendix E). Reference is made to (Zhu, 2011). The first and second pulse gradient

duration amounted of 3562 and 7124µs, respectively. Their gradient strength was

31mT/m.


73

2.13 Whipping of a commercial dairy cream and w/o/w-emulsions

2.13.1 Commercial dairy cream

Whipping cream with 40g milk fat per 100mL (UHT treated, stabilizer: carrageenan,

Campina) was purchased.

2.9.2 W/o/w emulsions

2.9.2.1 First attempt to prepare whippable double emulsions

Two hundreds milliliter of double emulsion were made in accordance to method D.

The composition of this emulsion was M1.25/2.5/1 in which M stands in this

experiment for a mix of 62.5% soft PMF and 37.5% Hozol. EosinY (0.001%, w/v)

was added to the internal water phase (w1) to improve visualization of possible phase

separation. Firstly, about 90g of w/o-emulsion was made, from which 40g was

weighed and mixed with 60g of external water phase (w2). Secondly, again 100g of

w/o/w emulsion was prepared to result in a total produced amount of 200g, which was

collected in four Greiner tubes of 50mL and cooled in an ice bath. Afterwards, the

samples were attached in a Rotator SB2 at fixed rotational speed of 20rpm to prevent

creaming, while being kept overnight in a room at 5°C.

2.9.2.2 Second attempt to prepare whippable double emulsions

The second attempt differs from the first attempt in terms of the manner of prevention

of creaming. Each 30 minutes, the sample was gently twisted. Headspace was

provided to enable mixing while twisting. After production until whipping, the sample

was placed in a refrigerator at 5°C for 6.5h.


74

2.9.2.3 Third attempt to prepare whippable double emulsions

In the third endeavor, creaming is prevented by addition of 0.2%(w/w) xanthan gum

to the external water phase (w2) and the double emulsion was prepared analogously as

in the first attempt. Prior to whipping, storage was done at 5°C for 16h.

2.9.2.4 Fourth attempt to prepare whippable double emulsions

Based on the knowledge that small molecular weight surfactant are efficient in

displacing proteins from the interfacial film, which is desired in an intended

destabilization such as whipping, sodium caseinate in the external water phase was

replaced by 1%(w/v) cream residue powder (CRP), which contains phospholipids. In

addition, 0.2%(w/w) xanthan gum was added. The sample was stored at 5°C for 7h.

2.9.3 Determination of the whipping time

A Kenwood mixer (Major KM250) equipped with a standard wire whisk was used

from which the bowl and whisker were kept in the fridge prior to whipping. The

temperature in the fridge was 5°C. The volume of whipping cream was 200mL and

the applied speed level of the mixer was 3. The whipping time was chronometered as

the time between switching on the mixer and visual satisfaction.

2.9.4 Determination of the overrun of a whipped emulsion

A plastic transparent recipient of 200mL was weighted empty (m1) and filled with

unwhipped (m2) and whipped cream (m3). To avoid overestimation of the overrun, the

recipient should be filled completely without including artificial larger bubbles, which

can be removed by tapping gently (van Aken, 2001; Van Lent et al., 2008).

The overrun was determined from the equation:


75

%100cream) unwhipped of mass(net

cream) whippedmass(net -cream) unwhipped of mass(net (%)Overrun =

%100)m-(m

)m-(m-)m-(m

12

1312= Equation 2.18

2.9.5 Physical destabilization (drainage) of whipped emulsions

The mass of a sieve with pore size 1mm and an aluminum dish was measured.

Approximately 50g of whipped emulsions was brought on the sieve that rested on the

aluminum dish. After 1h at room temperature (16-18°C) the serum that had leaked

from the whipped emulsion on the sieve into the aluminum dish was determined:

%100sieve on thebrought cream whippedof mass

dish aluminium in the serum of massnet (%) leakage Serum =

Equation 2.19

Chapter 3 Results and discussions

76

Chapter 3

Results and discussion

3.1 Optimization of the water droplet size analysis

3.1.1 Temperature experiment by using a thermocouple

A small temperature test was performed with the aim to find an appropriate Set

Temperature of the Maran spectrometer. The latter can be defined as the temperature

that doesn’t give rise to temperature changes of a representative sample inside this

tube during the time period that the NMR-tube has to stay inside the Maran

spectrometer in order to complete the analyses of all magnetic gradient pulse width

values (δ). After programming a certain Set Temperature, some time was required

until the Set Temperature was reached and stabilized. Before placing the emulsion in

the spectrometer, it was kept in a water bath (Julabo) with Set Temperature of 5.3°C.

The temperature inside the emulsion, while kept in the water bath and covered with

parafilm, amounted to 4.2 to 4.3°C (Table 3.1), which was measured with a

thermocouple (Agilent 3497 OA). Regarding the accuracy of the temperature

measurements with the thermocouple, a digital calibrated thermometer displayed

about 0.65°C higher than the thermocouple. As such, the data represented in Table 3.1

and Figure 3.1 are corrected for this. Afterwards, the NMR-tube with sample covered

by a parafilm was transferred to the Maran spectrometer. The (transfer) time between

the removal of the tubes from the water bath and the beginning of the pfg-NMR

measurement (time zero) was shorter than 45s (Table 3.1), which resulted in an

average temperature of the emulsion at time zero of 4.8°C. The thermocouple probe

was positioned in such a way that it was immobile and measured the temperature

inside the emulsion without touching the glass of the NMR-tube.

Figure 3.1 represents the follow-up of the temperature of an emulsion (H1.25/2.50),

which is placed in the Maran Ultra 23 spectrometer as a function of time during a pfg-


77

NMR measurement of approximately 9.5 minutes. Based on this figure, the Set

Temperature of -7°C and -8°C is recommended for analysis of w/o-emulsions because

it results in a stable probe temperature. Consequently, all emulsions were analyzed

accordingly, except the emulsions that were analyzed at an earlier date than the

conducted temperature experiment, for which the Set Temperature is mentioned. Once

the samples are brought in the spectrometer, attention must be paid to the fact that

temperature control in the probe is not excellent, meaning that the samples should be

analyzed right away and not after a set time delay.

A first remark about this temperature measurement concerns the dependency of the

optimal Set Temperature on the composition of the emulsion. The thermal heat

capacity of a more fluid like emulsion, containing Hozol, is bigger than the thermal

heat capacity of a solid like emulsion, containing soft PMF or a mix of Hozol and soft

PMF. Hence, more energy is needed to increase the temperature of a sample with

Hozol. A more representative sample is a more sensitive sample towards temperature

change, such as a sample made of soft PMF or a mix of soft PMF and Hozol.

A second remark has to do with the definition of an optimal Set Temperature. During

measurement of the sample in the Maran spectrometer, the objective is to find an

approximately constant temperature. Whether this results in a sample temperature of

exactly 5°C is of less importance, since this will be corrected for by performing a

calibration at the same Set Temperature as the sample.

A third remark concerns the heat capacity of the applied thermometers. The digital

thermometer responds quickly to temperature changes and the temperature was

recorded in less than 1min. The non digital thermometer is characterized by a larger

heat capacity and was therefore, prior to usage, cooled down to 5°C in order to

compensate the slow temperature adaptation.


78

Table 3.1: Temperature of the emulsion (H1.25/2.5) in the water bath, transfer time, temperature of the emulsion at time zero and average temperature of the emulsion during a pfg-NMR analysis. Transfer time is the time between removal from the water bath and time zero. All parameters are given for different Set Temperatures of the Maran Ultra 23 spectrometer.

Set T (°C)

T(emulsion) (°C) in water bath

Transfer time (s)

T(emulsion) (°C) at time zero

Average T(°C) during pfg-NMR analysis

-5°C 4.2 40 5.0 5.61 -6°C 4.2 33 4.6 5.28

-7°C(A) 4.3 36 4.8 4.99

-7°C(B) 4.3 36 5.1 4.92 4.98

-7°C(C) 4.3 44 4.7 4.83

-7°C(D) 4.3 36 5.0 4.92

-7°C(E) 4.3 30 4.9 4.89

-8°C(A) 4.3 30 4.5 4.59 4.62

-8°C(B) 4.3 39 4.6 4.56

-9°C 4.3 39 4.5 4.28

4

4.5

5

5.5

6

6.5

7

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7 7.5 8 8.5 9 9.5

Time (min)

Em

ulsi

on te

mpe

ratu

re (

°C)

Set T=-5°C

Set T=-6°C

Set T=-7°C

Set T=-8°C

Set T=-9°C

Figure 3.1: Follow-up of the temperature of the emulsion (H1.25/2.5) during NMR-analysis with different Set Temperatures of the Maran Ultra 23 spectrometer. For the Set Temperature -7°C and Set Temperature -8°C, averages of five and two measurements are shown respectively, whose standard deviation is given as error bars.

3.1.2 Repeatability experiment

Aiming for a correct manner of rounding up of values for D43, a repeatability

experiment was conducted on three samples of emulsion P0.5/1. According to the

definition of repeatability by the ISO (1993), the following conditions must be

fulfilled: the same measurement procedure, the same observer, the same measuring

instrument, used under the same conditions, the same location and repetition over a

short period of time. IUPAC states that the measure of repeatability is the standard

deviation qualified with the term ‘repeatability standard deviation’. Repeatability may


79

also be defined as the value below which the absolute difference between two single

test results obtained under the above conditions, may be expected to lie with a

specified probability.

In the experiment the sequence of conducted measurements is as follows:

sample 1- sample 2- sample 3- sample 1- sample 2- sample 3- sample 1- sample 2-

sample 3.

This sequence was chosen because the experiment had to be conducted over a short

period of time, but not too short. If, for example, sample 1 would have been

conducted three times in a row, the elapsed time (about 10 minutes) between two

measurements would be too short. Moreover, this would mean that a sample stays

continuously for about 30-35 minutes inside the spectrometer, which is characterized

by a poor temperature control. With the proposed sequence of conducting

measurements, the elapsed time between the first and second measurement of the

sample 1 and of sample 2 was 36 minutes. For sample 3, this took 34 minutes, which

was identical to the time duration between the second and third measurement of this

sample 3. The time duration between the second and third measurement was 33

minutes for sample 1 and 2. Thus, approximately, the repetition period was 34

minutes.

In Table 3.2, the repeating measurements are presented in the same order as they were

conducted. The volume-weighted arithmetic mean diameter (D43) and the geometric

standard deviation (σg) of the samples P0.5/1 were calculated by using different data

processing methods.

In Table 3.3 the statistical analysis of the repeatability experiment with the parameters

received from the Droplet Size application and Matlab are presented. The standard

deviation of the three measurements of the volume-weighted arithmetic mean

diameters of sample 1, 2 and 3 are 0.012, 0.004 and 0.003µm, respectively. Based on

these values, it is suggested that, when measuring the same sample again after 34

minutes under the same conditions, more than one digit after the comma of the

volume-weighted arithmetic mean diameter will be less reliable than the first digit

after the comma. In other words, it is expected that the difference between two tests of

the same sample, with a time interval of 34 minutes and under the same conditions,

may be of the magnitude of two digits after the comma. Also from Table 3.3 it can be

seen that the replicate samples are significantly different from each other if they are

measured over a time scale of 90minutes.


80

In conclusion, in order to offer sufficient information and implement the outcome of

this repeatability experiment, all D43-values will be rounded up to two digits after the

comma.

Table 3.2: Calculated volume-weighted arithmetic mean diameter (D43) and geometric standard deviation (σg) of the water droplets in the P0.5/1 emulsion by using Droplet Size application and Matlab. No results could be obtained with Excel. Three samples were made and each sample was analyzed three times. Droplet Size application Matlab P0.5/1 D43 (µm) σg D43 (µm) σg Sample 1 -first time 2.66 1.002 1.81 1.000 Sample 2 -first time 2.58 1.002 1.83 1.000 Sample 3 -first time 2.60 1.009 1.81 1.014 Sample 1 -second time 2.64 1.001 1.75 1.190 Sample 2 -second time 2.58 1.002 1.82 1.009 Sample 3 -second time 2.62 1.002 1.82 1.000 Sample 1 -third time 2.64 1.003 1.79 1.034 Sample 2 -third time 2.60 1.008 1.83 1.000 Sample 3 -third time 2.62 1.004 1.81 1.001

Table 3.3: Statistical analysis of the repeatability experiment indicating the average, standard deviation of the three repetitions of each sample and 95% confidence interval. Droplet Size application Matlab Sample 1 Average D43 (µm) 2.64 1.78 Standard deviation (µm) 0.012 0.034 95% Confidence interval (µm) [2.618 ; 2.675] [1.698 ; 1.869] Sample 2 Average D43 (µm) 2.59 1.83 Standard deviation (µm) 0.004 0.005 95% Confidence interval (µm) [2.580 ; 2.599] [1.812 ; 1.839] Sample 3 Average D43 (µm) 2.61 1.81 Standard deviation (µm) 0.003 0.008 95% Confidence interval (µm) [2.604 ; 2.621] [1.793 ; 1.832]

3.2 Quantitative particle size analysis of water droplets in commercial butters

In prospect of the preparation and analysis of w/o-emulsions, the droplet size of water

droplets in an industrially prepared (commercial) butter was determined. For all


81

analyses on butter, the running script, DSD.RIS.tif as described in section 2.3.2, was

used. The diffusion coefficient of water in the dispersed phase at 5°C was equal to

9.698E-10m/s2 for Bio Karneboter and 9.122E-10m/s2 for Ardense Roomboter. For

comparison, the diffusion coefficient of pure water at 5°C is equal to 1.3253E-09

m2/s.

By means of illustration, the experimental data of the first sample of Bio karneboter

and the best fitting calculated data, which were obtained by the three data processing

methods, are graphically represented in Figure 3.2a,b,c. In Figure 3.3 the averaged

echo intensity and standard deviation of three samples versus magnetic gradient pulse

width (δ) is graphically represented for both butters. As seen from this graph, a faster

echo decay as a function of magnetic gradient pulse width (δ) is observed for Bio

Karneboter than for Ardense Roomboter, hence larger water droplets will be found in

the former butter.

In Table 3.4 the volume-weighted arithmetic mean diameter (D43) and the geometric

standard deviation (σg) of the water droplets in the commercial butters are obtained by

using different data processing methods (Droplet Size application, Excel and Matlab),

as described in section 2.3.3.

In Table 3.5, a statistical analysis of the parameters D43 and σg, obtained by different

data processing methods, is presented: the average and standard deviation of three

samples for each commercial butter and the 95% confidence interval of the average

are mentioned.

The mean D43 of Bio Karneboter is significantly larger than the mean D43 of Ardense

Roomboter and this is valid for data coming from the Droplet Size application

(p=0.0086), Excel (p=0.0081) and Matlab (p=0.0079). This is in accordance to the

study of Van Lent et al. (2008). In the latter study a Bruker instrument was used.

Also, based on the samples of Bio Karneboter, the mean D43 obtained by the Droplet

Size application was significantly larger than the mean D43 obtained by Excel

(p=0.001) and by Matlab (p=0.001). Similarly, based on the samples of Ardense

Roomboter, the mean D43 obtained by the Droplet Size application was significantly

larger than the mean D43 obtained by Excel (p=0) and by Matlab (p=0).


82

0.5

0.6

0.7

0.8

0.9

1.0

1.1

0 0.0005 0.001 0.0015 0.002 0.0025 0.003 0.0035 0.004 0.0045

δ (s)

Ep

(-)

Ep measured

Ep calculated

Figure 3.2a: Measured and calculated echo attenuation ratio versus magnetic gradient pulse width by Droplet Size application, for Bio Karneboter (sample 1).

0.5

0.6

0.7

0.8

0.9

1.0

1.1

0 0.0005 0.001 0.0015 0.002 0.0025 0.003 0.0035 0.004 0.0045

δ (s)

Ep

(-)

Ep measured

Ep calculated

Figure 3.2b: Measured and calculated echo attenuation ratio versus magnetic gradient pulse width by Excel, for Bio Karneboter (sample 1).

1,400

1,600

1,800

2,000

2,200

2,400

2,600

2,800

3,000

3,200

0 0.0005 0.001 0.0015 0.002 0.0025 0.003 0.0035 0.004 0.0045

δ (s)

Ech

o in

tens

ity

I (measured)

Raccum (calculated)

Figure 3.2c: Experimental (I) and best fitting calculated (Raccum) echo intensity versus magnetic gradient pulse width by Matlab, for Bio Karneboter (sample 1).


83

Table 3.4: Volume-weighted arithmetic mean diameter (D43) and geometric standard deviation (σg) of commercial butter samples calculated by different data processing methods (Droplet Size application, Excel and Matlab) Droplet Size application Excel Matlab

OUTPUT OUTPUT OUTPUT OUTPUT OUTPUT OUTPUT OUTPUT

Rmed (µm) σ (µm) D43 (µm) σg σ (µm) MF D33 (µm) D43(µm) σg R43 (µm) Stdev (µm) σg

Bio Karneboter

sample 1 0.9942 0.4159 3.64 1.516 0.3221 1.0138 2.59 2.72 1.380 1.3738 0.5024 1.425

sample 2 1.0839 0.3578 3.40 1.430 0.2809 1.0079 2.47 2.57 1.324 1.2943 0.3960 1.349

sample 3 0.9811 0.4060 3.50 1.501 0.3138 1.0096 2.51 2.63 1.369 1.3247 0.4695 1.411

Ardense roomboter

sample 1 0.7107 0.4610 3.00 1.586 0.3640 1.0046 2.17 2.31 1.439 1.1482 0.4711 1.484

sample 2 0.5234 0.5512 3.04 1.735 0.4407 1.0035 2.09 2.30 1.554 1.1583 0.5875 1.614

sample 3 0.5968 0.5155 3.02 1.674 0.4062 1.0225 2.13 2.31 1.501 1.1552 0.5403 1.560

Key to symbols:

Rmed: median radius or number weighted geometric mean radius of the log-normal distribution (µm)

R43: volume-weighted arithmetic mean radius (µm)

D43: volume-weighted arithmetic mean diameter (µm)

D33: volume-weighted geometric mean diameter (µm)

σ: distribution width or neperian logarithm of the geometric standard deviation of the particle radius or diameter distribution (µm)

σg : geometric standard deviation of the particle radius or diameter distribution (dimensionless)

Stdev: arithmetic standard deviation of the volume-weighted particle radius distribution (µm)

MF: multiplication factor that is entered in the solver of Excel together with R33 and Sigma

OUTPUT: data obtained directly from the output of the data processing method


84

1000

1500

2000

2500

3000

3500

0 0.001 0.002 0.003 0.004 0.005

δ (s)

Ech

o in

tens

ityArdense Roomboter

Bio Karneboter

Figure 3.3: Plot of the average echo intensity of three samples of Ardense Roomboter and Bio Karneboter versus magnetic gradient pulse width. For each average echo intensity, the standard deviation of three samples is represented by an error bar. Table 3.5: Statistical analysis of D43 and σg, obtained by different data processing methods (Droplet Size application, Excel and Matlab), obtained from three samples with the same composition. Droplet Size application Excel Matlab Bio Karneboter Average of D43 3.51 2.64 2.66 Standard deviation 0.121 0.078 0.080 95% Confidence interval [3.214 ; 3.813] [2.447 ; 2.835] [2.463 ; 2.861] Ardense Roomboter Average of D43 3.02 2.31 2.31 Standard deviation 0.020 0.008 0.010 95% Confidence interval [2.970 ; 3.070] [2.289 ; 2.328] [2.282 ; 2.334] Droplet Size application Excel Matlab Bio Karneboter Average of σg 1.482 1.355 1.395 Standard deviation 0.0457 0.0292 0.0406 95% Confidence interval [1.369 ; 1.596] [1.283 ; 1.428] [1.294 ; 1.496] Ardense Roomboter Average of σg 1.665 1.493 1.552 Standard deviation 0.0753 0.0578 0.0654 95% Confidence interval [1.478 ; 1.852] [1.350 ; 1.637] [1.390 ; 1.715]


85

3.4 Quantitative particle size analysis of water droplets in w/o-emulsions

3.3.1 Analysis of emulsions with composition H0/1, H0.5/1, M0/1 and P0/1

Water in oil-emulsions H0/1, M0/1 and P0/1 were prepared and analyzed with the

running script DSD.RIS.tif of the Maran Ultra 23 spectrometer. The diffusion

coefficient of the dispersed phase at 5°C for these emulsions was 1.457E-09 m2/s,

whereas for H0.5/1, which was analyzed with the script DSD_Lien.RIS.tif, this was

1.298E-09 m2/s. To the water phase of emulsion H0.5/1, 0.5% (w/v) eosinY was

added in order to enable better visualization of serum separation, which occurred after

approximately 2 weeks.

The experimental numerical data of the echo intensities of the analyzed w/o-

emulsions as a function of magnetic gradient pulse width (δ) can be found in

Appendix F.

In Table 3.6 the volume-weighted arithmetic mean diameter (D43) and the geometric

standard deviation (σg) of the water droplets in different w/o-emulsions were obtained

by using different data processing methods. In the column of determined parameters

in Excel, the error message ‘No results, cannot divide by zero’ denotes that the sum of

relative frequencies was zero, resulting in the error message (#DEEL/0!) for the

normalized relative frequencies. In this case, D33, which is converted to D43, and the

distribution width (Sigma) were not able to be calculated. In the same column of

Table 3.6, the sentence ‘No change of filled in values’ refers to the fact that when

filling in the values of D33 and Sigma from the column of Droplet Size application in

Table 3.6, together with the multiplication factor (for better fit, as explained in section

2.3.3.2.) into the solver of the Excel file, the parameters D33 and Sigma remained

identical to the filled in values. Furthermore, flat bars denote that no results could be

obtained and empty cells refer to lack of measurements. Normally, the first measured

echo attenuation intensity point is a good estimate for I0 (or the intensity of the echo

attenuation without pulsed field gradient), however, when the first measured point is

not the largest measured point, then the largest point was taken as the best estimate for

I0.

The impairment of Excel to produce values for D43 and Sigma is explained by the fact

that in Excel, the relative frequencies are calculated for a chosen range of diameters

with a relatively broad bin width, namely 1µm. This approach has the disadvantage


86

that, for samples characterized by a small distribution width, the measured

distribution might be located in between two adjacent values of the chosen set of

diameters, resulting in a zero percentage relative frequency for the chosen set of

diameters. The inverse approach for determination of the calculated echo attenuation

ratios is an approach that calculates the droplet diameter for a certain relative

frequency. This is the approach which is used in Matlab.

Table 3.6: The volume-weighted arithmetic mean diameter (D43) and the geometric standard deviation (σg) of the water droplet distribution in different w/ o-emulsions by using different data processing methods. R-squared values are given whenever multiple outcomes of one sample by a data processing method was collected (see section 2.3.4). Droplet Size application Excel Matlab

D43 (µm) σg MF D43 (µm) σg D43 (µm) σg R2

H0/1

Produced 8/9/10

sample 1 - - - - - 3.94 1.000 0.9848

sample 1 Io(2.1) 3.94 1.000 0.9848

sample 1 * 5.50 1.097 1.410 4.00 1.004 4.00 1.000 0.9955

sample 2 4.90 1.001 no results, cannot divide by 0 3.72 1.000 0.9367

sample 2 * Io(3.1) 3.81 1.000 0.9731

sample 3 5.04 1.004 no change of filled in values - - -

sample 3 Io(2.1) 3.82 1.000 0.9439

sample 3* 3.92 1.000 0.9831

M0/1

Produced 9/9/10

sample 1 4.38 1.002 no change of filled in values - - -

sample 1 * 3.36 1.000

sample 2 - - - - - 3.23 1.000

sample 2 ** 4.32 1.002 no change of filled in values - - -

sample 3 - - - - - 3.22 1.000 0.9949

sample 3 ** 4.30 1.000 no results, cannot divide by 0 3.22 1.000 0.9969

P0/1

Produced 9/9/10

sample 1 4.76 2.065 1.012 3.35 1.821 3.44 1.895

sample 2 3.90 1.861 1.010 2.86 1.670 2.91 1.735

sample 3 4.60 2.309 1.012 3.23 2.013 3.30 2.094

H0.5/1

Produced 22/9/10

sample 1 4.28 1.116 1.044 3.06 1.081 - - -

sample 1 *** 3.26 1.000

sample 2 - - - - - 3.26 1.000 0.9967

sample 2 *** 4.26 1.001 no results, cannot divide by 0 3.26 1.000 0.9967

sample 3 4.26 1.101 1.037 3.05 1.079 3.26 1.000 *: output is calculated without including the first measured data point (echo intensity) **: without including the second measured data point ***: without the last measured data point. MF: multiplication factor


87

As illustrated in Table 3.6, data processing by Matlab of sample 1 of the w/o-

emulsion with code H0/1 and production date 8/9/10 has three values for the volume-

weighted arithmetic mean diameter and geometric standard deviation. This is

explained by the fact that three sets of data were obtained: the complete set, the set

from which one data point was removed and the set with a different I0. The complete

set didn’t give any results by the Droplet Size application. An error message

appeared: “Invalid floating point operation”. This was due to the fact that the

measured data were too much deviating from the calculated data and hence no good

fit could be achieved. By deleting a deviating data point, values for parameters were

obtained. For some samples the geometric standard deviation is equal to 1, which

would mean that all droplets are exactly the same. Figure 3.4 illustrates the effect of

the echo intensity decay as a function of gradient pulse width δ for a fixed volume-

weighted mean radius (R33) and a variable geometric standard deviation σg. Only the

data points at large δ are slightly influenced by σg. Hence, the estimation of the

distribution width is less accurate as compared to the distribution mean.

0

0.2

0.4

0.6

0.8

1

1.2

0 1 2 3 4 5 6 7 8 9

δ (ms)

Ech

o in

tens

ity Sigma g=1.005

Sigma g=1.01

Sigma g=1.015

Sigma g=1.05

Sigma g=1.1

Figure 3.4: Echo intensity decay as a function of gradient pulse width for variable geometric standard deviations. R33 is fixed at 1.5µm. Ds=1.31E-09m2/s. Figure 3.5 shows a constant relationship between higher volume-weighted arithmetic

mean diameters obtained from the Droplet Size application and lower values for D43,

calculated by Matlab or Excel. W/o-emulsions made with Hozol as the fat phase

render significantly higher mean D43 than in emulsions prepared with a mix of soft


88

PMF and Hozol (p=0.044). This can be explained by the contraction of soft PMF

during solidification at refrigerator temperature, which would coincide with expulsion

of water from the emulsified water droplets and separation of free water. Since the

latter could not be observed, the findings might be explained by an increased

permeabililty for water of the continuous phase.

0.00

1.00

2.00

3.00

4.00

5.00

6.00

H0/1 (8/9/10) M0/1 (9/9/10) P0/1 (9/9/10) H0.5/1 (22/9/10)

Emulsion composition

D43

(µm

) Droplet Size application

Excel

Matlab

Figure 3.5: Plot of the average volume-weighted arithmetic mean diameter (D43) of three samples for each emulsion composition, calculated by different data processing methods (Droplet Size application, Excel and Matlab). For each average D43, the standard deviation of three samples is represented by an error bar. 3.3.2 Analysis of emulsions with composition H0/1, H0.5/1, M0/1, P0/1, P0.5/1 and

P0.5/2

After mastering the Microfluidizer procedure better, emulsions with composition

P0.5/1 and P0.5/2 were made and samples H0/1, H0.5/1, M0/1 and P0/1 were remade.

These emulsions were analyzed with the script DSD_Lien.RIS.tif. The diffusion

coefficient of water in the dispersed phase at 5°C without sodium caseinate was

1.288E-09 m2/s. The diffusion coefficient at 5°C for emulsions containing 0.5% (w/v)

sodium caseinate was 1.247E-09 m2/s (H0.5/1) and 1.295E-09 m2/s (P0.5/1 and

P0.5/2). As illustration, Figure 3.6 gives a graphical representation of the

experimental intensity data of the echo attenuation in function of the magnetic

gradient pulse width (δ), as well as the best fit by Matlab for sample 1 of emulsion

H0.5/1 (Prod. date 21/10/10). The Set Temperature of the Maran Ultra 23

spectrometer was set at -14°C for analysis of P0.5/1 and P0.5/2. The analyzed

samples are presented in Table 3.7.


89

0 1 2 3 4 5 6 7 8 9

x 10-3

0

500

1000

1500

2000

2500

Small delta (s)

Inte

nsity

of

the

echo

att

enua

tion

Measured data

Fitted line

Figure 3.6: Graphical representation of the experimental data of intensity of the echo attenuation in function of magnetic gradient pulse width (δ) together with the best fit obtained by Matlab for sample 1 H0.5/1 (Prod. date 21/10/10).

3.2.2.1 Statistical analysis of emulsions H0/1, H0.5/1, P0/1, M0/1, P0.5/1 and P0.5/2

In Table 3.7, the values of the samples that are associated with the highest R2 are

preferentially included in the statistical processing of the data. Concerning the

differences in data processing methods, a closer look to Table 3.7 results in the

conclusion that data processing by Excel often leads to no outcome, as discussed in

section 3.3.1. The statistical analysis of Table 3.7 consisted of the investigation of the

differences of the diameters of samples with the same composition between the

different processing methods. Also, the comparison of the emulsions H0/1, P0/1 and

M0/1 gives an idea about the influence of the fat type on the mean water droplet size

and the comparison between [H0/1 and H0.5/1], [P0/1 and P0.5/1] and the

comparison between [P0.5/1 and P0.5/2] renders information about the effect of the

concentration of the hydrophilic and hydrophobic emulsifier, respectively on the

mean water droplet size.


90

Table 3.7: The volume-weighted arithmetic mean diameters (D43) and the geometric standard deviation (σg) of the water droplets in different w/o-emulsions by using different data processing methods. MF=multiplication factor. Flat bars denote that no results could be obtained. R-squared values are given whenever multiple outcomes of one sample by a data processing method was collected. Droplet Size application Excel Matlab

D43 (µm) σg R2 MF D43 (µm) σg R2 D43 (µm) σg R2

H0/1

Produced 19/10/10

Sample 1 2.62 1.232 0.9935 no results, cannot divide by 0 3.72 1.181 0.9893

Sample 1 *** 2.32 1.271 0.9939 no change of filled in values 3.75 1.211 0.9950

Sample 2 4.56 1.107 0.9993 1.035 3.13 0.932 0.9987 3.47 1.043 0.9927

Sample 2 *** 4.58 1.134 0.9994 1.034 3.14 1.000 0.9987 3.48 1.071 0.9998

Sample 3 5.08 1.242 0.9961 1.020 3.75 1.175 0.9973 3.72 1.190 0.9973

Sample 3 *** 5.14 1.271 0.9962 1.022 3.76 1.188 0.9971 3.82 1.212 0.9971

M0/1

Produced 19/10/10

Sample 1 3.72 1.029 0.9893 no change of filled in values 2.87 1.000 0.9911

Sample 1 *** 3.80 1.333 0.9950 1.009 2.89 1.264 2.90 1.283 0.9961

Sample 2 3.68 1.101 0.9918 1.008 2.96 1.092 2.83 1.064 0.9935



Sample 3 *** 3.70 1.287 0.9951 1.007 2.85 1.227 2.84 1.241 0.9963

P0/1

Produced 21/10/10

Sample 1 3.24 1.002 0.9719 no change of filled in values - -

Sample 1 *** 3.10 1.429 0.9955 1.006 2.41 1.346 2.41 1.386


Sample 2 *** 3.58 1.904 0.9896 1.009 2.62 1.714 2.71 1.792 0.9910

Sample 3 3.30 1.249 0.9545 0.981 2.56 1.296 0.9639 2.56 1.224 0.9577

Sample 3 *** 3.84 2.127 0.9937 1.014 2.70 1.845 0.9942 2.85 1.973 0.9948

H0.5/1

Produced 21/10/10

Sample 1 5.18 1.276 0.993 3.84 1.221 3.83 1.220

Sample 2 5.14 1.278 0.985 3.85 1.236 3.80 1.222

Sample 3 5.06 1.275 0.982 3.81 1.237 3.80 1.219

P0.5/1 ■

Produced 30/9/10

Sample 1 2.65 1.002 no change of filled in values 1.79 1.071



P0.5/2

Produced 30/9/10




Sample 2 *** 2.54 1.121 0.9921 1.128 2.47 1.066 1.99 1.000 0.9918

Sample 3 - - no change of filled in values 2.11 1.000 0.8289

Sample 3 *** 2.46 1.002 no change of filled in values 1.91 1.000 0.9835 ■: each sample is the average of three repetitions. ***: without the last measured data point


91

3.3.2.2 Difference between different data processing methods

For each emulsion composition, three samples were produced. Thus, 3 values

calculated with the Droplet Size application are compared with 3 values obtained with

Excel and 3 values from Matlab. This is graphically illustrated in Figure 3.7, in which

it can be observed that Matlab calculates a significantly lower mean volume-weighted

arithmetic mean diameter than the Droplet Size application for the same emulsion (all

p<0.02, except for H0/1). Possibly due to the small Sigma of sample 1 of H0/1, a

deviating value for D43 is obtained. A significantly larger mean volume-weighted

arithmetic mean diameter is recorded for the Droplet Size application than for Excel

for the samples with composition M0/1, P0/1 and H0.5/1 (all p<0.02). Insufficient

data from Excel were available for H0/1, P0.5/1 and P0.5/2. A significantly larger

mean σg by the Droplet Size application in comparison to Excel and Matlab can be

detected for the sample with composition H0.5/1 (p=0.0082 and p=0). For the other

emulsion compositions, concerning the comparison of the replicates per sample

composition, Matlab results in slightly but not significantly lower mean geometric

standard deviation as compared to the Droplet Size application.

0.00

1.00

2.00

3.00

4.00

5.00

6.00

H0/1(19/10/10)

M0/1(19/10/10)

P0/1(21/10/10)

H0.5/1(21/10/10)

P0.5/1(30/9/10)

P0.5/2(30/9/10)

Emulsion composition

D43

(µm

) Droplet Size application

Excel

Matlab

Figure 3.7: Graphical representation of the difference in mean volume-weighted arithmetic mean diameter between three data processing methods. Error bars denote the standard deviation of three samples.

3.3.2.3 Influence of the type of fat on the mean water droplet size

The influence of the type of fat on the mean volume-weighted arithmetic mean

diameter was investigated by comparison of the outcome from Matlab of samples


92

H0/1, M0/1 and P0/1. A significantly larger mean D43 (µm) was detected for H0/1

versus M0/1 (p=0.009) and for H0/1 versus P0/1 (p=0.005). As discussed in section

3.3.1, the solidification of soft PMF at refrigerator temperature might contribute to the

difference in mean water droplet size among emulsions with different fat composition.

3.3.2.4 Influence of the emulsifier on the mean water droplet size

To establish the effect of the concentration of the hydrophilic emulsifier on the mean

D43, the outcome by Matlab of samples H0/1 and H0.5/1 were compared. It could not

be stated that the addition of sodium caseinate had a significant effect on the mean D43

(p=0.2). This is not in accordance to the expectations; it is expected that adding

sodium caseinate would decrease the water droplet size, because more interfacial

surface can be stabilized by emulsifier. This statement holds when the applied air

pressure (6bar) of the Microfluidizer is capable of reducing the droplet size even

more. However, it is in accordance to what Calliauw (2009) observed with pfg-NMR

analysis, in contrast to the observations with light microscopy.

The same test was performed on the outcome by Matlab of samples P0/1 and P0.5/1.

A significantly larger mean D43 of P0/1 in comparison to P0.5/1 was found (p=0.011).

In other words, regarding emulsions based on soft PMF without hydrophilic

surfactant, the addition of sodium caseinate to 1% PGPR has a beneficial effect on the

reduction of the mean water droplet size.

The comparison of the mean D43 of P0.5/1 and P0.5/2, which tests the influence of the

concentration of the hydrophobic emulsifier on the mean D43, results in the conclusion

that, if the data are obtained by Matlab, the mean D43 is larger for the emulsion

samples containing soft PMF with 2% PGPR than for the samples containing soft

PMF with 1% PGPR (p=0.0065). If the data are obtained from the Droplet Size

application, then the opposite is reported (p=0.0086). Although the latter observation

is expected, the beneficial effect of PGPR to the water droplet size cannot be

statistically proven, because the data from the Droplet Size application and Matlab are

contradictory.


93

3.3.3 Elevation of the water fraction of emulsions based on Hozol

Anticipating the creation of a double emulsion in which the fat globules are filled with

a maximal water fraction in order to reduce the caloric content of a whipping cream,

the water percentage of emulsions, which contain Hozol as the fat phase, was

increased from 20% to 30%, 40%, 50% and 60wt%. The emulsifiers sodium caseinate

and PGPR were increased proportionally to the water percentage in the emulsion as

illustrated in Table 3.8.

Table 3.8: Composition of the emulsions with different water percentage

W/o-emulsion H 0.50/1 H 0.75/1.5 H 1.0/2.0 H 1.25/2.5 H 1.5/3.0

Water percentage (wt%) 20 30 40 50 60

Oil percentage (wt%) 80 70 60 50 40

Water phase

Sodium azide (wt%) 0.02 0.02 0.02 0.02 0.02

Sodium caseinate (wt%) 0.50 0.75 1.00 1.25 1.50

Buffer solution (pH6.7) ad 100% ad 100% ad 100% ad 100% ad 100%

Oil phase

PGPR (wt%) 1.0 1.5 2.0 2.5 3.0

Hozol (%) 99.0 98.5 98.0 97.5 97.0

By means of a dilution test with water, a quick assessment of the type of emulsion

was acquired. If water was miscible with the emulsion, then this was an o/w-

emulsion, whereas immiscibility referred to a w/o-emulsion. As such, all prepared

emulsions were classified as w/o-emulsions, except H1.5/3.

Comparing the first echo intensity of the various emulsions, values of 5529, 7718,

10610, 14457 and 185 were found for 20, 30, 40, 50 and 60wt% water in emulsions.

As shown in Figure 3.8, the very small value for the 60% emulsion is due to a nearly

completely decayed echo intensity within the first time period, which is indicative of

free water diffusion as occurs in emulsions with an aqueous continuous phase.


94

0

2000

4000

6000

8000

10000

12000

14000

16000

0 0.001 0.002 0.003 0.004 0.005 0.006 0.007 0.008 0.009

δ (s)

Ech

o in

tens

ityH0.50/1.00 measured

H0.75/1.50 measured

H1.00/2.00 measured

H1.25/2.50 measured

H1.50/3.00 measured

Figure 3.8: Measured echo intensity as a function of magnetic gradient pulse width (δ) for various emulsions. The connection line represents the calculated echo intensity obtained from the Droplet Size application.

The volume-weighted arithmetic mean diameters of the emulsions are presented in

Table 3.9 and this reveals that also H1.5/3 gives a water droplet size outcome by data

processing, but the calculated data fit the measured data less, which is expressed in a

smaller R2. The script that was used was DSD_Lien.RIS.tif. The water diffusion

coefficient in the serum at 5°C of H0.5/1, H0.75/1.5, H1/2, H1.25/2.5 and H1.5/3

amounted to 1.299E-09, 1.289E-09, 1.282E-09, 1.283E-09 and 1.268E-09 m2/s,

respectively. At a certain temperature, an increase of sodium caseinate reduces the

diffusion coefficient as water molecules become less mobile.

Figure 3.9 shows the average volume-weighted arithmetic mean diameter as a

function of mass fraction of water in the w/o-emulsion, as determined by the Droplet

size application, Excel and Matlab. In there, Matlab renders consistently smaller

volume-weighted mean diameters than the Droplet Size application. The mean D43,

obtained by Excel for emulsions with 40 and 50% water fraction, are similar to the

mean D43 obtained by the Droplet Size application, whereas the mean droplet size

data obtained by Excel for the emulsion with 20% water fraction resemble the data in

Matlab. The latter confirms the observations in sections 3.3.1 and 3.3.2.2. In Excel,

the emulsions with 40 and 50% water fraction are characterized by a small

distribution width (│σ│< 0.020µm), whereas │σ│ for the emulsion with 20% water

fraction and for all other prepared emulsions resulting in a equivalent water droplet

size distribution as the data obtained by Matlab, is higher than 0.10µm. Hence, the

accuracy of the data in Excel that are based on deviating calculated distribution

widths might be doubtful.


95

Table 3.9: Volume-weighted arithmetic mean diameter (D43) and geometric standard deviation (σg) obtained by different data processing methods, for emulsions with different mass fraction of water. R-squared values are given whenever multiple outcomes of one sample by a data processing method was collected. MF= multiplication factor. Flat bars denote that no results could be obtained. Droplet Size application Excel Matlab

D43 (µm) σg R2 MF D43 (µm) σg R2 D43 (µm) σg R2

H0.5/1

Prod. 04/11/10

sample 1 4.90 1.248 0.9985 1.028 3.60 1.183 0.9983 3.66 1.202 0.9990

sample 1 *** 4.94 1.277 0.9990 1.030 3.61 1.194 0.9982 3.68 1.222 0.9993

sample 2 4.84 1.266 0.9982 1.024 4.57 1.194 0.9983 3.62 1.219 0.9989

sample 2 *** 4.88 1.292 0.9985 1.026 3.57 1.204 0.9982 3.64 1.237 0.9990

sample 3 4.82 1.231 0.9968 1.022 3.55 1.175 0.9974 3.61 1.186 0.9974

sample 3 *** 4.84 1.242 0.9963 1.022 3.55 1.173 0.9969 3.61 1.188 0.9971

H0.75/1.5

Prod. 03/11/10

sample 1 4.22 1.129 0.9992 1.045 3.04 1.085 3.21 1.086

sample1 *** 4.24 1.168 0.9996

sample 2 4.00 1.004 0.9996 no change of filled in values - -

sample 2 **** 4.00 1.001 0.9996 no results, cannot divide by 0 3.08 1.000

sample 3 3.96 1.001 no results, cannot divide by 0 - -

sample 3 *** - - - - - 3.04 1.000

H1/2

Prod. 28/10/10

sample 1 3.98 1.119 0.9982 1.243 3.76 1.000 3.72 1.079 0.9670

sample 1 *** 4.00 1.142 0.9978 no results, cannot divide by 0 3.05 1.092 0.9970

sample 2 **** 3.88 1.001 no results, cannot divide by 0 - -

sample 3 - - - - - 3.01 1.000 0.9984

sample 3 *** 3.94 1.064 0.9990 1.197 3.82 1.001 3.71 1.000 0.9757

sample 3 **** 3.94 1.016 0.9989 no change of filled in values 3.03 1.000 0.9980


sample 4 *** 3.94 1.000 0.9984 no results, cannot divide by 0 - -

sample 4 * 3.94 1.000 0.9984 no results, cannot divide by 0 3.04 1.000

H1.25/2.5

Prod. 04/11/10

sample 1 3.88 1.043 0.9992 no results, cannot divide by 0 2.98 1.000 0.9988

sample 1 *** 3.88 1.110 0.9993 1.208 3.82 1.006 2.98 1.039 0.9986

sample 2 - - - - - 2.97 1.000

sample 2 *** 3.84 1.000 no results, cannot divide by 0 - -

sample 3 3.92 1.075 0.9992 no results, cannot divide by 0 3.01 1.000 0.9989

sample 3 *** 3.92 1.128 0.9993 1.197 3.70 0.975 3.01 1.071 0.9988

H1.5/3

Prod. 11/11/10

sample 1 3.52 1.001 0.9516 no change of filled in values 2.72 1.000 0.9496

sample 1 *** 3.52 1.002 0.9314 no change of filled in values 2.71 1.000 0.9298


sample 2 *** 5.12 2.524 0.7693 1.061 2.23 1.883 3.55 2.248

sample 3 - - - - - 2.74 1.000 0.9057

sample 3 *** 3.50 1.005 no change of filled in values 2.70 1.000 0.8706

* or *** signifies that the first or last measured data point is omitted from the calculations, respectively. **** refers to the exclusion of the last two data points in the calculation.


96

Emulsion H0.5/1 with 20% water fraction is characterized by a significantly larger

mean volume-weighted arithmetic mean diameter, obtained in Matlab and the Droplet

Size application, than emulsion H0.75/1 (p<0.01), H1/2 (p=0) and H1.25/2.5 (p=0)

with 30, 40 and 50% water fraction, respectively.

Concerning H0.75/1.5, H1/2 and H1.25/2.5, no significant difference of the mean

volume-weighted arithmetic mean diameter can be detected (p=0.054). If the

surfactant concentration would be insufficient, then an increase of the water fraction,

and hence increase of water/oil interface, would result in an increase of water droplet

size, as larger droplets have a lower interfacial area in a w/o-emulsion with constant

water fraction. Since this can not be detected in the prepared emulsions for increasing

water fractions, the applied surfactant concentration is not inadequate at water mass

fractions up to 50%.

0.00

1.00

2.00

3.00

4.00

5.00

6.00

10 20 30 40 50 60

Water fraction in w/o emulsion (w/w)

D43

(µm

) Droplet Sizeapplication

Excel

Matlab

Figure 3.9: Average volume-weighted arithmetic mean diameter and standard deviation (error bars) of 3 samples per emulsion composition as a function of water fraction (w/w) in the w/o-emulsion and determined by different data processing methods. The average D43 of emulsion H1.25/2.5 (50wt% water) was calculated on 4 samples.

3.3.4 Effect of the decrease of the driving air pressure of the Microfluidizer M110S on

the water droplet size in a w/o-emulsion

The aim of this experiment was to find out whether a decrease of air pressure results

in a larger water droplet size. Emulsions with composition H1.25/2.5 (50% water

mass fraction) were homogenized in a Microfluidizer at two air pressures: 4bar or


97

6bar. Due to pressure fluctuations above 6bar in the Microfluidizer, no higher

pressures were investigated.

The corresponding volume-weighted arithmetic mean diameters were determined by

the Droplet Size application and Matlab as represented in Table 3.10. Data processing

by Excel was omitted due to deficiency of results. The script that was used was

DSD_Lien.RIS.tif. The water diffusion coefficient in the serum at 5°C amounted to

1.283E-09m2/s.

Statistical analysis revealed that the mean volume-weighted arithmetic mean

diameter, obtained by the Droplet Size application, of a H1.25/2.5 emulsion is

significantly larger when the emulsion is homogenized at an air pressure of 4bar than

at 6bar (p=0.034). Increasing the air pressure of a Microfluidizer M110S with 1bar

results in a decrease of D43 of 0.03µm for both data processing methods. Based on this

experiment, an increase of air pressure of 2bar is not very cost-effective.

Table 3.10: Volume-weighted arithmetic mean diameter and geometric standard deviation of the w/o-emulsion H1.25/2.5 (Production 11/11/10), produced at different air pressures. Data obtained by the Droplet Size application and Matlab. Flat bars denote that no results could be obtained. R-squared values are given whenever multiple outcomes of one sample by a data processing method was collected. Droplet Size application Matlab

D43 (µm) σg R2 D43 (µm) σg R2

Air pressure= 4 bar

sample 1 3.92 1.001 0.9988 3.02 1.000 0.9986

sample 1 *** 3.92 1.125 0.9995 3.01 1.067 0.9991

sample 2 3.84 1.000 - -

sample 2 *** - - - -

sample 3 - - - -

sample 3 *** 3.86 1.002 2.98 1.000

Air pressure= 6 bar

sample 1 - - - -

sample 1**** 3.76 1.000 2.89 1.000

sample 2 - - - -

sample 2*** 2.94 1.000 0.9929

sample 2**** 3.82 1.001 2.93 1.000 0.9913

sample 3 - - - -

sample 3*** 3.82 1.000 0.9970 2.96 1.000 0.9934

sample 3**** 3.84 1.000 0.9963 2.95 1.000 0.9939 *** signifies that the last measured data point was not included in the calculations. **** refers to exclusion of the last two data points in the calculations.


98

3.3.5 Analysis of emulsions with the hydrophilic surfactant whey protein isolate

In this experiment, w/o-emulsions were made with whey protein isolate (WPI) as the

hydrophilic surfactant in a concentration of 1.25% (w/v) instead of sodium caseinate.

The fat phase was Hozol with 2.5% (w/v) PGPR and the air pressure was set at 6bar

in the Microfluidizer. The mass fraction of water was 50% and contained 0.5% (w/v)

eosinY. During manufacturing, some clumps could be observed. This might be due to

thermal denaturation of the whey protein isolate, since during premixing with an

Ultraturrax device, temperatures run up to 60°C. The volume-weighted arithmetic

mean diameters as obtained by the Droplet Size application and Matlab are collected

in Table 3.11. The script that was used was DSD_Lien.RIS.tif. The water diffusion

coefficient in the serum at 5°C amounted to 1.288E-09 m2/s for sample 1 and 2, and

1.281E-09 m2/s for sample 3. The average and standard deviation of the D43 obtained

by the Droplet Size application was 3.93µm and 0.15µm.

Table 3.11: Volume-weighted arithmetic mean diameter and geometric standard deviation of three samples (H1.25/2.5) with WPI as hydrophilic surfactant. Data are obtained by the Droplet Size application and Matlab. R-squared is given when different outcomes for one sample were collected. Flat bars denote that no results could be obtained. Droplet Size application Matlab

D43 (µm) σg R2 D43 (µm) σg R2

sample 1 - - - -

sample 1 *** 3.94 1.008 - -

sample 2 - - - -

sample 2 *** 3.78 1.000 - -

sample 3 4.12 1.169 0.9953 3.14 1.118 0.9968

sample 3 *** 4.18 1.268 0.9969 3.17 1.207 0.9979 *** signifies that the last measured data point was not included in the calculations.

There is no significant difference of the mean volume-weighted arithmetic mean

diameter, obtained by the Droplet Size application, between the samples made with

WPI and samples made with sodium caseinate (see section 3.3.3, H1.25/2.5)(p=0.29).

WPI differs from sodium caseinate in its molecular size and hence speed of reaching

the interfacial area. Since emulsions were aged for 24h, the WPI had sufficient time to

reach the water oil interface. Besides the time aspect, also the concentration and type

of the surfactant determines the water droplet size in w/o-emulsions which are made

in identical preparation conditions.


99

3.4 Qualitative particle size analysis of water droplets in w/o-emulsions by

fluorescence microscopy

3.4.1 Preliminary investigation of eosinY-solutions by fluorimetry

The aim of the fluorimetric investigation of eosinY in solution was to visualize water

droplets in a w/o-emulsion, which contains eosinY in the water phase. As mentioned

in section 3.3.3, the w/o-emulsion with 50% water contained 1.25wt% sodium

caseinate, a phosphate buffer (pH6.7) and 0.02wt% sodium azide. In order to see the

effect of these compounds on the maximum excitation and emission wavelength of

eosinY (5µg/mL), four different solutions were made and kept at room temperature.

The first solution was eosinY in distilled water. The second solution contained eosinY

and phosphate buffer in distilled water. The third solution comprised eosinY,

phosphate buffer and sodium azide in distilled water. The ingredients of the fourth

solution were eosinY, phosphate buffer, sodium azide and sodium caseinate in

distilled water. All four solutions were scanned at excitation and emission

wavelengths from 450 to 600nm. Afterwards, the maximum excitation or emission

wavelength was determined at narrower emission or excitation wavelength ranges,

respectively.


(5µg/mL) in water

For more detailed information about the excitation scan in Figure 3.10a, reference is

made to section 2.4.4.3. In Figures 3.10a and 3.10b the maximum excitation

wavelength lies in the heavily red or white colored area, respectively, which is located

between 510 and 520nm wavelength. Some scattering due to suspended particles in

the eosinY-solution at the bisection can be observed. The maximum excitation

wavelength of eosinY in water was extracted from the emission spectra at 533-543nm

with excitation at 470-540nm and amounted to 517nm.


100

450 500 550 6000

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Inte

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ity

(a

.u.)

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450.00 475.00 500.00 525.00 550.00 575.00 600.00

701.64647.57593.51539.44485.38431.31377.24323.18269.11215.05160.98106.9252.85-1.22

Figure 3.10a: EosinY in water (5µg/mL). Contour plot of the scan for excitation and emission wavelength ranging from 450 to 600nm in 75 steps of 2nm. X-axis: excitation wavelength (nm). Z-axis: number of steps that are used to go from 450 to 600nm emission wavelength. Red color denotes high intensity, blue color denotes low intensity.

Figure 3.10b: EosinY in water (5µg/mL). 3D-plot of the scan for excitation and emission wavelength ranging from 450 to 600nm. X-axis: excitation wavelength (nm). Y-axis: fluorescence intensity (arbitrary units). Z-axis: number of steps to go from the first to the last selected emission wavelength.

Information about the maximum emission wavelength can be obtained from the Z-

axis in Figure 3.10a. The values 42 and 48 on the Z-axis border the heavily red area

and correspond to an emission wavelength of 534nm and 546nm by conversion with

Equation 2.13. Figure 3.11 is a mirror image of Figure 3.10 by reflection around the

bisection and it shows that the maximum emission wavelength lies between 533 and

545nm and it confirms that the maximum excitation wavelength can be found

between Z-axis values of 32 (or 514nm) and 38 (or 526nm), as described in section

2.4.4.3. The emission maximum was obtained by selecting a range of excitation


101

wavelengths from 510 to 520nm (first method, see section 2.4.4.3) and amounted to

538nm.

450 500 550 6000

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.u.)

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450.00 475.00 500.00 525.00 550.00 575.00 600.00

735.10678.44621.77565.11508.45451.79395.13338.47281.81225.14168.48111.8255.16-1.50

Figure 3.11a: EosinY in water (5µg/mL). Contour plot of the scan for emission and excitation wavelength ranging from 450 to 600nm in 75 steps of 2nm. X-axis: emission wavelength (nm). Z-axis: number of steps to go from the first to the last selected excitation wavelength. Red color denotes high intensity, blue color denotes low intensity.

Figure 3.11b: EosinY in water (5µg/mL). 3D-plot of the scan for emission and excitation wavelength ranging from 450 to 600nm. X-axis: emission wavelength (nm). Y-axis: fluorescence intensity (arbitrary units). Z-axis: number of steps to go from the first to the last selected excitation wavelength.


(5µg/mL) in an aqueous phosphate buffer (pH6.7)

Figure 3.12 unravels that the maximum excitation wavelength is situated between 500

and 530nm. The maximum excitation wavelength was acquired from sub maximum


102

emission wavelengths, namely from 565 to 575nm (second method, see 2.4.4.3) and

was found to be 517nm. Figure 3.12 reveals a maximum emission wavelength range

of 534 to 562nm. Fluorescence spectra obtained at excitation wavelengths ranging

from 457 to 467nm revealed that a maximum emission wavelength can be found at

540nm. Whereas the fluorescence intensity of eosinY in water (Figure 3.11b)

remained below 1000a.u., the addition of phosphate buffer to eosinY increased the

intensity. Moreover, in the latter less scattering can be observed.

450 500 550 6000

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450.00 475.00 500.00 525.00 550.00 575.00 600.00

962.91888.74814.56740.39666.21592.04517.87443.69369.52295.34221.17146.9972.82-1.36

Figure 3.12: EosinY (5µg/mL) in aqueous phosphate buffer (pH6.7) in 75 steps of 2nm. Contour plot of the scan for emission and excitation wavelength ranging from 450 to 600nm. X-axis: excitation wavelength (nm). Z-axis: number of steps to go from the first to the last selected emission wavelength. Red color denotes high intensity, blue color denotes low intensity.


(5µg/mL) in aqueous phosphate buffer (pH6.7) with sodium azide (0.02%, w/v)

The maximum excitation wavelength can be found from 495 to 533nm (Figure 3.13).

The maximum excitation wavelength is 517nm and was measured at an emission

wavelength range of 565 to 575nm. The maximum emission wavelength is located

between 530 and 560nm (Figure 3.13) and amounted to 542nm, which was measured

at an excitation wavelength range of 500 to 570nm. The shoulder at 480-482nm as

seen in Figure 3.10 to 3.12 is also present in Figure 3.13.


103

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962.91888.74814.57740.39666.22592.05517.87443.70369.52295.35221.18147.0072.83-1.34

Figure 3.13: EosinY (5µg/mL) in aqueous phosphate buffer (pH6.7) with sodium azide (0.02%). Contour plot of the scan for emission and excitation wavelength ranging from 450 to 600nm in 75 steps of 2nm. X-axis: excitation wavelength (nm). Z-axis: number of steps to go from the first to the last selected emission wavelength. Red color denotes high intensity, blue color denotes low intensity.


(5µg/mL) in aqueous phosphate buffer (pH6.7) with sodium azide (0.02%, w/v) and

sodium caseinate (1.25%,w/v)

The maximum excitation wavelength is located between 510 and 542.5nm (Figure

3.14). Fluorescence spectra at emission wavelengths ranging from 566 to 576nm

revealed a maximum excitation wavelength at 527nm. Figure 3.14 reveals a

maximum emission wavelength range of 533 to 565nm. Fluorescence spectra

obtained at excitation wavelengths ranging from 500 to 510nm revealed a maximum

emission wavelength at 547nm.

This eosinY-solution, in comparison to solutions in the absence of the protein,

demonstrated a red-shift in the excitation and emission spectra. Less pronounced

scattering is expected inside an emulsion, as sodium caseinate will migrate

preferentially to the interface.


104

450 500 550 6000

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962.94888.82814.70740.58666.46592.34518.22444.10369.98295.86221.74147.6273.50-0.62

Figure 3.14: EosinY (5µg/mL) in aqueous phosphate buffer (pH6.7) with sodium azide (0.02%) and sodium caseinate (1.25%). Contour plot of the scan for emission and excitation wavelength ranging from 450 to 600nm in 75 steps of 2nm. X-axis: excitation wavelength (nm). Z-axis: number of steps to go from the first to the last selected emission wavelength. Red color denotes high intensity, blue color denotes low intensity.

3.4.6 Selection of the filter block in the fluorescence microscope

Table 3.12 gives an overview of the obtained maxima of excitation and emission

wavelength for different aqueous solutions. The water phase of the water-in-oil

emulsions consisted of sodium caseinate, phosphate buffer and sodium azide. Hence,

the outcomes of this solution (Figure 3.14) are compared to the available filter blocks

in the fluorescence microscope. Filter block I2/3 is appropriate in terms of passing

through wavelengths which include the maximum emission wavelength of the

eosinY-solution. However, the excitation filter passes wavelengths which are located

in the sub maximum excitation regions. Filter block N2 is appropriate in terms of

passing through wavelengths which are close to the maximum excitation wavelength

of the eosinY-solution. However it fails in picking the wavelengths that correspond to

maximal fluorescence intensity. Consequently, filter block I2/3 was preferred,

although it is not perfect for eosinY-solutions.

Table 3.12: Overview of maximum excitation and emission wavelengths for different aqueous solutions of eosinY. E=eosinY (0.001%w/v), PE=eosinY and phosphate buffer (pH6.7). PNE=eosinY, phosphate buffer and NaN3 (0.02%w/v). PNEN= eosinY, phosphate buffer, NaN3 and Na caseinate (1.25% w/v). Max. excitation λ (nm) Max. emission λ (nm) E 517 538 PE 517 540 PNE 517 542 PNEN 527 547

I2/3 filter block BP 450-490 LP 520

N2 filter block BP 530-560 LP 580


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3.4.7 Fluorescence microscopic images of water droplets in a w/o-emulsion

The analyzed emulsion contained 50wt% water, in which 0.001% (w/v) eosinY,

1.25% (w/v) sodium caseinate, phosphate buffer (pH6.7) and sodium azide (0.02%,

w/v) was included. The oil phase was Hozol with 2.5% (w/v) PGPR. The emulsion

was covered with aluminum foil and diluted ten times with Hozol just before

microscopic analysis.

As mentioned in section 3.4.6, the selected filter block I2/3 is not perfect for eosinY.

Consequently, a weak fluorescence of not well-defined water droplets is observed

(Figure 3.15). Both small and bigger (about 10µm) droplets can be noted.

Figure 3.15: (Top) Light microscopic image. (Bottom) Fluorescent microscopic image. Ten times diluted H1.25/2.50 (three days old) with Hozol. Concentration of eosinY in water phase is 0.001%. Objective x100.


106

3.4.8 Imaging of water droplets in water in oil emulsions by confocal laser scanning

microscopy

Figure 3.16 is a (negative) confocal laser scanning microscopic (CLSM) image of a

w/o-emulsion with more appropriate absorption (514nm) and excitation filters

(538nm) than the light and fluorescent microscopic image (Figure 3.15). Smaller

water droplets in the size range of 3 to 4µm can be observed than in Figure 3.15. This

might be explained, on the one hand, by the difference in time elapse between

emulsion preparation and shooting of the pictures. This could be investigated by pfg-

NMR analysis of w/o-emulsions as a function of time. On the other hand, CSLM

doesn’t require a cover glass, which might in the case of fluorescence microscopy,

cause water droplets to coalesce under the influence of pressure. van Aken and Zoet

(2000) defined coalescence of water droplets by pressure of cover slips as coalescence

induced by flow, which gradually increases upon increase of dispersed phase. The

CSLM-sample is investigated by an objective which is placed under the objective

glass, whereas for fluorescence microscopy, the objective is located above the

objective glass and hence the latter requires separation by means of a cover glass.

Moreover the required dilution step in fluorescence microscopy induces flow in the

emulsion, which might affect the coalescence rate. All the mentioned reasons point in

the direction of the CSLM-image as a more correct representation of the water

droplets. However, in order to assess the cause of the observed difference in water

droplets between the two microscopic devices, more investigation is needed.

Figure 3.16: Confocal laser scanning microscopic (negative) image of an undiluted w/o-emulsion, H1.25/2.50 (24h after preparation). Concentration of eosinY in water phase is 0.001%.


107

3.5 Determination of the enclosed water volume and yield of w/o/w-emulsions

3.5.1 Method optimization

The optimization of the determination of the enclosed water volume of double

emulsions consisted of the creation of a double emulsion and the quest for an

appropriate concentration of MnCl2 enabling the characterization of double

emulsions. Moreover it was investigated whether the usage of T2-analysis to

characterize a double emulsion at 5°C was authorized and the preparation method for

double emulsions was further optimized by investigation of the effect of the duration

of mixing and the cooling conditions on the enclosed water volume or yield.

3.5.1.1 Optimization of the preparation method

The aim was to find a preparation method that resulted in a double emulsion with a

significant fraction of enclosed water. A w1/o-emulsion is emulsified in an external

water phase (w2) which results in a w1/o/w2-emulsion. As such, an oil in water

emulsion is obtained, in which the fat phase encloses water and hence the caloric

content is reduced.

As described in section 2.5.2.1, Method A comprises the application of an Ultraturrax

TV45 and a Microfluidizer for the manufacturing of both w/o-emulsions and w/o/w-

emulsions. Twenty four hours after production, the double emulsions were

characterized by a low (<4%) or no enclosed water volume, as determined by T2-

relaxation measurements at 5°C after addition of volumes up to 100µL MnCl2

(10mM) to a sample of 8mL. These findings can be explained by either the absence of

internal water or the permeability of the fat phase. The latter is investigated in section

3.5.1.3. Absence of internal water might be due to the presence of an osmotic gradient

between the water phases in a w/o/w-emulsion or due to destruction of the double

emulsion during preparation. To exclude the possibility of lack of internal water due

to osmotic pressure gradients induced by MnCl2 addition, the osmolarity of

components of the water phase was calculated by multiplication of the molarity (C)

by the amount of dissociated particles per mole (i). The osmotic pressure was

determined by the formula of van ‘t Hoff: Π = iCRT, where (iC) stands for the


108

osmolarity (osm/m3), R and T signify the gas constant (8.314J/mol/K) and the

absolute temperature (K).

From Table 3.13, it is clear that there is a small osmotic pressure difference of 1.3kPa

between the water phases. Hence, this physical property plays a minor role in the lack

of internal water. In fact, a minor transport of water from the w1 to the w2-phase

would restore the osmotic equilibrium.

Table 3.13: Calculation of the osmotic pressure in kPa at 278K (storage temperature)

W1-phase Concentration

(g/100mL) Molar mass

(g/mole) Molarity

(mM) Osmolarity (osm/m3)

Osmotic pressure (kPa)

eosinY 0.0010 647.90 0.015 <0.050 Sodium azide 0.0200 64.99 3.10 6.20 Sodium caseinate 1.2500 3E+05 0.042 <0.050 KH2PO4 0.8491 136.09 61.3 123 K2HPO4 0.6731 174.14 38.6 116

244.6 565.4

W2-phase Sodium azide 0.0200 64.99 3.10 6.20 Sodium caseinate 1.0000 3E+05 0.033 <0.050 KH2PO4 0.8491 136.09 61.3 123 K2HPO4 0.6731 174.14 38.6 116 max. MnCl2 0.0025 125.84 0.200 0.600 245.2 566.7 The inexistence of internal water might be due to the destruction of the double

emulsion by the Microfluidizer at the applied homogenization pressure and time

duration. Samples were collected before and after the second application of the

Microfluidizer step. The emulsions that were collected before the Microfluidizer step

demonstrated separation of an upper creamy layer and a lower water phase in less

than 24h. As judged by the ratio of the thickness of the layers (Figure 3.17) and by T2-

relaxation measurements (Figure 3.18), internal water was present before

microfluidization of the double emulsion. Figure 3.17 shows a lower serum layer and

an upper cream layer. It was clear that the ratio of the volume of the separated phases

of a non-microfluidized sample was not equal to the ratio of a sample with unmixed

pure oil phase and water phase (20:80), but rather similar to the ratio of the volumes

in a sample with unmixed w/o-emulsion and external water (40:60). Hence, the visual

creaming aspect already provided a strong indication that (at least part of) the water

remained encapsulated within the oil phase.


109

Figure 3.17: Photograph of unmixed sample of oil and external water (20:80), an unmixed sample of w/o-emulsion (P1.25/2.5) and external water (40:60) and a separated non-microfluidized w/o/w-emulsion (P1.25/2.5/1).

In Figure 3.18, the T2-distribution of a microfluidized and non-microfluidized sample

is depicted. In the former T2-distribution, the peak associated with internal water is

absent. Hence, the microfluidized emulsion, which was homogeneously distributed

throughout the length of the NMR-tube, can be regarded as a o/w emulsion.

Consequently, in order to result in a w/o/w-emulsion, the mixing of a w/o-emulsion

with the external water phase should be performed without the usage of a

Microfluidizer M110S.

0

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300

400

500

600

700

800

1000 10000 100000 1000000 10000000

Time (µs)

Sig

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itude

Beforemicrofluidization

Aftermicrofluidization

Figure 3.18: T2-distribution of a sample before and after microfluidization (P1.25/2.5/1) with addition of 100µL of 10mM MnCl2 to 8mL vortexed sample.

Serum layer

Cream layer


110

3.5.1.2 Finding an appropriate concentration of MnCl2

Figure 3.19 schematically represents the effect of the addition of no, insufficient,

sufficient and too much MnCl2 to a double emulsion on the T2-distribution. In the

absence of MnCl2, a small fraction of low T2 and a large fraction of high T2 was

observed, which is ascribed to fat and water, respectively. It was seen that 25 to 50µL

of 10mM MnCl2 in a sample of 8mL was insufficient to fully separate the signals that

are related to the internal (not influenced by MnCl2) and external water (affected by

MnCl2) in the T2-distribution. Higher volumes than 100µL of 10mM MnCl2 per 8mL

sample fused the signals that are related to the fat phase and the external water.

Hence, either 75µL or 100µL of 10mM MnCl2 per 8mL sample was found an

appropriate amount of MnCl2. This comes down to a concentration of 94 to 125µM

MnCl2 in the double emulsion (i.e. 156 to 208µM MnCl2 in the external water phase).

Figure 3.19: Schematic representation of the effect of MnCl 2 addition on the T2-distribution of a multiple emulsion.

3.5.1.3 Investigation of the permeability of the oil phase by a temperature experiment

Sabatino et al. (2011) reported that a reliable characterization of a vesicular dispersion

by T2-analysis is possible when there is no permeability of the bilayer. Since the


111

bilayer in a liposome acts as a physical barrier similar to the fat phase in a double

emulsion, the permeability of the latter was evaluated by performing a temperature

experiment. Impermeability of the fat phase at the applied temperature, authorizes the

usage of T2-analysis to characterize a double emulsion.

Three 8mL samples, which were made in accordance to Method B (see section

2.5.2.2), with composition P1.25/2.5/1 and 0µL (sample 0), 75µL (sample 1) and

100µL (sample 2) of 10mM MnCl2, added prior to analysis were heated successively

from 5°C to 25°C and 45°C in a warm water bath. Afterwards, the samples were

cooled for 1.5h at 5°C. At each mentioned temperature, T2-relaxation measurements

were performed. In Figure 3.20, the effect of temperature on the T2-distribution in

Sample 1 is given. Whereas at 5°C a clear separation of the two water peaks is visible,

this doesn’t hold anymore at 25°C and 45°C. Comparing sample 0 (Figure 3.21) and

sample 1 (Figure 3.20) at 5°C, it is clearly observed that the addition of MnCl2

separates the water signal into two peaks: a peak characterized by medium relaxation

(or medium relaxation time mode), which corresponds to the external water and a

peak characterized by slow relaxation (or large relaxation time mode), which is

associated with the internal water phase. The signal of the fat phase (fast relaxation

time mode) is located at shorter times. Evaluation of the permeability and the effect of

temperature on the T2-distribution is done by analysis of the area under the curve, the

signal amplitude and the relaxation time at different temperatures.

5°C

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25°C

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45°C

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Back to 5°C

-200

0

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600

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1000

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1 10 100 1000 10000

Time (ms)

Sig

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75µL MnCl2

Figure 3.20: Effect of temperature (5°C, 25°C, 45°C and back to 5°C) on the T2-dsitribution of Sample 1(P1.25/2.5/1, 1st repetition) upon addition of 75µL of 10mM MnCl2 to 8mL of vortexed double emulsion.


113

5°C

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200400600800

1000120014001600

1000 10000 100000 1000000 10000000 100000000

Time (µs)

Sig

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mpl

itude

Without MnCl2

Figure 3.21: T2-distribution of sample 0 (P1.25/2.5/1 without MnCl2 addition) 3.5.1.3.1 Analysis of the area under the curve at different temperatures

Figure 3.22 depicts the difference in area under the curve of Sample 1 and 2 at 5°C

before and after heating. Since Sample 1 was measured once only at 5°C, Sample 2

was statistically analyzed. The mean area under the curve that is related to the

external water (medium relaxation) significantly decreases after thermal treatment

(p=0.0383). Considering Sample 2, the mean area under the curve that is associated

with fat (fast relaxation) and internal water (slow relaxation) significantly increases

after a heat-cool experiment (for both p=0.0383). Consequently, the mean enclosed

water volume of three repetitions of Sample 2 at 5°C significantly increases

(p=0.0361) after heat application with a factor 1.84 from 16.2% ± 0.6 to 29.8% ± 0.3.

Sample 1 confirms the change of the area under the curve and enclosed water fraction

after heat application.


114

13902

1385313598

14355

0

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12000

14000

16000

Fast relaxation Medium relaxation Slow relaxation

Are

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urve

5°C (sample 1)

Back to 5°C (sample 1)

5°C (sample 2)

Back to 5°C (sample 2)

Total AUC 5°C (sample2)

Total AUC back to 5°C (sample1)

Total AUC 5°C (sample 1)

Total AUC back to 5°C (sample 2)

Figure 3.22: Area under the curve as a function of relaxation time at 5°C before and after heat application. Error bars denote the standard deviation of three repetitions of Sample 1 and 2, except Sample 1 at 5°C, which was measured once only. The total area under the curve is represented by a flat horizontal line and amounts to 13853 and 13598 for Sample 1 at 5°C and back to 5°C, respectively, whereas for Sample 2 this is equal to 13902 and 14355, respectively.

Regarding the change of the area under the curve related to fat, this might point out

the possibility of transition of the type of polymorphs of the fat crystals in soft PMF.

The latter is provoked in a process called tempering. One polymorph differs from the

other in melting point, stability, density, melting enthalpy and nucleation rate. In

general, tempering results in more stable polymorphs that are characterized by a

higher melting point, higher density, higher melting enthalpy and lower nucleation

rate (Dewettinck and Fredrick, 2010). This comes down to a more solid like fat phase,

characterized by the selection of a certain type of polymorphs upon a heat-cool

experiment. However, since polymorphs are very small (ångström scale), the

observed change in area under the curve related to fat might be due to slow

crystallization, whereby after cooling to 5°C, a larger fraction of the fat phase remains

liquid.

Figure 3.23 and Table 3.14 indicate that at 25°C the area under the curve for fast

relaxing hydrogens (fat phase) can be recorded in Sample 1, whereas in Sample 2 the

signal related to fat is absent. At 45°C, at which there is less fat crystallization, the

signal of the fat phase in Sample 2, expressed in units of area under the curve, is not

significantly lower in comparison to the initial 5°C (p=0.1). Cooling to 5°C

significantly increases the mean area under the curve for fat in comparison to 45°C, in

virtue of the liquid-solid phase transition (both p=0.0383 for Sample 1 and 2). On the


115

one hand, upon temperature rise, a larger signal for more mobile protons might be

expected since the liquid fat fraction increases. On the other hand, at 45°C soft PMF

is completely liquid, but the incubation time (about 30 minutes) might have been too

limited and hence, a fraction of soft PMF might have been still solid. The liquid

fraction is expected to relax slower than the solid fraction. Consequently, the area

under the curve of the fat signal at 45°C might be smaller than at 5°C, due to a shift of

the more liquid fraction of soft PMF towards the signal of the external water.

However, this would coincide with an increase of the area under the curve of the latter

signal, which cannot be evaluated from Table 3.14.

-200

0

200

400

600

800

1000

1200

1400

1600

1800

5 25 45 5Temperature (°C)

AU

C Oil peak (sample1)

Oil peak (sample2)

Figure 3.23: Effect of temperature on the area under the peak associated with the fastest relaxation time for two samples. Each sample at each temperature is analyzed three times, except Sample 1 at 5°C, which is analyzed once only. Error bars denote the standard deviation of three repetitions.

Due to lack of separation of signals in the T2-distribution at higher temperatures,

nothing can be stated about the enclosed water volume upon temperature increase. A

similar temperature experiment on vesicular dispersions was performed by Sabatino et

al. (2011) and this study concluded that upon temperature rise, the real enclosed water

volume doesn’t change, whereas the estimated enclosed water volume might decrease

due to fast exchange of water between the internal and external water phase.


116

Table 3.14: Area under the curve for fast relaxation (fat), medium relaxation (external water) and slow relaxation (internal water) at 5, 25, 45 and back to 5°C. Each sample is analyzed three times per temperature, except the first sample at 5°C which is analyzed once. Some cells are merged together due to lack of separation of peaks. Sample 1

Temperature (°C) AUC (fat) AUC (Ext. water) AUC (Int. water) Total AUC

5 616 10857 2380 13853

25 1573 12876 14449

25 1696 12471 14167

25 1490 12699 14189

45 14035 14035

45 13903 13903

45 13767 13767

5 1609 7321 4668 13598

5 1568 11934 13502

5 1511 11847 13358

Sample 2

5 425 11458 2098 13981

5 551 11137 2221 13909

5 540 11091 2186 13817

25 15971 3057 19028

25 15182 3963 19144

25 15056 4175 19231

45 106 14243 14349

45 63 14200 14263

45 517 10767 2853 14137

5 1711 9019 3898 14628

5 1481 8959 3778 14218

5 1481 8959 3778 14218

3.5.1.3.2 Analysis of the signal amplitude at different temperatures

At all investigated temperatures, the mean maximal signal amplitude of the T2-distribution

is reached at medium relaxation times (Table 3.15) and is significantly smaller at 45°C than

at the initial 5°C (p=0.05). This means that at increasing temperatures, the peaks flatten and

widen in such a way that they merge together. This might point to the possibility of thermal

destruction of the double emulsion or permeability of the fat phase for water or MnCl2 at

higher temperatures. However, upon cooling after heating, the peak of internal water pops

up again, which indicates that the double emulsion is not destructed by the applied

temperature rise, nor that there is physical contact, which is irreversible, of the internal

water phase with the external water phase wherein MnCl2 is dissolved. Hence, even at

higher temperatures, the permeability of soft PMF for MnCl2 does not impose restrictions


117

regarding the authorization of the usage of T2-analyses at 5°C for double emulsions based

on soft PMF.

A broader distribution of the signals in the T2-distribution or lower resolution at higher

temperatures might refer to a less homogeneous relaxation behavior of hydrogens in the

same environment upon temperature rise.

Also in Table 3.15, the high values of signal amplitude for the medium relaxation mode

are attributed to completely fused signals associated with the medium and fast relaxation

mode.

Table 3.15: Maximal signal amplitude at different relaxation times in the T2-distribution of two samples, analyzed thrice. Values in bold denote maximal signal amplitude per temperature and per repetition. Empty cells refer to missing data. Sample 1

Fast relaxation mode Medium relaxation mode Slow relaxation mode

T (°C) 1st rep. 2nd rep. 3rd rep. 1st rep. 2nd rep. 3rd rep. 1st rep. 2nd rep. 3rd rep.

5 171 1206 449

25 234 305 217 827 1054 775 470 755 439

45 64 110 0 844 791 570 458 412 0

5 471 180 146 1140 832 716 1044 698 542

Sample 2

5 159 296 285 1304 1663 1628 352 367 380

25 0 0 0 1887 8120 11103 382 1854 2746

45 16 21 176 853 773 1018 246 179 385

5 305 155 155 1230 977 1135 908 617 617

3.5.1.3.3 Analysis of the relaxation time at different temperatures

Upon temperature rise, it is expected to observe an increase of relaxation time, since

hydrogens become more mobile and the relaxation takes longer.

Fast, medium and low relaxation times at maximal signal amplitude in the T2-distribution for

different temperatures are summarized in Table 3.16 and Figure 3.24, in which a significant

increase of relaxation time can be detected for the fast relaxation mode upon temperature

increase from 5°C to 45°C (p=0.0383). In an additional experiment, two NMR-tubes were

filled with 16mL soft PMF and with Hozol. The purpose of this experiment was to found out

whether emulsification of fat globules affects the influence of temperature on the fast

relaxation mode. The bulk fat samples were subjected to 5°C, 25°C and 45°C (Figure 3.25).

Since the receiver gain of the spectrometer is optimized prior to analysis and hence, the


118

signal is optimally amplified, useful information can be drawn from the relaxation time

instead of the area under the curve. Heating soft PMF or Hozol results in an increase of the

relaxation time of the signal at the fast relaxation mode. In conclusion, a temperature rise has

a decisive effect on the fast relaxation mode of bulk fat and this can be confirmed in the

analyzed samples with emulsified fat. In Figure 3.25 also bulk water without MnCl2 was

subjected to the same conditions. An increase of the relaxation time is observed when the

temperature rises from 25°C to 45°C.

Regarding signals at medium relaxation times of the double emulsion, significantly slower

mean relaxation time of the hydrogen atoms is recorded on account of higher mobility of

hydrogen atoms as temperature increases from 5°C to 25°C and from 25°C to 45°C (p<0.04).

As a consequence, longer relaxation times are recorded.

Concerning slow relaxing hydrogens (internal water), a significantly larger mean relaxation

time is noted at 45°C than at (initial) 5°C (p=0.0381).

After cooling, two peaks, associated with fast relaxation, are created, which reflects the

presence of hydrogens in different environments. For Sample 1, these are located at 3.9 and

12.1ms. For Sample 2, these can be found at 3.4 and 10.5ms.

Table 3.16: Fast, medium and slow relaxation time modes (ms) at different temperatures (°C) of Sample 1 and 2. Flat bars refer to absence of signal. Empty cells denote no measurements. Sample 1

Fast relaxation mode Medium relaxation mode Slow relaxation mode

T(°C) 1st rep. 2nd rep. 3rd rep. 1st rep. 2nd rep. 3rd rep. 1st rep. 2nd rep. 3rd rep.

5 10 99 675

25 16 18 16 120 120 120 818 743 818

45 28 38 - 194 194 176 1202 1202 -

5 4 4 4 109 99 99 506 557 557

14 12 10

Sample 2

5 10 12 12 74 67 67 613 557 557

25 - - - 99 120 132 901 901 992

45 33 13 38 160 160 160 1323 1457 1202

5 3 3 3 82 82 82 506 506 506

12 10 10


119

0

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Sig

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of t

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5°C (Sample 1)

25°C (Sample 1)

45°C (Sample 1)

0

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Modal relaxation time (ms)

Sig

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mpl

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of t

he m

ode

5°C (Sample 2)

25°C (Sample 2)

45°C (Sample 2)

Figure 3.24: Exposition of the signal amplitude of the different peaks in the T2-distribution of Sample 1 (Top) and Sample 2 (Bottom) as a function of the relaxation time of three repetitions of one sample at 5, 25 and 45°C, except Sample 1 at 5°C, which is analyzed once only.

By calculation of the ratio of average modal values of the fast and slow relaxation time for

each sample (Table 3.17), it can be seen that both relaxation times of the signals of internal

and external water shift to larger times, which might contribute to the drop in resolution of the

T2-distribution. Therefore, T2-measurements should be performed at a low temperature to

optimize the resolution of the T2-distribution.


120

0

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25°C soft PMF

45°C soft PMF

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45°C Hozol

0

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1500

2000

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time (ms)

Sig

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5°C water

25°C water

45°C water

Figure 3.25: T2-distribution of soft PMF, Hozol and water, analyzed at different temperatures.


121

Table 3.17: Average relaxation time mode of three repetitions per sample that correspond to signal amplitude for external (medium relaxation) and internal (slow relaxation) water. Factor denotes the ratio of increase in average time between two subsequent temperatures. Stand. dev. and Stand. dev. (Factor) refer to the standard deviation of three measured relaxation time modes and Factors at one temperature, respectively.

Sample T(°C)

Medium relaxation time

mode (ms)

Stand. Dev. (ms)

Factor

Stand. dev. (Factor)

Large relaxation time

mode (ms)

Stand. dev. (ms)

Factor

Stand. dev. (Factor)

1 5°C 98.8 0 675.0 0

25°C 119.7 0 1.2 - 793.0 43.3 1.2 -

45°C 188.0 10.4 1.6 0.09 1165.3 63.5 1.5 0.14

1.9 - 1.7 -

2 5°C 69.5 3.9 575.7 32.3

25°C 117.0 16.7 1.7 0.33 931.3 52.5 1.6 0.16

45°C 160.0 0 1.4 0.21 1327.3 127.5 1.4 0.21

2.3 0.13 2.3 0.32

3.5.1.3.4 Variation of the duration of mixing of the double emulsions

By variation of the duration of the Ultraturrax mixing of the double emulsions, a maximum

enclosed water volume or yield was strived after. The theoretically possible enclosed water is

20g on 80g of total water in the w/o/w-emulsion (20:20:60). The duration of mixing with the

Ultraturrax S25N-10G at 24000rpm was set at 2min, while mixing with the Ultraturrax DK25

at 24000rpm was performed for 1, 2, 4, 6 or 8 minutes. It is essential to subject equal amounts

of sample to the different mixing times.

In this experiment, the w/o/w-emulsions were made in accordance to Method B (see section

2.5.2.2) with soft PMF as a fat phase. Before analysis, samples of 8mL were vortexed and

meanwhile 75 or 100µL of 10mM MnCl2 was added. Regarding gravitational stability, the

double emulsions creamed after 24h. The T2-relaxation distribution was measured after 24h

and illustrated in Figure 3.26, from which it is clear that a larger duration of mixing with the

Ultraturrax DK25 resulted in less enclosed water volume or a lower yield. Based on the

experimental data, at least one difference between the different durations of mixing on the

mean enclosed water volume (or the mean yield) can be detected (p=0.009). A significant

difference between mixing the double emulsion for 1 minute or 8 minutes was observed on

the mean enclosed water volume percentage (p=0.0383). Hence, the highest yield is achieved

after mixing with an Ultraturrax DK25 for 1 minute and all subsequent emulsions were

prepared like this.


122

According to the manual of the device, longer mixing times don’t achieve further reduction of

droplet size, but only an increase of temperature, which might destroy the double emulsion

and cause the drop of the enclosed water volume.

0

2

4

6

8

1012

14

16

18

20

0 1 2 3 4 5 6 7 8 9

Mixing time with Ultraturrax DK25 (min)

Est

imat

ed e

nclo

sed

wat

er

volu

me

(%)

0

10

20

30

40

50

60

70

80

Yie

ld (

%)

Figure 3.26: Effect of mixing time (minutes) of a w1/o/w2-emulsion with an Ultraturrax DK25 (24000rpm) on the enclosed water volume (%) and yield (%) by T2-relaxation measurements. Error bars denote the standard deviation of 3 subsequent measurements of the yield of one sample. All samples needed 75µL of 10mM MnCl 2, except the sample of 4 minutes to which 100µL of 10mM MnCl 2 was added to 8mL of double emulsion.

3.5.1.3.5 Effect of the reduction of the duration of mixing with an Ultraturrax S25-10G

In this experiment the effect of the reduction of the duration of mixing with an Ultraturrax

S25-10G on the enclosed water volume or yield was evaluated.

Double emulsions were made by Method B, whereby the duration of mixing with an

Ultraturrax S25-10G was changed from 2 minutes to 1 minute. In the case of 1 minute

mixing, the average enclosed water volume and standard deviation, based on three repetitions

of the same sample, amounted to 18.3% and 0.1%, respectively. For the sample that was

mixed for 2 minutes, this amounted to 18.6% and 0.1%, respectively. No significant

difference of mixing one minute longer with the Ultraturrax S25-10G on the mean percentage

of enclosed water volume (p=0.0722) was observed. In order to provide a balance between

sufficient mixing and the prevention of destruction of the double emulsion, all subsequent

emulsions were prepared by mixing for 2 minutes, because this didn’t reveal more destruction

than mixing for 1 minute with an Ultraturrax S25-10G.


123

3.5.1.3.6 Effect of quick cooling on the percentage of enclosed water volume

In comparison to bulk fat, fat in emulsion globules is shielded from catalytic impurities for

crystallization by emulsification. Hence, emulsified fat requires a higher density of catalytic

impurities or more likely a higher degree of supercooling to induce nucleation than bulk fat.

Quick cooling by means of placing emulsions after production directly in an ice bath, might

result in more supercooling of the fat in the globules as compared to samples cooled in the

fridge and more fine crystals.

Figure 3.27 shows the enclosed water volume and yield for double emulsions samples, made

in accordance to Method B (see section 2.5.2.2), that are cooled in an ice bath or in the fridge.

The oil phase in this experiment is a mixture of soft PMF and Hozol (87.5/12.5) with 2.5%

PGPR. After 24h, samples of both cooling regimes were characterized by a creamy layer.

By statistical analysis, there was at least one difference between the four analyzed samples on

the mean enclosed water (p=0.0143). Although no unanimous difference could be detected

between samples cooled in an ice bath or in the fridge on the mean enclosed water percentage

(or yield) (p=0.24-0.4), all subsequent samples were cooled down in an ice bath after

preparation.

0

2

4

6

8

10

12

14

16

18

20

ice bath no ice bath

Est

imat

ed e

nclo

sed

wat

er v

olum

e (%

)

0

10

20

30

40

50

60

70

80

Yie

ld (

%)

Figure 3.27: Effect of cooling regime on the enclosed water volume by T2-relaxation measurements or yield of the double emulsion. Error bars denote the standard deviation of 3 subsequent measurements of the yield of one sample. Per cooling regime, two samples were analyzed. To the black colored bars, 100µL of 10mM MnCl2 was added, whereas to the white colored bars 75µL of 10mM MnCl2 was added to 8mL vortexed sample, prior to analysis.


124

3.5.2 Method application

3.5.2.1 Variation of the composition of the fat phase

In prospect of the aim to create whippable double emulsions, the ratio of soft PMF and Hozol

(and hence the solid fat content) was varied and the effect on the enclosed water volume (or

yield) was investigated.

As mentioned in section 1.2.2, partial coalescence of oil globules in whipping cream is

maximized at 10-50% solid fat content. At 5°C, the solid fat content of bulk soft PMF is 80%

(Verhaeghe, 2004). The type of surfactants plays an additional role in terms of influence on

the solid fat content. Although the solid fat content is not an additive property, the addition of

Hozol with 0% solid fat at 5°C, results in mixtures whose solid fat content in bulk fat may be

roughly approximated by:

% solid fat = 0% solid fat (Hozol)(1-x) + 80% solid fat (soft PMF)(x)

where (x) and (1-x) refer to the percentage of soft PMF and Hozol in bulk fat.

However, the maximum solid fat content of bulk fat at a certain temperature is in general

higher and reached at a faster rate than emulsified fat (Campbell et al., 2002). That’s why it

was chosen to analyse mixes of soft PMF and Hozol in various ratios in double emulsions.

Table 3.18 reports the analyzed mixtures of oils in double emulsions.

Table 3.18: Mixtures of soft PMF and Hozol and the associated calculated solid fat content in bulk fat Code Soft PMF (wt%) Hozol (wt%) SFC (%) in bulk fat 100/0 100.0 0.0 80

87.5/12.5 87.5 12.5 70 75/25 75.0 25.0 60

62.5/37.5 62.5 37.5 50 50/50 50.0 50.0 40

37.5/62.5 37.5 62.5 30 25/75 25.0 75.0 20

12.5/87.5 12.5 87.5 10


125

3.5.2.1.1 Effect of the fat composition on the enclosed water volume and yield of double

emulsions made by Method B

Figure 3.28 represents the enclosed water volume and yield using a mixture of soft PMF and

Hozol in the fat phase. As will be seen in section 3.5.2.1.3, the accuracy of the values of the

enclosed water and yield that are obtained with method B, should be interpreted with caution.

However they allow relative comparison of values in this experiment.

Based on the samples, a difference was detected between the different mixtures of fat on the

mean enclosed water volume (p=0.0047), but no trend can be observed from Figure 3.28.

0,0

5,0

10,0

15,0

20,0

25,0

30,0

12.5/87.5 25/75 37.5/62.5 50/50 62.5/37.5 75/25 87.5/12.5 100/0

Mixture soft PMF/Hozol

Est

imat

ed e

nclo

sed

wat

er

volu

me

(%)

0

20

40

60

80

100

120

Yie

ld (%

)

Figure 3.28: Effect of the ratio of soft PMF and Hozol on the enclosed water volume and yield by T2-relaxation measurements. Error bars around the average yield denote the standard deviation of 3 measurements of one sample. All samples required 75µL of 10mM MnCl 2 per 8mL vortexed double emulsion, added prior to analysis, except the 100/0 fat- sample, to which 100µL of 10mM MnCl2 per 8mL vortexed double emulsion was added. 3.5.2.1.2 Effect of variation of the fat phase on the T2-distribution of double emulsion made

by Method B

Double emulsions with a low ratio of soft PMF/Hozol are characterized by a low fat phase

crystallization. Figure 3.29 gives an overview of the obtained values for the area under the

curve that correspond to fast (fat), medium (external water) and slow (internal water)

relaxation. Based on these samples, the ratio of soft PMF/Hozol doesn’t affect the mean area

under the curve that is associated with fast relaxation (fat phase).


126

1

10

100

1000

10000

100000

12.5/87.5 25/75 37.5/62.5 50/50 62.5/37.5 75/25 87.5/12.5 100/0

Ratio soft PMF/Hozol in fat phase

Are

a u

nder

the

peak

Oil peak

Externalwater peak

Internalwater peak

Total areaunder thecurve

Figure 3.29: Area under the peak as a function of ratio of soft PMF/Hozol in the fat phase of a double emulsion. Error bars denote the standard deviation of three repetitions. One sample per ratio was made, except for ratio 87.5/12.5, two samples were made. To all samples 75µL of 10mM MnCl2 was added prior to analysis, except one sample with ratio 87.5/12.5, which contained 100µL of 10mM MnCl2.

3.5.2.1.3 Effect of the variation of the fat phase on the T2-distribution of double emulsion

made by Method C

An overview of the area under the different peaks for different ratios of soft PMF/Hozol in

double emulsions is given in Figure 3.30.

1

10

100

1000

10000

100000

12.5/87.5 25/75 37.5/62.5 50/50 62.5/37.5 75/25 87.5/12.5 100/0

Ratio soft PMF/Hozol

Are

a un

der

the

peak

Fat peak

Externalwater peak

Internalwater peak

Total areaunder thepeak

Figure 3.30: Area under the peak as a function of ratio of soft PMF/Hozol in the fat phase of a double emulsion. Error bars denote the standard deviation of three repetitions of one sample. To all samples 28µL of 10mM MnCl2 was added. Whereas in 3.3.2.5 (Method B) this could not be reported, Figure 3.30 shows that if double

emulsions are made by Method C, emulsions with a low ratio of soft PMF/Hozol are


127

characterized by a lower area under the curve for the signal that is associated with fat, than at

higher ratios of soft PMF/Hozol. A trendline drawn through the points that connect the area

under the curve that is related to fat as a function of the ratio soft PMF/Hozol, gives the

equation y=92.9x+30.1 (R2=0.82). This could be explained by the fact that since the

relaxation time is higher for protons in a more liquid fat, a part of the fat signal merges with

the signal of the medium relaxation mode and hence, the area under the curve for fat at lower

ratios of soft PMF/Hozol decreases. However, this would coincide with an increase of the

area under the curve associated at medium relaxation mode, which cannot be observed.

Whereas in Figures 3.24 and 3.25 an increase of relaxation time of the smallest mode in the

T2-distribution of P1.25/2.5/1 and bulk soft PMF, respectively, was observed upon

temperature increase and hence, decrease of solid fat content and Adam-Berret et al. (2011)

reported that pure fat mixes with a low solid fat content at a constant temperature have a high

T2-relaxation time and vice versa, Figure 3.31 shows for the analyzed emulsions that the

smallest mode of the relaxation time distribution (fat phase) is not different among samples

with ratios of soft PMF/Hozol from 37.5/62.5 to 100/0 and hence, different solid fat contents

in the double emulsion. This might be explained by the presence of a fraction of soft PMF in

all analyzed emulsions, by which the relaxation time related to fat remains approximately

constant for the analyzed ratios of soft PMF/Hozol.

0.1

1

10

100

12.5/87.5 25/75 37.5/62.5 50/50 62.5/37.5 75/25 87.5/12.5 100/0

Ratio of soft PMF/Hozol

Rel

axat

ion

time

(ms)

Figure 3.31: Smallest mode of relaxation time distribution as a function of the ratio of soft PMF/Hozol in the fat phase of a double emulsion. Error bars denote the standard deviation of three repetitions for one sample.


128


emulsions made by Method C

Method C (see 2.5.2.3) comprises the filling of an NMR-tube for 15mm height. All tubes are

elevated for 27mm during analysis in the spectrometer. Right after production, 28µL of

10mM MnCl2 is added and vortexed. The same experiment was carried out as described in

section 3.5.2.1.

Figure 3.32 represents the enclosed water volume and yield as a function of the ratio of soft

PMF and Hozol in the fat phase of a double emulsion, for which no linear trend can be

reported.

In comparison to the same experiment, performed with Method B (3.5.2.1.1), Method C

resulted in a significantly lower mean enclosed water volume (p=0). This is explained by the

way of filling of the NMR-tubes. Tubes in Method B are filled until the mark (40mm),

whereas in Method C, samples of 15mm height are analyzed, while elevated. As the detection

zone for tubes in Method B covers mainly the upper part of the sample and, if not completely

homogeneously vortexed, this contains more less dense or oily particles, which are filled with

internal water, less external water is recorded. As a consequence, based on Equation 2.14, a

higher enclosed water volume in Method B than in Method C is achieved. In terms of the

accuracy of the enclosed volume and yield, Method C is more reliable, due to the complete

coverage of the sample in the detection zone of the Maran Ultra 23 spectrometer.

A double emulsion with a soft PMF/Hozol ratio of 67.5/32.5 is characterized by a mean

enclosed water volume of 15.6 ± 0.1% and a mean yield of 62.4 ± 0.4%. This means that this

w1/o/w2-emulsion (20/20/60) actually contains 32.5g w1/o emulsion per 100g double

emulsion (12.5/20/67.5). A commercial whipping cream contains approximately 30 to 40g fat

per 100g cream. Hence, based on the enclosed volume, the volume fraction of the 20%

emulsion might be sufficient to enable efficient whipping.


129

0,0

2,0

4,0

6,0

8,0

10,0

12,0

14,0

16,0

18,0

12.5/87.5 25/75 37.5/62.5 50/50 62.5/37.5 75/25 87.5/12.5 100/0

Ratio of soft PMF/Hozol

Est

imat

ed e

nclo

sed

wat

er v

olum

e (%

)

0

10

20

30

40

50

60

70

Yie

ld (

%)

Figure 3.32: Effect of the ratio of soft PMF and Hozol on the enclosed water volume (or yield) by T2-relaxation measurements. Error bars around the average yield denote the standard deviation of 3 measurements of one sample.


emulsions made by Method D

Method D (see 2.5.2.4) is similar to Method C, but comprises the production of the w/o-

emulsion with an Ultraturrax device ánd Microfluidizer.

Two different fat mixes with a soft PMF/Hozol ratio of 62.5/37.5 and 100/0 were investigated

by T2-analysis. In Table 3.19 the average and standard deviation of three repetitions of one

and three samples with a soft PMF/Hozol ratio of 62.5/37.5 and 100/0 are represented,

respectively. Comparison with the values from section 3.5.2.1.4 results in the conclusion that

based on these samples, the mean enclosed water volume is lower in double emulsions made

with Method D than with Method C (p=0.05). Probably, during the second emulsification

step, more water is expelled from fat globules if the internal water droplets are smaller.

Table 3.19: Average enclosed water volume and standard deviation of three repetitions per sample. Samples were filled for 15mm height, 28µL MnCl2 was added after production and measured in a 27mm elevated position.

Soft PMF/Hozol Enclosed water volume (%) 100/0 12.8 ± 0.4

12.7 ± 0.2 11.8 ± 0.1

62.5/37.5 10.5 ± 0.3


130

3.5.2.2 Effect of the concentration of hydrophilic emulsifier in the external water phase on the

enclosed water volume

As discussed in section 1.1.4.1, Garti and Aserin (1996) reported high concentrations of

external hydrophilic emulsifier reduce the encapsulation efficiency. In this experiment the

effect of the increase of sodium caseinate from 1% (w/v) to 1.25% (w/v) in the external water

phase on the enclosed water volume was investigated. Regarding emulsion P1.25/2.5/1 that

was prepared by Method B, the average and standard deviation of three repetitions of the

same sample, amounted to 18.6% and 0.1%, respectively, which was significantly higher than

17.1% and 0.3%, respectively, for sample P1.25/2.5/1.25 (p=0.038). In conclusion, already by

increasing the external hydrophilic surfactant sodium caseinate with 0.25% (w/v) the

encapsulation efficiency of a double emulsion is negatively influenced.

3.6 Fat globule analysis by a Malvern Mastersizer S Three repetitions of a particle size analysis of a double emulsion with composition

H1.25/2.5/1 and made in accordance to Method B (section 2.5.2.2), were performed on the

same day of production with a Malvern Mastersizer S. A few drops of double emulsion were

brought into the MS-17 wet sample dispersion unit filled with deionized water. The average

D43 and the standard deviation of the average of three repetitions was 16.94µm and 0.04µm

(Figure 3.33).

0

2

4

6

8

10

12

14

0.1 1 10 100 1000

Diameter (µm)

Vol

ume-

wei

ghte

d di

strib

utio

n (%

)

Figure 3.33: Volume-weighted distribution as a function of diameter of oil globules of H1.25/2.5/1 (P/A 11/11-03).


131

3.7 Visualization of double emulsions by light microscopy

An image of a double emulsion with composition H1.25/2.5/1 made by Method B (see section

2.5.2.2) was taken (Figure 3.34). A lot of very small water droplets can be observed in the oil

globules, which coincides with type C of water droplet entrapment as discussed in section

1.6.1.

Figure 3.34: Light microscopic image of H1.25/2.5/1 three days after production (P/A 11-14/03), upon tenfold dilution with external water phase. Objective 50x.

3.8 Research on the thickness of the separated cream layer of double emulsions

The thickness of the separated cream layer can be determined manually with a ruler and can

be illustrated by one dimensional pulsed field gradient NMR profilometry.

3.8.1 Determination of the thickness of the separated creamy layer with a ruler

Thickness determination by the manual method points out that the oil containing (upper) part

or cream layer of the separated double emulsion by Method B, C and D makes up

approximately 50 to 60% of the total volume. No differences could be observed among


132

different fat phases. If these oil globules are monodisperse spherical particles that contact

each other without deformation, the porosity would be approximately 40%. Since for an

emulsion, a distribution of globule sizes exist, the porosity or extraglobular water in the cream

layer might be rather between 5 to 20%.

3.8.2 Profilometric analysis of double emulsions

One dimensional pulsed field gradient NMR profilometry allows to analyze the extent of

creaming of a double emulsion and the calculation of the water content of the cream layer of a

double emulsion. Moreover, the creaming rate can be determined. Concerning the latter, the

analyzed samples already creamed after 24h. Hence, focus was laid on investigation of the

thickness and water content of the creamed layer of the double emulsion.

Regarding the extent of creaming, a setup is applied which embodies a gradual rise of the

NMR-tube, whereby after each ascent the signal amplitude is recorded of each slice of the

sample as a function of frequency. The NMR-tube is filled for 47mm with a double emulsion

(P1.25/2.5/1) and was prepared by Method C. Figure 3.35 demonstrates its profilometric

analysis. A complete data-output is given in Appendix G. Also a sample with soft PMF and

2.5% PGPR is included in the figure, whose maximal signal intensity is 8 times lower than the

maximal intensity of the w/o/w-sample. Protons in fat are characterized by a small T2-

relaxation time and hence, more pronounced relaxation occurs than for water protons. A small

T2-relaxation time is related to a small profilometry signal intensity. Regarding the w/o/w-

sample, one can observe two maximal signal amplitudes. The higher maximal signal intensity

at 80000 units is measured when the detection zone of the spectrometer converges with the

separated serum phase at the bottom of the sample, which occurs after an elevation of the tube

for 2 or 3cm. The lower maximal signal intensity at 55000 units coincides with the detection

of the creamy layer of the separated sample. At an elevation of 1 and 2cm, both maxima are

recorded, indicating that the separation border between the cream layer and water phase is

located within the detection window, which is illustrated for an elevation of 1cm in Figure

3.36. In there, a drawing of a NMR-tube is placed next to the profile. It has to be mentioned

that the frequency axis is in fact a rescaled height axis, since the frequency is proportional to

the height of a sample, which is based on the equation:

ω = ωo+ γ∆xG


133

where ω is the Larmor frequency of precession of hydrogen atoms in a magnetic field, ω0 is

the Larmor frequency in a magnetic field B0, γ is the gyromagnetic ratio of hydrogen atoms,

∆x is the position along the axis on which G, the field gradient, is applied (Zhu et al., 2008).

From γ and G, the relationship between ω and ∆x is known. In Figure 3.36, the lower

frequencies are related to the lower part in the detection window, at which the water phase is

situated. The hydrogens in the creamy layer are detected at higher frequencies. The signal

amplitude is proportional to the amount of mobile hydrogens (Zhu et al., 2008), but also

strongly affected by T2. As more mobile hydrogens are present in the separated serum phase

than in the upper creamy part, this explains the higher signal amplitude for serum versus the

creamy part of the sample.

Since both the cream and water phase are symmetrically recorded at a tube elevation of 1 and

2cm, the creamy layer must be located in the middle of the detection window at about 1.5cm

elevation. As the detection zone starts from 2.2 to 4.7cm, the middle of this is found at

3.45cm, or, considering 1.5cm elevation, the middle of the detection zone is positioned about

2.0cm above the bottom of the tube. The ratio of the thickness of the cream layer (47-20mm)

over the total filling height (47mm) is equal to the approximate thickness of the creamy layer,

which amounts to 58.5%. This is in accordance to the measured thickness of the creamy layer

with a ruler in section 3.8.1.

From this, the water content can be evaluated in the cream layer, which will be partly

encapsulated within the oil droplets. Hundred milliliter double emulsion contains 58.5mL

cream and 41.5mL serum phase or also 22mL (or 20g) fat and 80mL (or 80g) total water. The

latter reasoning gives a volume fraction of 21.6mL fat and 78.4mL total water per 100mL

double emulsion. The water content in the cream layer is calculated by subtraction of 41.5mL

serum phase from 78.4mL water, which amounts to 36.9mL water per 58.5mL cream (63%).

This enables the calculation of intraglobular and extraglobular water in the cream layer. A

double emulsion P1.25/2.5/1 contains on average 10.5mL enclosed water on 100mL water

(section 3.5.2.1.5). This results in 8.2mL enclosed water on 78.4mL water or 100mL double

emulsion. Based on the thickness of 58.5% cream layer, 36.9mL (78.4mL-(100-58.5)mL)

water was present in the cream layer. Subtraction of 36.9mL water in the cream layer in

100mL double emulsion and 8.2mL enclosed water in 100mL double emulsion amounts to

28.7mL extraglobular water in the cream layer in 100mL double emulsion.

Alternatively, the water content in the creamy layer can be assessed after performing a

profilometric analysis on a bulk water phase. Two profiles were read in Figure 3.37 for a tube

filled with deionized water and a tube with external water phase w2 (1% (w/v) sodium


134

caseinate). The area under the profile of deionized and external water phase amounts to 2643

and 2703 units, respectively. The separated serum layer of the double emulsion is not

deionized water, nor is it the external water phase, since the concentration of sodium caseinate

is lower in the separated sample due to preferential localization of this compound at the water-

oil interface. As all other compounds in the external water phase are similar to the separated

serum phase, the true area under the profile of the water fraction of the double emulsion must

approximate its value. The calculation of the water content of the cream layer is performed

with the signal intensity of the external water phase. At 0cm elevation, at which no signals of

separated serum phase are registered, the average signal intensity of 27 data points in the

middle of the detection zone is 54173 units. The water content in the cream layer is calculated

by dividing the latter by the average signal intensity of external water of 28 data points in the

middle of the detection zone, which amounts to 85954 units. This gives a water content of the

creamy layer of 63%, which is exactly the same value as calculated from the thickness of the

creamy layer.

0

10000

20000

30000

40000

50000

60000

70000

80000

90000

-0.04 -0.02 0 0.02

Frequency (MHz)

Sig

nal i

nten

sity

Soft PMF andPGPR

ocm elevationw /o/w

1cm elevationw /o/w

2cm elevationw /o/w

3cm elevationw /o/w

4cm elevationw /o/w

5cm elevationw /o/w

Figure 3.35: Pfg-NMR 1D profilometry at different elevations of a double emulsion (P1.25/2.5/1) and a sample of soft PMF with 2.5% PGPR (w/v), determined at 5°C (P/A 2-3/03/11).


135

1cm elevation w/o/w

-0,05

-0,04

-0,03

-0,02

-0,01

0

0,01

0,02

0,03

0,04

0,05

0 10000 20000 30000 40000 50000 60000 70000 80000 90000

Signal Intensity

Frequency (MHz)

Figure 3.36: Frequency as a function of signal intensity of a 1cm elevated w/o/w sample (P1.25/2.5/1) filled over 47mm in a Maran NMR glass tube. The red bar denotes the detection window from 22 to 47mm. Black bar denotes the filling degree.

01000020000

3000040000500006000070000

8000090000

100000

-0,06 -0,04 -0,02 0 0,02 0,04 0,06

Frequency (Mhz)

Sig

nal I

nten

sity

External w ater phase (w 2) Deionized w ater

Figure 3.37: Pfg-NMR 1D profilometry of external water phase (W2) and deionized water. NMR-tubes were filled for 47mm height.


136

3.9 Whipping of a commercial dairy cream

3.9.1 Whipping time of a whipped commercial dairy cream

The average whipping time and standard deviation of three repetitions of 200mL cream was

281s and 1.7s.

3.9.2 Overrun of a whipped commercial dairy cream

The average and standard deviation of the net mass of three unwhipped cream samples and

two whipped cream samples in recipients of 200mL was (202.89 ± 0.45)g and (92.09 ±

3.29)g, respectively. Hence, the average overrun is 54.6%.

3.9.3 Physical destabilization (drainage) of a whipped commercial dairy cream

After storage at 16-18°C of 50g of whipped cream on a sieve, no leaked serum could be

detected.

3.10 Whipping of w/o/w-emulsions

3.10.1 First attempt

A double emulsion was prepared by Method D as described in section 2.8.2.1. The applied

ratio of soft PMF/Hozol (62.5/37.5) was chosen after consideration of several aspects that

affect the solid fat content, besides the fact that this is a empirical experiment.

Firstly, the temperature of the refrigerated room in which the emulsion was stored amounts to

5°C, which results in a solid fat content of bulk soft PMF of 80% (Verhaeghe, 2004) or a solid

fat content of the bulk mix of soft PMF/Hozol (62.5/37.5) of 50%.

Secondly, after emulsification the solid fat content drops. In Fredrick et al. (2011) in which

homogenized recombined emulsified milk fat (35wt%) with a fat globule diameter of about

3µm was compared to bulk milk fat, the solid fat content at 5°C after one day differed about


137

5%. In this thesis the fat globules are larger and filled with water. Section 3.5.2.1.5

demonstrated that the internal water of this double emulsion amounted to 10.5g/100g, which

comes down to 8.4g on 80g of total water in a w/o/w-emulsion (20/20/60). This means that

100g of a stable double emulsion actually contains 28.4g w1/o-droplets, which is built up of

2/3 (20g) fat and 1/3 (8.4g) enclosed water. The volume of a fat globule with diameter 17µm

(see section 3.6) is 2572µm3, from which two third or 1715 µm3 is occupied by fat. A fat

globule with a diameter of 3µm gives a volume of 14µm3. Hence, there is a volume difference

of a factor 122. This probably renders the difference in solid fat content between bulk fat and

emulsified fat in this experiment lower than the observed difference in Fredrick et al. (2011).

A third aspect in consideration is to mimic dairy cream that is well whippable at a solid fat

content of 10-50% (see section 2.1.1).

Creaming of a recombined cream depends on the fat droplet size (Stokes’s law), the viscosity

of the external water phase and the interfacial film properties. Changing the fat droplet size

by homogenization in a Microfluidizer appeared to be detrimental for the enclosed water

volume. Alteration of the viscosity and interfacial film properties requires the addition of

compounds. Bearing in mind the popularity of clean label foods on the one hand and the

increase of complexity by introduction of additional compounds on the other hand, it was

decided to reduce the gravitational destabilization by rotation of the sample at 20rpm, while

being kept overnight at 5°C. However, this made the emulsion churn. This churned sample

was whipped in order to ameliorate separation of the coalesced cream phase from the serum.

After 1 min and 4 min and 40sec of whipping, the ratio of cream to serum amounted to

34.4/65.6 and 33.5/66.5, respectively, which shows that an increase of the whipping time

reduces the amount of water and/or increases the amount of fat in the fat phase. Allowing for

a fat/water ratio of 20/80 for a completely separated double emulsion, the ratios of this sample

reveal that the coalesced cream phase must still contain water droplets and hence is a w/o-

emulsion.

3.10.2 Second attempt

The second attempt differs in terms of the manner of prevention of creaming. Each 30

minutes, the sample was gently twisted. Headspace was provided to enable mixing while

twisting. After production until whipping, the sample was placed in a refrigerator at 5°C for


138

6.5 hours. Nevertheless this sample exhibited a small creamy layer, which made the emulsion

unwhippable.

3.10.3 Third attempt

In the third endeavour, creaming is prevented by addition of 0.2wt% xanthan gum to the

external water phase (w2) and the double emulsion is prepared analogously as in the first

attempt. After about 3 minutes of whipping, churning was observed.

3.10.4 Fourth attempt

Analogously as in section 3.10.3, the external water phase contained 0.2wt% xanthan gum.

Sodium caseinate in the external water phase was replaced by cream residue powder. Already

after 15s of whipping, the emulsion churned. The difference in onset of churning or

perikinetic instability upon whipping between emulsions with sodium caseinate or cream

residue powder in the external phase can be explained by the presence of phospholipids in the

latter external phase that replaces proteins from the interfacial film upon shear action and

hence, perikinetically destabilizes the emulsion faster than in the absence of such small

molecular weight surfactants.

General conclusions

139

General conclusions

In order to create w/o/w-emulsions, the preparation of a w/o-emulsion is required. The size of

the water droplets in the w/o-emulsions was analysed by pfg-NMR. Comparing three data

processing methods (Droplet Size application, Excel and Matlab) it was observed that the

latter two methods resulted in a smaller water droplet size than the former method. Excel

frequently failed to give an output.

From the experiments on w/o-emulsions, it became clear that the type of fat phase had a

significant effect on the mean water droplet size, whereby emulsions with soft PMF or a mix

of soft PMF and Hozol were characterized by a smaller particle size than emulsions based on

Hozol only. Addition of the hydrophilic emulsifier sodium caseinate (0.5%, w/v) to

emulsions based on soft PMF with 1% PGPR had a significant beneficial effect on the

reduction of the mean droplet size.

W/o-emulsions with a mass fraction of water up to 50% could be obtained without alteration

of the type of emulsion, whereby the water droplet size was not significantly different for

water mass fractions of 30, 40 or 50%.

Since there was a small but significant effect on the mean droplet size for emulsions made at a

driving air pressure of 4bar or 6bar in the Microfluidizer, it is advised to prepare w/o-

emulsions at the lower pressure setting.

Fluorimetric experiments indicated that it should be possible to analyse water droplets of w/o-

emulsions with 50% mass fraction of water, in which 0.001% (w/v) eosinY is included,

qualitatively by light microscopy. This requires the use of a filter block that passes the

maximum excitation and emission wavelength range of 517 to 527nm and 542 to 547nm,

respectively.

Considering the optimization of the preparation of w/o/w-emulsions, the use of a

Microfluidizer M110S at 1bar for 1.5min for mixing the w/o-emulsion with the external water

phase destroyed the double emulsion and hence no enclosed water could be detected. The

percentage of enclosed water was be determined by T2-analysis, which was shown to be an

authorized and valuable tool for characterization of w/o/w-emulsions, whereby a

General conclusions

140

concentration of 94 to 125µM MnCl2 in the double emulsion (i.e. 156 to 208µM MnCl2 in the

external water phase) was needed to ensure complete resolution of the internal and external

water phase.

Increasing the duration of mixing of the w1/o-emulsion and the external phase w2 significantly

lowered the enclosed water volume or yield. Moreover, increasing the concentration of

sodium caseinate in the external water phase by 0.25% (w/v) significantly reduced the

encapsulation efficiency of the double emulsion.

The thickness of the separated cream layer in w/o/w-emulsions was determined either

manually with a ruler or spectrometrically by profilometry. The latter method offers the

possibility to calculate the water content in the cream layer. On the other hand, the addition of

0.2wt% xanthan gum to the external water phase makes the w/o/w-emulsion stable against

cream separation.

In comparison to commercial dairy cream, the desired textural change during whipping at 5°C

was not observed in w/o/w-emulsions based on a ratio of soft PMF/Hozol of 62.5/37.5,

whereby churning occured much quicker. No improvement regarding the whippability was

observed by replacement of sodium caseinate by cream residue powder in the external water

phase. In a next step, the solid fat content of w/o/w-emulsions with different fat composition

can be investigated.

In conclusion, w/o-emulsions with up to 50wt% of water could be obtained. This mixture

could be incorporated in an aqueous phase with retention of about 42 to 62%, depending on

the preparation method, of water inside the emulsion droplets if the homogenization intensity

during the second step was sufficiently small. The pfg-NMR technique enabled water droplet

size estimation in w/o-emulsions, whereas laser diffraction enabled oil droplet size analysis in

w/o/w-emulsions. T2-relaxation analysis upon MnCl2 addition permitted resolution of internal

and external water in a double emulsion. Whereas a low fat cream substitute could be

obtained, still additional research is needed to obtain good whipping properties.

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141

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Appendix A: Part of a data sheet in Excel that represents the experimental echo attenuation ratios Ep(δ) δ) δ) δ) of the emulsion H0.75/1.50 (sample1) and the matrix of the calculated echo attenuation ratios as a function of the radius and δ (E(R,δ)). which is used in Equation 2.8.

r (µm) = 0.25 0.75 1.25 1.75 2.25 2.75 3.25 3.75 4.25 4.75 Measured

data δi (s) I E (R,δ) (-) E (R,δ) (-) E (R,δ) (-) E (R,δ) (-) E (R,δ) (-) E (R,δ) (-) E (R,δ) (-) E (R,δ) (-) E (R,δ) (-) E (R,δ) (-) Ep (δ) (-)

0 0 1.000000000 1.000000000 1.000000000 1.000000000 1.000000000 1.000000000 1.000000000 1.000000000 1.000000000 1.000000000 1.000000000 0.00050 1 0.999920118 0.995029754 0.976540817 0.945182665 0.903409649 0.853163221 0.796254846 0.734492386 0.669667789 0.603504387 1.000000000 0.00075 2 0.999879004 0.991751185 0.956117767 0.891857398 0.807447278 0.710896991 0.609193864 0.508326465 0.413106987 0.327015061 0.946901647 0.00100 3 0.999837891 0.988457858 0.933975575 0.831338885 0.699952594 0.559842328 0.426335290 0.309471802 0.214258862 0.141531783 0.908592357 0.00125 4 0.999796781 0.985171815 0.911305940 0.768339228 0.592004808 0.419866002 0.275331087 0.167344061 0.094395864 0.049455640 0.855941678 0.00150 5 0.999755672 0.981896174 0.888682525 0.705882748 0.490863177 0.301853464 0.165386863 0.081090964 0.035668912 0.014095704 0.800259266 0.00175 6 0.999714531 0.978628741 0.866358882 0.645749324 0.400474245 0.209150413 0.093018932 0.035478947 0.011653751 0.003304763 0.749705747 0.00200 7 0.999673459 0.975377369 0.844512188 0.589096807 0.322652743 0.140486672 0.049372523 0.014151844 0.003329736 0.000645634 0.697604728 0.00225 8 0.999632355 0.972134207 0.823142295 0.536275279 0.257223367 0.091785850 0.024838496 0.005171743 0.000836289 0.000105639 0.646689514 0.00250 9 0.999591253 0.968901829 0.802285398 0.487490123 0.203352112 0.058561830 0.011911540 0.001744079 0.000186201 0.000014615 0.610694831 0.00275 10 0.999550152 0.965680199 0.781943530 0.442698176 0.159682026 0.036604751 0.005470874 0.000546021 0.000037014 0.000001723 0.569354188 0.00300 11 0.999509053 0.962469280 0.762110915 0.401739339 0.124710015 0.022477263 0.002416765 0.000159580 0.000006613 0.000000175 0.526042981 0.00325 12 0.999467956 0.959269038 0.742778164 0.364390712 0.096971259 0.013591597 0.001030772 0.000043763 0.000001069 0.000000015 0.502250107 0.00350 13 0.999426860 0.956079437 0.723934306 0.330400471 0.075136439 0.008109927 0.000425931 0.000011315 0.000000157 0.000000001 0.466485492 0.00400 14 0.999344675 0.949732016 0.687666834 0.271459273 0.044750371 0.002793661 0.000066944 0.000000645 0.000000003 0.000000000 0.401911725 0.00450 15 0.999262496 0.943426735 0.653215517 0.222924040 0.026454108 0.000929525 0.000009586 0.000000031 0.000000000 0.000000000 0.349155834 0.00500 16 0.999180323 0.937163315 0.620489993 0.183022867 0.015562489 0.000301343 0.000001273 0.000000001 0.000000000 0.000000000 0.318035649 0.00600 17 0.999015999 0.924760949 0.559875275 0.123331963 0.005340957 0.000030020 0.000000019 0.000000000 0.000000000 0.000000000 0.256617697 0.00800 18 0.998687431 0.900446440 0.455831443 0.055987662 0.000620630 0.000000266 0.000000000 0.000000000 0.000000000 0.000000000 0.136287291

Appendices

151

Appendix B: scripts in Matlab SIMULATION_DATA.M % simulation of pfg-NMR decay graphs for W/O als a function of droplet size (lognormal distribution) clc; clear all ; Ds=1.31e-9; %free diffusion coefficient of water in aqueous phase ldelta = xlsread( 'emulsie1-Maran-data17.xls' ,1, 'c2' ) %diffusion time (big delta) [s] gamma=267522128; %gyromagnetic constant in 1/(T.s) g = xlsread( 'emulsie1-Maran-data17.xls' , 1, 'e2' ) %magnetic field gradient [T/m] %sdelta=(0.0:0.0001:0.01); %pulse gradient widths [s] %ndelta=1+(0.01-0.0)/0.0001 %n umber of small delta values sdelta = xlsread( 'emulsie1-Maran-data17.xls' , 1, 'b2:b18' ); ndelta=length(sdelta) I=xlsread( 'emulsie1-Maran-data17.xls' , 1, 'f2:f18' ); %primary data of Maran Io=I(1,1); %first experimental point (good estimate for Io) pFW=0; %percentage of free water (%) nra=25; %25 contributions in Bessel-series besselroots=[1.84;5.33;8.54;11.71;14.86;18.02;21.16 ;24.31;27.46;30.60;33.75;36.89;40.03;43.18;46.32;49.46;52.61;55.75;58.89;62 .03;65.17;68.32;71.46;74.60;77.74] %roots of Bessel relations mean=0.7e-6; %mean particle radius [m] stdev=0.2e-6; %st.dev. of particle radius distribution [m] mu=log(mean^2/sqrt(stdev^2+mean^2)) %geometric mean radius (in fact: ln) of lognormal distribution sigma=sqrt(log(stdev^2/mean^2+1)) %geometric standard deviation (in fact: ln) p=(0.01:0.01:0.99); %cumulative probability from ... in steps of .... up to .... r=logninv(p,mu,sigma); %radii corresponding to cumulative probability (according to lognormal) d=r.*2e6 %diameters in micron nr=length(r); %number of particle size classes % calculation of nra zero points alfa per size clas s; alfa = 0; for i = 1:nr; for j = 1:nra; alfa(i,j)=besselroots(j)/r(i);

Appendices

152

end ; end ; % calculation of NMR signal R per size class for ev ery small delta + overall NMR signal Raccum for the particle size dis tribution for every small delta; R=0; FW=0; %contribution of free water (FW) in signal at each small delta for j = 1:ndelta; %for every individual value of small delta Raccum(j)=0 for i = 1:nr; som = 0; for k = 1:nra; som=som+[(2*sdelta(j,1)/(Ds*alfa(i,k)^2 ))-((2+exp(-alfa(i,k)^2*Ds*(ldelta-sdelta(j,1)))-2*exp(-alfa(i, k)^2*Ds*ldelta)-2*exp(-alfa(i,k)^2*Ds*sdelta(j,1))+exp(-alfa(i,k)^2*Ds*(ldelta+sdelta(j,1))))/(alfa(i,k)^2* Ds)^2)]/(alfa(i,k)^2*(alfa(i,k)^2*r(i)^2-2)); end ; R(i,j) = Io*exp(-2*gamma^2*g^2*som); Raccum(j)=Raccum(j)+R(i,j)/nr % NMR decay point for the lognormal distribution end ; FW(j)=Io*exp(-gamma^2*g^2*Ds*sdelta(j,1)^2*(lde lta-sdelta(j,1)/3)); RaccumFW(j) = Raccum(j)*(100-pFW)/100 + FW(j)*p FW/100; %calculated NMR signal with free water contribution end ; figure (1) plot (d,p) % plot of particle diameter distribution (in micron) Rmin=R(1,:); % NMR decay curve for smallest particle radius of the lognormal distr ibution Rmax=R(nr,:); % NMR decay curve for largest particle radius of the lognormal distri bution figure (2) plot (sdelta,Rmin,sdelta,Rmax,sdelta,Raccum,sdelta,Raccu mFW,'db' ,sdelta,I, 'dm' )

Appendices

153

FITLIEN.M % Calculation of the SQD for measured <-> theoretic al NMR signal (XX) function [MLH] = fitlien(XX); %XX(1)=1 %XX(2)=0.2 %XX(3)=0 %XX(1) = mean radius (in micron) %XX(2) = standard deviation of radius(in micron) %XX(3) = percentage of free water %XX(4) = Io % import necessary parameters from the workspace %rawdata = evalin('base','rawdata'); %nr = evalin('base','nr'); %R = evalin('base','R'); %r = evalin('base','r'); gamma = evalin( 'base' , 'gamma' ); %gyromagnetic constant in 1/(T.s) g = evalin( 'base' , 'g' ); %magnetic field gradient [T/m] Ds = evalin( 'base' , 'Ds' ); %free diffusion coefficient of water in aqueous phase ldelta = evalin( 'base' , 'ldelta' ); %diffusion time (big delta) [s] sdelta = evalin( 'base' , 'sdelta' ); ndelta=length(sdelta); I=evalin( 'base' , 'I' ); %primary data of Maran I0=XX(3); %first experimental point (good estimate for Io) pFW=0; %pFW=XX(4); %if percentage of free water (%) has to be an adjustable parameter nra=25; %25 contributions in Bessel-series besselroots=[1.84;5.33;8.54;11.71;14.86;18.02;21.16 ;24.31;27.46;30.60;33.75;36.89;40.03;43.18;46.32;49.46;52.61;55.75;58.89;62 .03;65.17;68.32;71.46;74.60;77.74]; %roots of Bessel relations mean=XX(1)*1e-6; %mean particle radius [m] stdev=XX(2)*1e-6; %st.dev. of particle radius distribution [m] mu=log(mean^2/sqrt(stdev^2+mean^2)); %geometric mean radius (in fact: ln) of lognormal distribution sigma=sqrt(log(stdev^2/mean^2+1)); %geometric standard deviation (in fact: ln) p=(0.01:0.01:0.99); %cumulative probability from ... in steps of .... up to .... r=logninv(p,mu,sigma); %radii corresponding to cumulative probability (according to lognormal) %d=r.*2e6 %diameters in micron nr=length(r); %number of particle size classes

Appendices

154

% calculation of nra zero points alfa per size clas s; alfa = 0; for i = 1:nr; for j = 1:nra; alfa(i,j)=besselroots(j)/r(i); end ; end ; % calculation of theoretical NMR signal Raccum for the particle size distribution XX for every small delta; FW=0; %contribution of free water (FW) in signal at each small delta for j = 1:ndelta; %for every individual value of small delta Raccum(j)=0; for i = 1:nr; som = 0; for k = 1:nra; som=som+[(2*sdelta(j,1)/(Ds*alfa(i,k)^2 ))-((2+exp(-alfa(i,k)^2*Ds*(ldelta-sdelta(j,1)))-2*exp(-alfa(i, k)^2*Ds*ldelta)-2*exp(-alfa(i,k)^2*Ds*sdelta(j,1))+exp(-alfa(i,k)^2*Ds*(ldelta+sdelta(j,1))))/(alfa(i,k)^2* Ds)^2)]/(alfa(i,k)^2*(alfa(i,k)^2*r(i)^2-2)); end ; R(i,j) = I0*exp(-2*gamma^2*g^2*som); Raccum(j)=Raccum(j)+R(i,j)/nr; % NMR decay point for the lognormal distribution end ; FW(j)=I0*exp(-gamma^2*g^2*Ds*sdelta(j,1)^2*(lde lta-sdelta(j,1)/3)); RaccumFW(j) = Raccum(j)*(100-pFW)/100 + FW(j)*p FW/100; %calculated NMR signal with free water contribution end ; assignin( 'base' , 'RaccumFW' ,RaccumFW); % Calculation of the SQD of the difference between the theoretical and measured NMR signal SQD=0; for i=1:ndelta; SQD = SQD + (I(i)-RaccumFW(i))^2; end ; MLH = 0.5*8*log10(SQD/8) assignin( 'base' , 'MLH' ,MLH); assignin( 'base' , 'SQD' ,SQD); assignin( 'base' , 'sdelta' ,sdelta); assignin( 'base' , 'I' ,I); % plot van theoretisch (blauw) en waargenomen NMR s ignaal (roze) plot(sdelta,I, 'dm' ,sdelta,RaccumFW, 'b' )

Appendices

155

MINIM_LIEN.M % start value XX2, varies until max likelihood (fit ), saved as ZZZ XX2(1)=0.8; XX2(2)=0.1; XX2(3)=I(1,1)*1.05; %XX2(4)=2;%this parameter may be used to enable adj ustment of percentage of free water pFW=0; [ZZZ,fval,exitflag,output,grad,hessian] = fminunc(@ fitlien,XX2); %lognormal(ZZZ); display(ZZZ); display(hessian); SIMULATION.M % simulation of pfg-NMR decay graphs for W/O emulsi ons as a function of droplet size clc; clear all ; nr=10; %amount of particle size classes %factor=evalin('base','factor'); %kb=evalin('base','kb'); %rawdata=evalin('base','rawdata'); Ds=1.31e-9; %free diffusion coefficient of water in aqueous phase ldelta=0.21; %diffusion time (big delta) [s] gamma=267522128; %gyromagnetische constante in 1/(T.s) g=2; %magnetic field gradient [T/m] nra=25; %25 contributions in the Bessel-series sdelta=[0.0000 0.001 0.002 0.003 0.004 0.005 0.006 0.008]; %pulse gradient widths [s] ndelta=8; %number of small delta values %sdelta=(0.0:0.0001:0.01) %ndelta=1+(0.01-0.0)/0.0001 besselroots=[1.84;5.33;8.54;11.71;14.86;18.02;21.16 ;24.31;27.46;30.60;33.75;36.89;40.03;43.18;46.32;49.46;52.61;55.75;58.89;62 .03;65.17;68.32;71.46;74.60;77.74] %roots of the Bessel relations r=[0.5;1.5;2.5;3.5;4.5;5.5;6.5;7.5;8.5;9.5]; %particle radii in micron % setting of the class averages; %for i = 2:nr; % r(i) = r(i-1)+kb; %end; % calculation of nra zero points alfa for the class averages;

Appendices

156

alfa = 0; for i = 1:nr; r(i)=r(i)/1e6; %particle radii [m] for j = 1:nra; alfa(i,j)=besselroots(j)/r(i); end ; end ; % calculation of the NMR signal R for each class fo r each small delta from the rawdata(x,1); R=0; for j = 1:ndelta; for i = 1:nr; som = 0; for k = 1:nra; som=som+[(2*sdelta(1,j)/(Ds*alfa(i,k)^2 ))-((2+exp(-alfa(i,k)^2*Ds*(ldelta-sdelta(1,j)))-2*exp(-alfa(i, k)^2*Ds*ldelta)-2*exp(-alfa(i,k)^2*Ds*sdelta(1,j))+exp(-alfa(i,k)^2*Ds*(ldelta+sdelta(1,j))))/(alfa(i,k)^2* Ds)^2)]/(alfa(i,k)^2*(alfa(i,k)^2*r(i)^2-2)); end ; R(i,j) = exp(-2*gamma^2*g^2*som); end ; end ; R05=R(1,:); R15=R(2,:); R25=R(3,:); R35=R(4,:); figure (1) plot (sdelta,R05, 'r' ,sdelta,R15, 'b' ,sdelta,R25, 'g' ,sdelta,R35, 'y' ) SIMULATION_LOG.M % simulation of pfg-NMR decay graphs for W/O emulsi ons as a function of % the droplet size (lognormal distribution) clc; clear all ; %factor=evalin('base','factor'); %rawdata=evalin('base','rawdata'); Ds=1.31e-9; %free diffusion coefficient of water in aqueous phase ldelta=0.21; %diffusion time (big delta) [s] gamma=267522128; %gyromagnetische constante in 1/(T.s) g=2; %magnetic field gradient [T/m] nra=25; %25 contributions of the Bessel-series

Appendices

157

%sdelta=[0.0000 0.001 0.002 0.003 0.004 0.005 0.006 0.008]; %pulse gradient widths [s] %ndelta=8; %n umber of small delta values sdelta=(0.0:0.0001:0.01); ndelta=1+(0.01-0.0)/0.0001 besselroots=[1.84;5.33;8.54;11.71;14.86;18.02;21.16 ;24.31;27.46;30.60;33.75;36.89;40.03;43.18;46.32;49.46;52.61;55.75;58.89;62 .03;65.17;68.32;71.46;74.60;77.74] %roots of the Bessel relations mean=3e-6; %mean particle radius in m stdev=1e-6; %stdev of particle radius distribution in m mu=log(mean^2/sqrt(stdev^2+mean^2)) sigma=sqrt(log(stdev^2/mean^2+1)) p=(0.1:0.1:0.9); %cumulative probability from ... in steps of .... up to .... r=logninv(p,mu,sigma); nr=length(r); %amount of particle size-classes %r=[0.5;1.5;2.5;3.5;4.5;5.5;6.5;7.5;8.5;9.5]; %particle radii in micron % calculation of nra zero points alfa for each clas s averga; alfa = 0; for i = 1:nr; for j = 1:nra; alfa(i,j)=besselroots(j)/r(i); end ; end ; % calculation of the NMR signal R for each class fo r each small delta; R=0; for j = 1:ndelta; %8 different values for small delta for i = 1:nr; som = 0; for k = 1:nra; som=som+[(2*sdelta(1,j)/(Ds*alfa(i,k)^2 ))-((2+exp(-alfa(i,k)^2*Ds*(ldelta-sdelta(1,j)))-2*exp(-alfa(i, k)^2*Ds*ldelta)-2*exp(-alfa(i,k)^2*Ds*sdelta(1,j))+exp(-alfa(i,k)^2*Ds*(ldelta+sdelta(1,j))))/(alfa(i,k)^2* Ds)^2)]/(alfa(i,k)^2*(alfa(i,k)^2*r(i)^2-2)); end ; R(i,j) = exp(-2*gamma^2*g^2*som); end ; end ; figure (1) plot (r,p) Rmin=R(1,:); Rmax=R(nr,:); figure (2) plot (sdelta,Rmin,sdelta,Rmax)

Appendices

158

Appendix C Commands T2 relaxation measurements (RINMR, Maran Ultra 23 spectrometer ) Load CPMG Load Parameters (or REP) CPMG_paolo.RiPar Tau 200 Nech 8K DS 0 NS 2 .AUTOO1 .AUTORG DS 2 NS 8 GO Parameters ID Value P90 7.90 P180 15.80 P1 1.00 P2 1.00 P3 1.00 P4 1.00 P5 1.00 DEAD1 5.00 DEAD2 3.00 DW 1.00 RD 2000000.00 TAU 57500.00 D1 100.00 D2 7000.00 D3 100.00 D4 20000.00 D5 1000.00 D6 1000000.00 D7 1000000.00 D8 1000000.00 D9 1000000.00 D10 1000000.00 D11 1000000.00 D12 1000000.00 SI 1024 NECH 256 NS 4 SF 23.400000 O1 26911.60 SF2 0.000000 O2 0.00 FW 1.0 RG 4.45 PH1 0213 PH2 0213 PH3 2031 PH4 0213 PH5 1122 LB 0.00 PA 0.00 PB 0.00 DP 0.00 TRIM0 49 TRIM1 45 TRIM2 0

TRIM3 0 TRIM4 0 TRIM5 0 TRIM6 157 TRIM7 159 TRIM8 0 TRIM9 158 TRIMA 0 TRIMB 173 TRIMC 0 TRIMD 167 TRIME 0 TRIMF 170 TRIMG 0 TRIMH 0 TRIMI 0 TRIMJ 0 TRIMK 0 TRIML 0 TRIMM 0 TRIMN 0 TRIMO 0 TRIMP 0 TRIMQ 0 TRIMR 0 TRIMS 0 TRIMT 0 TRIMU 0 TRIMV 0 TRIMW 75 TRIMX 0 SW 1000000.0 DB 35 BES 1000000 BUT 100000 RFA0 100.0 RFA1 0.0 RFA2 0.0 RFA3 0.0 RFA4 0.0 RFA5 0.0 RF2A0 0.0 RF2A1 0.0 RF2A2 0.0 RF2A3 0.0 RF2A4 0.0

Appendices

159

RF2A5 0.0 WW 5.0 C1 0 C2 0 C3 0 C4 0 C5 0 TI ???? SMP 0 GX 0 GY 32767 GZ 0 G1 10000 G2 50 G3 0 G4 0 G5 0 G6 0 G7 0 G8 0 G9 0 IG1 1 IG2 1 IG3 1 IG4 1 IG5 1 IG6 1 IG7 1 IG8 1 IG9 1 MAC1 0.0 MAC2 0.0 SH1 SH2 SH3 SH4 SH5 DS 4 NA 1 SEQ DIFFTRIG GRS X GRP Y GRR Z %TEMPDIR Z %ROOTDIR Z %DATADIR C:\Daan\slib.00001.RiDat %EXPORTDIR C:\Bart Heyman\guarsaus3c_diepvries_zonderstaafje.00001 %LISTFILE C:\Program Files\Resonance\RINMR\list\DIFFLIST_ps %LOGFILE C:\Program Files\Resonance\RINMR\DATA\SLIB.00001.RiLog %HARDWARE 3 GSH1 GSH2 GSH3 GSH4 GSH5 SNR 100 %SEQFILE C:\PROGRAM FILES\RESONANCE\RINMR\SEQ\BIN\DIFFTRIG.Exe PP 0 NOBC 0 C6 1 C7 1 C8 1 C9 1 C10 1 C11 1 C12 1 FP1 1.00000 FP2 1.00000 FP3 1.00000 FP4 1.00000 FP5 1.00000 %LASTWEIGHT 0.000

%GOSTATE 6 %SCANSDONE 1 %CAL1 0.000000 %CAL2 0.000000 %CAL3 0.000000 %CAL4 0.000000 %CALIBDIR C:\Program Files\Resonance\RINMR\DATA\ %1 %2 %3 %4 %5 PREXA1 0.000 PREXK1 100000000.00 PREXA2 0.000 PREXK2 100000000.00 PREXA3 0.000 PREXK3 100000000.00 PREXA4 0.000 PREXK4 100000000.00 PREYA1 0.000 PREYK1 100000000.00 PREYA2 0.000 PREYK2 100000000.00 PREYA3 0.000 PREYK3 100000000.00 PREYA4 0.000 PREYK4 100000000.00 PREZA1 0.000 PREZK1 100000000.00 PREZA2 0.000 PREZK2 100000000.00 PREZA3 0.000 PREZK3 100000000.00 PREZA4 0.000 PREZK4 100000000.00 XB0A 0.000 XB0K 100000000.00 YB0A 0.000 YB0K 100000000.00 ZB0A 0.000 ZB0K 100000000.00 PREBA4 0.000 PREBK4 0.00 PPTH 4.0 PPRF 50 PPAF 1 PPPF 0 DEC90 5000000.00 CPD WALTZ16 GSLICEX 1.000 GSLICEY 0.000 GSLICEZ 0.000 GPHASEX 0.000 GPHASEY 1.000 GPHASEZ 0.000 GREADX 0.000 GREADY 0.000 GREADZ 1.000 GREAD 0 GPHASE 32767 GSLICE 0 %SNR 0 GD 0.00 %ERROR 1002 %CALCERROR 0.000 INC2D 0.00 SF2D 0.000000 %TP 0 %TS 0 %R0 900.000 %R1 0.000 %R2 0.000 %R3 0.000 %R4 0.000

Appendices

160

%R5 0.000 %R6 0.000 %R7 0.000 %R8 0.000 %R9 0.000 %ADCSCALE 2048 PREAMP 0 TRIGGER 0 MATRIX 0 VER Cï XB0 0.000 YB0 0.000 ZB0 0.000 XOFFSET 0.00000000 YOFFSET 0.00000000 ZOFFSET 0.00000000 D13 0.00 D14 0.00 D15 0.00 D16 0.00 D17 0.00 D18 0.00 D19 0.00 D20 0.00 D21 0.00 D22 0.00 D23 0.00 D24 0.00 D25 0.00 D26 0.00 D27 0.00 D28 0.00 D29 0.00 D30 0.00 D31 0.00 D32 0.00 C13 0 C14 0 C15 0 C16 0 C17 0 C18 0 C19 0 C20 0 C21 0 C22 0 C23 0 C24 0 C25 0 C26 0 C27 0 C28 0 C29 0 C30 0 C31 0 C32 0 G10 0 G11 0 G12 0 G13 0 G14 0 G15 0 G16 0 G17 0 G18 0 G19 0 G20 0 G21 0 G22 0 G23 0 G24 0 G25 0 G26 0 G27 0 G28 0 G29 0

G30 0 G31 0 G32 0 ACQUISITION 3 RG1 0.00 RG2 0.00 RG3 0.00 RG4 0.00 RG5 0.00 RG6 0.00 RG7 0.00 RG8 0.00 RG9 0.00 %TOTALSTEPS 0 %HIDEERROR 0 %LASTSEQERROR 0 SH6 SH7 SH8 SH9 SH10 FP6 0.00000 FP7 0.00000 FP8 0.00000 FP9 0.00000 FP10 0.00000 %DISPLAYBUFFER 0 QCSHIM1 0 QCSHIM2 0 QCSHIM3 0 QCSHIM4 0 QCSHIM5 0 QCSHIM6 0 QCSHIM7 0 QCSHIM8 0 QCLEDS 0 QCVAR1 0.0 QCVAR2 0.0 QCVAR3 0.0 QCVAR4 0.0 QCVAR5 0.0 QCVAR6 0.0 QCVAR7 0.0 QCVAR8 0.0 QCVAR9 0.0 QCVAR10 0.0 QCVAR11 0.0 QCVAR12 0.0 QCVAR13 0.0 QCVAR14 0.0 QCVAR15 0.0 QCVAR16 0.0 QCVAR17 0.000 QCVAR18 0.000 QCVAR19 0 QCVAR20 0

Appendices

161

Appendix D: Exported data from WinDXP to Excel (W/o/w emulsion with fat phase of soft PMF and Hozol in a ratio of 3:1, 1st repetition, production 09/03/11; analysis 10/3/11.

NMR Data Best Fit Data Distribution

Time Magnitude Time DDAT DCALC DERR TC CCALC

403.95 13765.22 403.95 13765.22 13813.14 -47.92 100.00 0.00

803.95 13733.46 803.95 13733.46 13694.11 39.34 105.57 0.00

1203.95 13583.12 1203.95 13583.12 13577.43 5.70 111.44 0.00

1603.95 13454.82 1603.95 13454.82 13462.97 -8.15 117.65 0.00

2003.95 13376.35 2003.95 13376.35 13350.65 25.70 124.20 0.00

2403.95 13207.53 2403.95 13207.53 13240.36 -32.83 131.11 0.00

2803.95 13162.25 2803.95 13162.25 13132.01 30.23 138.41 0.00

3203.95 13008.36 3203.95 13008.36 13025.53 -17.17 146.12 0.00

3603.95 12940.85 3603.95 12940.85 12920.83 20.02 154.25 0.00

4003.95 12800.83 4003.95 12800.83 12817.85 -17.02 162.84 0.00

4403.95 12731.37 4403.95 12731.37 12716.50 14.87 171.91 0.00

4803.95 12625.24 4803.95 12625.24 12616.74 8.50 181.48 0.00

5203.95 12516.68 5203.95 12516.68 12518.49 -1.82 191.58 0.00

5603.95 12426.43 5603.95 12426.44 12421.71 4.72 202.25 0.00

6003.95 12313.33 6003.95 12313.33 12326.34 -13.00 213.51 0.00

6403.95 12238.05 6403.95 12238.05 12232.32 5.73 225.39 0.00

6803.95 12123.42 6803.95 12123.42 12139.62 -16.20 237.94 0.00

7203.95 12057.64 7203.95 12057.65 12048.18 9.46 251.19 0.00

7603.95 11957.20 7603.95 11957.20 11957.97 -0.77 265.17 0.00

8003.95 11879.82 8003.95 11879.82 11868.95 10.87 279.94 0.00

8403.95 11768.27 8403.95 11768.27 11781.08 -12.81 295.52 0.00

8803.95 11696.46 8803.95 11696.46 11694.32 2.14 311.97 0.00

9203.95 11604.71 9203.95 11604.71 11608.64 -3.93 329.34 0.00

9603.95 11513.35 9603.95 11513.35 11524.02 -10.67 347.68 0.00

10004 11459.54 10003.95 11459.54 11440.42 19.12 367.03 0.00

10404 11351.85 10403.95 11351.85 11357.81 -5.96 387.47 0.00

10804 11288.17 10803.95 11288.17 11276.17 12.00 409.04 0.00

11204 11194.33 11203.95 11194.33 11195.48 -1.15 431.81 0.00

11604 11126.48 11603.95 11126.48 11115.70 10.78 455.85 0.00

12004 11039.83 12003.95 11039.83 11036.82 3.01 481.23 0.00

12404 10952.29 12403.95 10952.29 10958.82 -6.52 508.02 0.00

12804 10889.16 12803.95 10889.16 10881.67 7.49 536.30 0.00

13204 10800.59 13203.95 10800.59 10805.36 -4.77 566.16 0.00

13604 10731.18 13603.95 10731.18 10729.86 1.32 597.68 0.00

14004 10645.42 14003.95 10645.43 10655.17 -9.75 630.96 0.00

14404 10582.34 14403.95 10582.34 10581.27 1.07 666.08 0.00

14804 10496.65 14803.95 10496.65 10508.13 -11.48 703.17 0.00

15204 10432.04 15203.95 10432.04 10435.74 -3.70 742.32 0.00

15604 10355.46 15603.95 10355.46 10364.10 -8.64 783.64 0.00

16004 10287.65 16003.95 10287.65 10293.18 -5.53 827.27 0.00

16404 10210.28 16403.95 10210.28 10222.97 -12.69 873.33 0.00

16804 10156.05 16803.95 10156.05 10153.46 2.59 921.95 0.00

17204 10080.29 17203.95 10080.29 10084.64 -4.35 973.27 0.00

17604 10016.66 17603.95 10016.66 10016.50 0.17 1027.46 0.00

18004 9952.79 18003.95 9952.79 9949.01 3.77 1084.66 0.00

18404 9882.52 18403.95 9882.52 9882.19 0.33 1145.05 0.00

18804 9818.91 18803.95 9818.91 9816.00 2.91 1208.80 0.00

Appendices

162

19204 9749.55 19203.95 9749.55 9750.45 -0.90 1276.09 0.00

19604 9677.36 19603.95 9677.36 9685.52 -8.16 1347.14 0.00

20004 9623.89 20003.95 9623.89 9621.21 2.68 1422.14 0.00

20404 9554.23 20403.95 9554.23 9557.50 -3.27 1501.31 0.00

20804 9502.05 20803.95 9502.05 9494.39 7.66 1584.89 0.00

21204 9432.40 21203.95 9432.40 9431.87 0.53 1673.13 0.00

21604 9373.50 21603.95 9373.50 9369.92 3.58 1766.28 0.00

22004 9302.43 22003.95 9302.43 9308.55 -6.12 1864.61 0.00

22404 9241.87 22403.95 9241.87 9247.74 -5.87 1968.42 0.00

22804 9180.96 22803.95 9180.96 9187.49 -6.53 2078.01 0.00

23204 9126.05 23203.95 9126.05 9127.79 -1.74 2193.70 0.00

23604 9066.78 23603.95 9066.78 9068.63 -1.85 2315.83 0.00

24004 9014.12 24003.95 9014.12 9010.01 4.11 2444.75 0.00

24404 8948.39 24403.95 8948.39 8951.91 -3.52 2580.86 0.00

24804 8888.87 24803.95 8888.87 8894.34 -5.47 2724.55 0.00

25204 8829.93 25203.95 8829.93 8837.29 -7.35 2876.23 0.00

25604 8778.37 25603.95 8778.37 8780.74 -2.37 3036.36 0.00

26004 8727.47 26003.95 8727.47 8724.70 2.78 3205.40 0.00

26404 8664.18 26403.95 8664.18 8669.16 -4.97 3383.86 0.00

26804 8607.43 26803.95 8607.43 8614.10 -6.67 3572.24 0.00

27204 8554.44 27203.95 8554.44 8559.54 -5.10 3771.12 0.00

27604 8494.23 27603.95 8494.23 8505.46 -11.22 3981.07 0.00

28004 8450.95 28003.95 8450.95 8451.85 -0.90 4202.71 0.00

28404 8398.79 28403.95 8398.79 8398.71 0.08 4436.69 1.19

28804 8344.88 28803.95 8344.88 8346.04 -1.16 4683.69 18.87

29204 8301.26 29203.95 8301.26 8293.82 7.44 4944.45 33.09

29604 8237.97 29603.95 8237.97 8242.07 -4.09 5219.72 43.54

30004 8196.44 30003.95 8196.44 8190.76 5.68 5510.32 49.97

30404 8132.53 30403.95 8132.54 8139.90 -7.36 5817.09 52.19

30804 8070.77 30803.95 8070.77 8089.47 -18.70 6140.95 50.06

31204 8038.22 31203.95 8038.22 8039.49 -1.27 6482.83 43.54

31604 7996.35 31603.95 7996.35 7989.93 6.42 6843.75 32.68

32004 7934.90 32003.95 7934.90 7940.81 -5.90 7224.76 17.64

32404 7891.21 32403.95 7891.21 7892.10 -0.89 7626.99 0.00

32804 7850.01 32803.95 7850.01 7843.81 6.20 8051.60 0.00

33204 7799.76 33203.95 7799.76 7795.94 3.82 8499.86 0.00

33604 7747.47 33603.95 7747.47 7748.48 -1.00 8973.07 0.00

34004 7702.40 34003.95 7702.40 7701.42 0.99 9472.63 0.00

34404 7663.82 34403.95 7663.81 7654.76 9.06 10000.00 0.00

34804 7620.12 34803.95 7620.12 7608.50 11.62 10556.73 0.00

35204 7554.68 35203.95 7554.68 7562.63 -7.95 11144.46 0.00

35604 7518.90 35603.95 7518.90 7517.15 1.75 11764.90 0.00

36004 7457.35 36003.95 7457.35 7472.06 -14.71 12419.89 0.00

36404 7418.27 36403.95 7418.27 7427.35 -9.08 13111.34 0.00

36804 7389.85 36803.95 7389.85 7383.02 6.83 13841.29 0.00

37204 7335.53 37203.95 7335.54 7339.06 -3.53 14611.87 0.00

37604 7290.79 37603.95 7290.79 7295.48 -4.69 15425.36 0.00

38004 7246.31 38003.95 7246.31 7252.25 -5.94 16284.14 0.00

38404 7214.14 38403.95 7214.14 7209.40 4.74 17190.72 0.00

38804 7167.19 38803.95 7167.19 7166.90 0.29 18147.78 0.00

39204 7124.46 39203.95 7124.46 7124.76 -0.30 19158.12 0.00

39604 7097.55 39603.95 7097.55 7082.97 14.58 20224.71 0.00

40004 7043.81 40003.95 7043.81 7041.53 2.27 21350.68 0.00

40404 7005.69 40403.95 7005.69 7000.44 5.25 22539.34 0.00

Appendices

163

40804 6966.77 40803.95 6966.77 6959.69 7.08 23794.17 0.00

41204 6916.45 41203.95 6916.45 6919.28 -2.83 25118.87 61.76

41604 6889.40 41603.95 6889.40 6879.21 10.19 26517.31 130.23

42004 6839.68 42003.95 6839.68 6839.47 0.21 27993.61 201.07

42404 6804.17 42403.95 6804.17 6800.06 4.11 29552.09 272.82

42804 6762.64 42803.95 6762.65 6760.98 1.67 31197.35 343.93

43204 6723.67 43203.95 6723.67 6722.22 1.45 32934.20 412.83

43604 6690.10 43603.95 6690.10 6683.78 6.32 34767.74 477.92

44004 6651.45 44003.95 6651.45 6645.66 5.79 36703.36 537.69

44404 6606.52 44403.95 6606.52 6607.85 -1.33 38746.75 590.68

44804 6580.67 44803.95 6580.67 6570.36 10.31 40903.90 635.57

45204 6544.54 45203.95 6544.54 6533.17 11.37 43181.14 671.20

45604 6506.04 45603.95 6506.04 6496.30 9.74 45585.16 696.61

46004 6463.99 46003.95 6463.99 6459.72 4.27 48123.03 711.05

46404 6433.49 46403.95 6433.49 6423.44 10.05 50802.18 714.02

46804 6395.06 46803.95 6395.06 6387.47 7.60 53630.49 705.28

47204 6356.06 47203.95 6356.06 6351.78 4.28 56616.26 684.85

47604 6324.24 47603.95 6324.24 6316.39 7.85 59768.26 653.01

48004 6291.07 48003.95 6291.07 6281.29 9.78 63095.73 610.31

48404 6248.44 48403.95 6248.44 6246.48 1.96 66608.46 557.54

48804 6223.60 48803.95 6223.60 6211.95 11.66 70316.76 495.72

49204 6177.73 49203.95 6177.73 6177.70 0.04 74231.50 426.04

49604 6142.95 49603.95 6142.95 6143.73 -0.78 78364.19 349.88

50004 6125.86 50003.95 6125.86 6110.03 15.82 82726.96 268.73

50404 6084.52 50403.95 6084.52 6076.61 7.91 87332.62 184.19

50804 6048.58 50803.95 6048.58 6043.46 5.12 92194.69 97.87

51204 6022.61 51203.95 6022.61 6010.58 12.03 97327.44 11.42

51604 5980.81 51603.95 5980.81 5977.97 2.84 102745.95 0.00

52004 5951.21 52003.95 5951.21 5945.62 5.60 108466.13 0.00

52404 5915.88 52403.95 5915.88 5913.53 2.35 114504.76 0.00

52804 5874.35 52803.95 5874.35 5881.70 -7.35 120879.58 0.00

53204 5857.35 53203.95 5857.35 5850.13 7.23 127609.30 0.00

53604 5835.63 53603.95 5835.63 5818.81 16.82 134713.70 0.00

54004 5790.76 54003.95 5790.76 5787.74 3.02 142213.61 0.00

54404 5761.21 54403.95 5761.21 5756.93 4.28 150131.08 0.00

54804 5722.16 54803.95 5722.16 5726.36 -4.19 158489.31 0.00

55204 5699.70 55203.95 5699.70 5696.03 3.66 167312.89 0.00

55604 5668.54 55603.95 5668.54 5665.95 2.59 176627.70 0.00

56004 5644.55 56003.95 5644.55 5636.11 8.43 186461.09 0.00

56404 5609.90 56403.95 5609.90 5606.51 3.39 196841.94 0.00

56804 5580.37 58403.95 5480.99 5462.01 18.98 207800.72 0.00

57204 5545.81 60803.95 5280.49 5296.05 -15.56 219369.61 0.00

57604 5519.98 62803.95 5159.25 5163.66 -4.41 231582.58 0.00

58004 5497.46 65203.95 5015.17 5011.53 3.64 244475.47 0.00

58404 5480.99 67603.95 4865.27 4866.39 -1.12 258086.16 0.00

58804 5449.19 70003.95 4724.24 4727.88 -3.64 272454.59 0.00

59204 5420.94 72403.95 4592.80 4595.66 -2.86 287622.94 0.00

59604 5382.42 75203.95 4443.30 4448.91 -5.62 303635.78 0.00

60004 5344.91 77603.95 4330.12 4329.23 0.89 320540.09 0.00

60404 5332.40 80403.95 4187.15 4196.31 -9.15 338385.50 0.00

60804 5280.49 83203.95 4072.83 4070.21 2.62 357224.44 0.00

61204 5277.95 86403.95 3930.26 3933.94 -3.68 377112.22 0.00

61604 5243.27 89603.95 3805.16 3805.50 -0.34 398107.16 0.00

62004 5226.78 92803.95 3681.22 3684.38 -3.17 420271.00 17.77

Appendices

164

62404 5200.83 96003.95 3561.41 3570.11 -8.69 443668.72 56.86

62804 5159.25 99603.95 3439.43 3449.17 -9.75 468369.09 91.49

63204 5133.06 103203.95 3328.51 3335.75 -7.23 494444.63 121.23

63604 5123.35 106803.95 3215.61 3229.29 -13.69 521971.81 145.74

64004 5100.13 110803.95 3111.90 3118.58 -6.68 551031.56 164.75

64404 5067.89 114403.95 3011.66 3025.25 -13.58 581709.13 178.12

64804 5035.69 118803.95 2903.72 2918.66 -14.94 614094.63 185.77

65204 5015.17 122803.95 2801.45 2828.36 -26.91 648283.13 187.72

65604 4989.43 127203.95 2722.03 2735.69 -13.66 684375.00 184.04

66004 4961.58 132003.95 2632.57 2641.89 -9.32 722476.19 174.88

66404 4939.68 136803.95 2541.61 2555.03 -13.42 762698.56 160.46

66804 4918.99 141603.95 2451.01 2474.49 -23.48 805160.31 141.02

67204 4900.47 146803.95 2372.46 2393.73 -21.27 849986.00 116.89

67604 4865.27 152003.95 2304.48 2319.09 -14.61 897307.25 88.39

68004 4857.08 157603.95 2226.26 2244.90 -18.63 947263.00 55.89

68404 4826.04 163203.95 2164.15 2176.50 -12.35 1000000.00 19.77

68804 4798.83 168803.95 2101.72 2113.32 -11.60 1055673.00 0.00

69204 4769.75 175203.95 2026.44 2046.84 -20.41 1114445.50 0.00

69604 4754.56 181203.95 1988.95 1989.51 -0.56 1176490.00 0.00

70004 4724.24 188003.95 1921.30 1929.73 -8.43 1241988.80 0.00

70404 4715.29 194403.95 1867.97 1877.97 -10.00 1311133.90 0.00

70804 4682.62 201603.95 1825.78 1824.37 1.41 1384128.80 0.00

71204 4662.75 208803.95 1775.04 1775.12 -0.08 1461187.30 0.00

71604 4635.32 216403.95 1727.00 1727.30 -0.30 1542536.00 0.00

72004 4614.75 224003.95 1688.79 1683.25 5.54 1628413.50 0.00

72404 4592.80 232003.95 1655.04 1640.47 14.57 1719072.30 0.00

72804 4582.22 240403.95 1602.48 1599.02 3.46 1814778.10 0.00

73204 4555.72 249203.95 1566.34 1558.94 7.39 1915812.30 0.00

73604 4528.33 258003.95 1522.41 1521.85 0.56 2022471.30 0.00

74004 4511.78 267203.94 1494.97 1485.84 9.13 2135068.30 0.00

74404 4476.46 276803.94 1459.31 1450.91 8.40 2253934.00 0.00

74804 4465.04 286803.94 1431.38 1417.01 14.37 2379417.30 0.00

75204 4443.30 297203.94 1407.32 1384.09 23.23 2511886.50 0.00

75604 4438.54 308003.94 1368.06 1352.08 15.97 2651730.80 0.00

76004 4411.46 318803.94 1340.95 1322.00 18.95 2799360.50 0.00

76404 4390.43 330403.94 1299.98 1291.56 8.42 2955209.30 0.00

76804 4368.62 342403.94 1270.12 1261.82 8.30 3119734.50 0.00

77204 4333.96 354403.94 1255.04 1233.63 21.40 3293419.50 0.00

77604 4330.12 367203.94 1222.80 1205.06 17.75 3476774.00 0.00

78004 4314.82 380403.94 1197.63 1177.00 20.63 3670336.50 0.00

78404 4295.77 394003.94 1159.00 1149.39 9.61 3874675.00 0.00

78804 4257.78 408403.94 1137.38 1121.43 15.95 4090390.00 0.00

79204 4252.39 422803.94 1108.57 1094.63 13.95 4318114.00 0.00

79604 4232.42 438003.94 1074.79 1067.45 7.35 4558516.50 0.00

80004 4204.33 454003.94 1051.15 1039.94 11.21 4812302.50 0.00

80404 4187.15 470403.94 1015.79 1012.81 2.98 5080218.00 0.00

80804 4181.66 487203.94 983.08 986.02 -2.94 5363049.00 0.00

81204 4166.34 504803.94 968.23 958.95 9.28 5661626.00 0.00

81604 4142.49 522803.94 927.81 932.24 -4.43 5976825.50 0.00

82004 4114.34 541603.94 911.52 905.32 6.20 6309573.50 0.00

82404 4096.67 560803.94 872.59 878.77 -6.18 6660846.50 0.00

82804 4083.22 581203.94 852.87 851.54 1.32 7031675.50 0.00

83204 4072.83 602003.94 817.51 824.77 -7.25 7423150.00 0.00

83604 4055.30 623603.94 797.14 797.95 -0.81 7836419.00 0.00

Appendices

165

84004 4043.56 646003.94 767.48 771.15 -3.67 8272696.00 0.00

84404 4007.79 669203.94 739.90 744.43 -4.53 8733262.00 0.00

84804 4002.46 693203.94 712.07 717.82 -5.75 9219468.00 0.00

85204 3984.78 718403.94 690.64 690.97 -0.33 9732744.00 0.00

85604 3974.14 744003.94 652.90 664.79 -11.89 10274595.00 0.00

86004 3940.98 770803.94 629.25 638.49 -9.25 10846612.00 0.00

86404 3930.26 798403.94 606.78 612.56 -5.78 11450476.00 0.00

86804 3923.15 827203.94 585.51 586.67 -1.16 12087958.00 0.00

87204 3899.31 856803.94 558.08 561.25 -3.17 12760931.00 0.00

87604 3871.86 887603.94 541.60 536.02 5.58 13471370.00 0.00

88004 3880.11 919603.94 490.83 511.06 -20.22 14221362.00 0.00

88404 3844.71 952403.94 480.73 486.72 -5.99 15013107.00 0.00

88804 3832.53 986803.94 468.22 462.50 5.72 15848932.00 0.00

89204 3818.26 1022403.90 438.88 438.75 0.13 16731289.00 0.00

89604 3805.16 1058804.00 411.49 415.77 -4.28 17662770.00 0.00

90004 3797.18 1097204.00 383.19 392.89 -9.70 18646110.00 0.00

90404 3766.32 1136404.00 355.42 370.88 -15.46 19684194.00 0.00

90804 3758.62 1177204.00 334.64 349.33 -14.69 20780072.00 0.00

91204 3731.92 1219604.00 323.30 328.31 -5.00 21936962.00 0.00

91604 3727.14 1263604.00 304.89 307.88 -2.99 23158258.00 0.00

92004 3702.58 1308804.00 284.18 288.27 -4.08 24447548.00 0.00

92404 3694.90 1356004.00 276.73 269.17 7.56 25808616.00 0.00

92804 3681.22 1404404.00 251.08 250.95 0.13 27245458.00 0.00

93204 3667.97 1454804.00 229.49 233.33 -3.84 28762294.00 0.00

93604 3657.06 1507204.00 231.85 216.37 15.48 30363578.00 0.00

94004 3641.76 1561604.00 197.40 200.11 -2.72 32054008.00 0.00

94404 3619.31 1617604.00 183.85 184.70 -0.85 33838552.00 0.00

94804 3611.04 1675604.00 165.65 170.03 -4.38 35722444.00 0.00

95204 3580.92 1736004.00 152.20 156.03 -3.83 37711220.00 0.00

95604 3579.61 1798404.00 133.26 142.83 -9.57 39810716.00 0.00

96004 3561.41 1862804.00 127.32 130.41 -3.09 42027100.00 0.00

96404 3547.45 1929604.00 127.42 118.70 8.72 44366872.00 0.00

96804 3524.88 1999204.00 93.06 107.66 -14.60 46836908.00 0.00

97204 3522.61 2070804.00 92.28 97.41 -5.13 49444460.00 0.00

97604 3529.93 2145204.00 92.13 87.82 4.31 52197184.00 0.00

98004 3499.69 2222404.00 78.60 78.91 -0.31 55103156.00 0.00

98404 3474.71 2302404.00 70.21 70.65 -0.44 58170912.00 0.00

98804 3464.56 2384804.00 65.46 63.08 2.38 61409464.00 0.00

99204 3467.90 2470804.00 59.91 56.06 3.84 64828312.00 0.00

99604 3439.43 2559604.00 31.14 49.67 -18.52 68437496.00 0.00

100004 3420.07 2651204.00 46.53 43.85 2.68 72247616.00 0.00

100404 3418.11 2746804.00 35.85 38.53 -2.69 76269856.00 0.00

100804 3410.61 2845204.00 40.50 33.75 6.75 80516032.00 0.00

101204 3385.87 2947604.00 41.76 29.42 12.34 84998600.00 0.00

101604 3375.54 3053604.00 21.38 25.54 -4.16 89730728.00 0.00

102004 3365.58 3163204.00 25.08 22.07 3.01 94726304.00 0.00

102404 3347.50 3276804.00 27.59 18.99 8.59 100000000.00 0.00

3276804 27.59

Appendices

166

Appendix E Appendix Commands Profilometry (RINMR, Maran Ultra 23 spectrometer) Acquisition Sequence Load All Profile Parameters Load all (or REP) Profilometry.RiPar GO FT MAG Export to Excel New sample: Go FT MAG Export to Excel Parameters in Profilometry.RiPar ID Value P90 7.50 P180 15.00 P1 1.00 P2 1.00 P3 1.00 P4 1.00 P5 1.00 DEAD1 7.00 DEAD2 2.80 DW 10.00 RD 10000000.00 TAU 6000.00 D1 100.00 D2 3562.00 D3 1000.00 D4 1.00 D5 1.00 D6 1000000.00 D7 1000000.00 D8 1000000.00 D9 1000000.00 D10 1000000.00 D11 1000000.00 D12 1000000.00 SI 512 NECH 256 NS 16 SF 23.400000 O1 27932.39 SF2 0.000000 O2 0.00 FW 1.0 RG 1.20 PH1 0213 PH2 0213 PH3 0011 PH4 0213 PH5 0213 LB 0.00 PA 0.00 PB 0.00 DP 0.00 TRIM0 49

TRIM1 45 TRIM2 0 TRIM3 0 TRIM4 0 TRIM5 0 TRIM6 157 TRIM7 159 TRIM8 0 TRIM9 158 TRIMA 0 TRIMB 173 TRIMC 0 TRIMD 167 TRIME 0 TRIMF 170 TRIMG 0 TRIMH 0 TRIMI 0 TRIMJ 0 TRIMK 0 TRIML 0 TRIMM 0 TRIMN 0 TRIMO 0 TRIMP 0 TRIMQ 0 TRIMR 0 TRIMS 0 TRIMT 0 TRIMU 0 TRIMV 0 TRIMW 75 TRIMX 0 SW 100000.0 DB 24 BES 1000000 BUT 1000000 RFA0 100.0 RFA1 0.0 RFA2 0.0 RFA3 0.0 RFA4 0.0 RFA5 0.0 RF2A0 0.0

Appendices

167

RF2A1 0.0 RF2A2 0.0 RF2A3 0.0 RF2A4 0.0 RF2A5 0.0 WW 5.0 C1 0 C2 0 C3 0 C4 0 C5 0 TI ???? SMP 0 GX 0 GY 3000 GZ 0 G1 3500 G2 3500 G3 0 G4 0 G5 0 G6 0 G7 0 G8 0 G9 0 IG1 1 IG2 1 IG3 1 IG4 1 IG5 1 IG6 1 IG7 1 IG8 1 IG9 1 MAC1 0.0 MAC2 0.0 SH1 SH2 SH3 SH4 SH5 DS 0 NA 1 SEQ PROFILE GRS X GRP Y GRR Z %TEMPDIR Z %ROOTDIR Z %DATADIR E:\parameters\CPMG_daan20090501.RiPar %EXPORTDIR C:\Documents and Settings\Jan\Desktop\Dodac0.5percent_0.1Mn_tau50.00001 %LISTFILEC:\Documents and Settings\Jan\My Documents\PhD\Enclosed volume in DODAC\Maran measurements\lists#\deltaGlist.txt %LOGFILE C:\Program Files\Resonance\RINMR\DATA\DODAC_0.1PERC+MNCL2.00001.RiLog %HARDWARE 0 GSH1 GSH2 GSH3 GSH4 GSH5 SNR 100 %SEQFILE C:\Program Files\Resonance\RINMR\bak\bin\CPMG.exe PP 0 NOBC 0 C6 1 C7 1 C8 1 C9 1 C10 1 C11 1 C12 1 FP1 1.00000 FP2 1.00000 FP3 1.00000 FP4 1.00000 FP5 1.00000 %LASTWEIGHT 0.000 %GOSTATE 0 %SCANSDONE 0 %CAL1 0.000000 %CAL2 0.000000 %CAL3 0.000000

%CAL4 0.000000 %CALIBDIR C:\Program Files\Resonance\RINMR\DATA\ %1 %2 %3 %4 %5 PREXA1 0.000 PREXK1 100000000.00 PREXA2 0.000 PREXK2 100000000.00 PREXA3 0.000 PREXK3 100000000.00 PREXA4 0.000 PREXK4 100000000.00 PREYA1 0.000 PREYK1 100000000.00 PREYA2 0.000 PREYK2 100000000.00 PREYA3 0.000 PREYK3 100000000.00 PREYA4 0.000 PREYK4 100000000.00 PREZA1 0.000 PREZK1 100000000.00 PREZA2 0.000 PREZK2 100000000.00 PREZA3 0.000 PREZK3 100000000.00 PREZA4 0.000 PREZK4 100000000.00 XB0A 0.000 XB0K 100000000.00 YB0A 0.000 YB0K 100000000.00 ZB0A 0.000 ZB0K 100000000.00 PREBA4 0.000 PREBK4 0.00 PPTH 4.0 PPRF 50 PPAF 1 PPPF 0 DEC90 5000000.00 CPD WALTZ16 GSLICEX 1.000 GSLICEY 0.000 GSLICEZ 0.000 GPHASEX 0.000 GPHASEY 1.000 GPHASEZ 0.000 GREADX 0.000 GREADY 0.000 GREADZ 1.000 GREAD 0 GPHASE 3000 GSLICE 0 %SNR 0 GD 0.00 %ERROR 0 %CALCERROR 0.000 INC2D 0.00 SF2D 0.000000 %TP 0 %TS 0 %R0 0.000 %R1 0.000 %R2 0.000 %R3 0.000 %R4 0.000 %R5 0.000 %R6 0.000 %R7 0.000 %R8 0.000 %R9 0.000 %ADCSCALE 2048 PREAMP 0 TRIGGER 0 MATRIX 0 VER äeú XB0 0.000 YB0 0.000 ZB0 0.000 XOFFSET 0.00000000 YOFFSET 0.00000000 ZOFFSET 0.00000000

Appendices

168

D13 1000000.00 D14 1000000.00 D15 1000000.00 D16 1000000.00 D17 1000000.00 D18 1000000.00 D19 1000000.00 D20 1000000.00 D21 1000000.00 D22 1000000.00 D23 1000000.00 D24 1000000.00 D25 1000000.00 D26 1000000.00 D27 1000000.00 D28 1000000.00 D29 1000000.00 D30 1000000.00 D31 1000000.00 D32 1000000.00 C13 0 C14 0 C15 0 C16 0 C17 0 C18 0 C19 0 C20 0 C21 0 C22 0 C23 0 C24 0 C25 0 C26 0 C27 0 C28 0 C29 0 C30 0 C31 0 C32 0 G10 0 G11 0 G12 0 G13 0 G14 0 G15 0 G16 0 G17 0 G18 0 G19 0 G20 0 G21 0 G22 0 G23 0 G24 0 G25 0 G26 0 G27 0

G28 0 G29 0 G30 0 G31 0 G32 0 ACQUISITION 3 RG1 0.00 RG2 0.00 RG3 0.00 RG4 0.00 RG5 0.00 RG6 0.00 RG7 0.00 RG8 0.00 RG9 0.00 %TOTALSTEPS 0 %HIDEERROR 0 %LASTSEQERROR 0 SH6 SH7 SH8 SH9 SH10 FP6 1.00000 FP7 1.00000 FP8 1.00000 FP9 1.00000 FP10 1.00000 %DISPLAYBUFFER 0 QCSHIM1 0 QCSHIM2 0 QCSHIM3 0 QCSHIM4 0 QCSHIM5 0 QCSHIM6 0 QCSHIM7 0 QCSHIM8 0 QCLEDS 0 QCVAR1 0.0 QCVAR2 0.0 QCVAR3 0.0 QCVAR4 0.0 QCVAR5 0.0 QCVAR6 0.0 QCVAR7 0.0 QCVAR8 0.0 QCVAR9 0.0 QCVAR10 0.0 QCVAR11 0.0 QCVAR12 0.0 QCVAR13 0.0 QCVAR14 0.0 QCVAR15 0.0 QCVAR16 0.0 QCVAR17 0.000 QCVAR18 0.000 QCVAR19 0 QCVAR20 0

Appendices

169

Appendix F Table: The experimental numerical data of the echo intensities as a function of small delta of different emulsions

Measured Echo Intensity (I)

H0/1 Prod. date 8/9/10 M0/1 Prod. date 9/9/10 P0/1 Prod. date 9/9/10

∆ (s) sample 1 sample 2 Sample 3 sample 1 Sample 2 sample 3 sample 1 sample 2 sample 3

4.00E-04 1.65E+03 1.71E+03 1.87E+03 1.45E+03 1.31E+03 1.38E+03 4.30E+03 3.52E+03 3.97E+03

6.00E-04 1.71E+03 1.87E+03 2.11E+03 1.39E+03 1.25E+03 1.33E+03 3.99E+03 3.34E+03 3.72E+03

8.00E-04 1.70E+03 2.01E+03 2.28E+03 1.33E+03 1.23E+03 1.29E+03 3.76E+03 3.22E+03 3.54E+03

1.00E-03 1.62E+03 2.03E+03 2.21E+03 1.30E+03 1.20E+03 1.26E+03 3.58E+03 3.11E+03 3.39E+03

1.25E-03 1.45E+03 1.86E+03 1.97E+03 1.24E+03 1.13E+03 1.19E+03 3.38E+03 2.98E+03 3.21E+03

1.50E-03 1.28E+03 1.66E+03 1.70E+03 1.17E+03 1.08E+03 1.14E+03 3.20E+03 2.83E+03 3.07E+03

1.75E-03 1.10E+03 1.40E+03 1.46E+03 1.10E+03 1.02E+03 1.08E+03 3.07E+03 2.74E+03 2.94E+03

2.00E-03 9.68E+02 1.24E+03 1.27E+03 1.02E+03 9.59E+02 1.02E+03 2.94E+03 2.63E+03 2.85E+03

2.25E-03 8.03E+02 1.04E+03 1.11E+03 9.49E+02 9.05E+02 9.69E+02 2.85E+03 2.56E+03 2.77E+03

2.50E-03 7.09E+02 9.46E+02 9.63E+02 8.82E+02 8.39E+02 8.85E+02 2.74E+03 2.48E+03 2.70E+03

2.75E-03 6.25E+02 8.56E+02 8.38E+02 8.04E+02 7.90E+02 8.18E+02 2.66E+03 2.42E+03 2.64E+03

3.00E-03 5.42E+02 7.44E+02 7.51E+02 7.45E+02 7.27E+02 7.75E+02 2.57E+03 2.35E+03 2.57E+03

3.25E-03 4.60E+02 6.57E+02 6.49E+02 6.86E+02 6.73E+02 7.26E+02 2.50E+03 2.29E+03 2.51E+03

3.50E-03 4.05E+02 5.89E+02 5.84E+02 6.27E+02 6.30E+02 6.58E+02 2.41E+03 2.22E+03 2.45E+03

3.75E-03 3.12E+02 5.07E+02 4.52E+02 5.64E+02 5.89E+02 6.21E+02 2.35E+03 2.18E+03 2.39E+03

4.00E-03 2.90E+02 4.75E+02 4.62E+02 5.21E+02 5.45E+02 5.82E+02 2.28E+03 2.14E+03 2.32E+03

4.50E-03 2.00E+02 3.23E+02 3.45E+02 4.47E+02 4.82E+02 5.14E+02 2.15E+03 2.03E+03 2.23E+03

Measured Echo Intensity (I)

H0.5/1 Prod. date 22/9/10

∆ (s) sample 1 sample 2 Sample 3 5.00E-04 3.68E+03 3.68E+03 3.55E+03 7.50E-04 3.36E+03 3.36E+03 3.23E+03 1.00E-03 3.20E+03 3.20E+03 3.10E+03 1.25E-03 3.04E+03 3.04E+03 2.95E+03 1.50E-03 2.91E+03 2.91E+03 2.77E+03 1.75E-03 2.74E+03 2.74E+03 2.60E+03 2.00E-03 2.54E+03 2.54E+03 2.43E+03 2.25E-03 2.37E+03 2.37E+03 2.28E+03 2.50E-03 2.20E+03 2.20E+03 2.11E+03 2.75E-03 2.02E+03 2.02E+03 1.95E+03 3.00E-03 1.90E+03 1.90E+03 1.83E+03 3.25E-03 1.72E+03 1.72E+03 1.67E+03 3.50E-03 1.64E+03 1.64E+03 1.56E+03 4.00E-03 1.34E+03 1.34E+03 1.25E+03 4.50E-03 1.16E+03 1.16E+03 1.09E+03 5.00E-03 1.02E+03 1.02E+03 9.65E+02 6.00E-03 6.86E+02 6.86E+02 7.68E+02 8.00E-03 4.20E+02 4.20E+02 4.03E+02

Appendices

170

Details H0/1 sample 1

δ (s) ∆ (s) G1 g (Tesla/m) I g^2.δ^2.(∆-δ/3)

4.00E-04 2.00E-01 18000 1.74E+00 1.65E+03 9.68E-08

6.00E-04 2.00E-01 18000 1.74E+00 1.71E+03 2.18E-07

8.00E-04 2.00E-01 18000 1.74E+00 1.70E+03 3.87E-07

1.00E-03 2.00E-01 18000 1.74E+00 1.62E+03 6.04E-07

1.25E-03 2.00E-01 18000 1.74E+00 1.45E+03 9.44E-07

1.50E-03 2.00E-01 18000 1.74E+00 1.28E+03 1.36E-06

1.75E-03 2.00E-01 18000 1.74E+00 1.10E+03 1.85E-06

2.00E-03 2.00E-01 18000 1.74E+00 9.68E+02 2.41E-06

2.25E-03 2.00E-01 18000 1.74E+00 8.03E+02 3.05E-06

2.50E-03 2.00E-01 18000 1.74E+00 7.09E+02 3.77E-06

2.75E-03 2.00E-01 18000 1.74E+00 6.25E+02 4.56E-06

3.00E-03 2.00E-01 18000 1.74E+00 5.42E+02 5.42E-06

3.25E-03 2.00E-01 18000 1.74E+00 4.60E+02 6.36E-06

3.50E-03 2.00E-01 18000 1.74E+00 4.05E+02 7.37E-06

3.75E-03 2.00E-01 18000 1.74E+00 3.12E+02 8.46E-06

4.00E-03 2.00E-01 18000 1.74E+00 2.90E+02 9.62E-06

4.50E-03 2.00E-01 18000 1.74E+00 2.00E+02 1.22E-05

Appendices

171

Appendix G: output of a profilometric analysis Frequency (MHz) Signal intensity

0.049804688 273.2489624 Frequency 23427932

0.049609375 235.45047 P90 7.5E-06

0.049414063 256.2937927 P180 1.5E-05

0.04921875 286.750885 P1 1E-06

0.049023438 901.8967896 P2 1E-06

0.048828125 637.4200439 P3 1E-06

0.048632813 407.6343079 P4 1E-06

0.0484375 178.0191498 P5 1E-06

0.048242188 155.5707703 DEAD1 7E-06

0.048046875 296.5934143 DEAD2 2.8E-06

0.047851563 778.2650757 DW 1E-05

0.04765625 296.4411621 RD 10

0.047460938 558.7873535 TAU 0.006

0.047265625 600.5683594 D1 1E-04

0.047070313 139.3050842 D2 0.003562

0.046875 455.2594299 D3 0.001

0.046679688 466.1853943 D4 1E-06

0.046484375 145.8015747 D5 1E-06

0.046289063 664.8319092 D6 1

0.04609375 510.8852539 D7 1

0.045898438 460.7337341 D8 1

0.045703125 162.0378113 D9 1

0.045507813 297.1578674 D10 1

0.0453125 599.9174805 D11 1

0.045117188 631.8066406 D12 1

0.044921875 271.763092 SI 512

0.044726563 414.2615662 NECH 256

0.04453125 402.9092712 NS 16

0.044335938 544.3898926 SF 23400000

0.044140625 760.6894531 O1 27932.39

0.043945313 287.5783691 SF2 0

0.04375 156.998291 O2 0

0.043554688 321.2329712 FW 1

0.043359375 392.8141479 RG 1.2

0.043164063 214.7452393 PH1 0213

0.04296875 238.5203247 PH2 0213

0.042773438 618.4665527 PH3 0011

0.042578125 691.7803345 PH4 0213

0.042382813 326.994751 PH5 0213

0.0421875 478.6191406 LB 0

0.041992188 133.2767792 PA 0

0.041796875 435.1164551 PB 0

0.041601563 655.3277588 DP 1.034583

0.04140625 270.3832397 TRIM0 49

0.041210938 59.87940216 TRIM1 45

0.041015625 506.2037048 TRIM2 0

0.040820313 1022.53894 TRIM3 0

0.040625 293.696228 TRIM4 0

0.040429688 113.4191132 TRIM5 0

0.040234375 465.0850525 TRIM6 157

0.040039063 776.0014648 TRIM7 159

0.03984375 603.4848633 TRIM8 0

Appendices

172

0.039648438 286.8362732 TRIM9 158

0.039453125 152.5377045 TRIMA 0

0.039257813 524.3954468 TRIMB 173

0.0390625 420.5890808 TRIMC 0

0.038867188 222.1972809 TRIMD 167

0.038671875 347.4411621 TRIME 0

0.038476563 222.091156 TRIMF 170

0.03828125 399.2488403 TRIMG 0

0.038085938 371.6633606 TRIMH 0

0.037890625 299.5723877 TRIMI 0

0.037695313 526.5463867 TRIMJ 0

0.0375 230.3275604 TRIMK 0

0.037304688 233.6271362 TRIML 0

0.037109375 190.8079681 TRIMM 0

0.036914063 512.5438843 TRIMN 0

0.03671875 904.374939 TRIMO 0

0.036523438 160.8424988 TRIMP 0

0.036328125 112.9999237 TRIMQ 0

0.036132813 221.906723 TRIMR 0

0.0359375 596.473938 TRIMS 0

0.035742188 117.9434891 TRIMT 0

0.035546875 463.7452393 TRIMU 0

0.035351563 384.6939087 TRIMV 0

0.03515625 295.9091187 TRIMW 75

0.034960938 407.1180115 TRIMX 0

0.034765625 117.0415649 SW 100000

0.034570313 503.1583862 DB 24

0.034375 202.5902405 BES 1000000

0.034179688 227.3736115 BUT 1000000

0.033984375 330.9534912 RFA0 100

0.033789063 186.7667847 RFA1 0

0.03359375 607.4312744 RFA2 0

0.033398438 234.3165131 RFA3 0

0.033203125 492.7983704 RFA4 0

0.033007813 508.1192017 RFA5 0

0.0328125 475.6696167 RF2A0 0

0.032617188 816.7148438 RF2A1 0

0.032421875 361.7311096 RF2A2 0

0.032226563 846.8509521 RF2A3 0

0.03203125 337.5320129 RF2A4 0

0.031835938 328.0878601 RF2A5 0

0.031640625 238.6884155 WW 5

0.031445313 224.521698 C1 0

0.03125 611.2073975 C2 0

0.031054688 559.6374512 C3 0

0.030859375 270.987915 C4 0

0.030664063 92.80229187 C5 0

0.03046875 389.1214905 TI ????

0.030273438 284.5443115 SMP 0

0.030078125 531.8380737 GX 0

0.029882813 206.9532471 GY 3000

0.0296875 386.1412354 GZ 0

0.029492188 454.256958 G1 3500

0.029296875 126.819603 G2 3500

Appendices

173

0.029101563 374.5834351 G3 0

0.02890625 408.7837219 G4 0

0.028710938 374.0313721 G5 0

0.028515625 497.9112244 G6 0

0.028320313 534.1647339 G7 0

0.028125 334.4261169 G8 0

0.027929688 345.5342712 G9 0

0.027734375 147.9359436 IG1 1

0.027539063 50.90776443 IG2 1

0.02734375 215.4097748 IG3 1

0.027148438 637.8907471 IG4 1

0.026953125 308.1389771 IG5 1

0.026757813 312.6181335 IG6 1

0.0265625 366.6786499 IG7 1

0.026367188 468.5193787 IG8 1

0.026171875 467.3326111 IG9 1

0.025976563 647.7133789 MAC1 0

0.02578125 190.9958038 MAC2 0

0.025585938 341.8713989 SH1

0.025390625 161.2305756 SH2

0.025195313 541.5947876 SH3

0.025 419.7670593 SH4

0.024804688 298.8596497 SH5

0.024609375 635.3144531 DS 0

0.024414063 408.7278137 NA 1

0.02421875 401.7145996 SEQ PROFILE

0.024023438 420.7365723 GRS X

0.023828125 767.1320801 GRP Y

0.023632813 216.095993 GRR Z

0.0234375 179.8995361

0.023242188 523.973999

0.023046875 390.7264099

0.022851563 212.7952881

0.02265625 418.6812744

0.022460938 300.6339111

0.022265625 211.0618744

0.022070313 285.1594238 GSH1

0.021875 214.8972626 GSH2

0.021679688 410.0625 GSH3

0.021484375 81.38557434 GSH4

0.021289063 98.58622742 GSH5

0.02109375 305.0961304 SNR 100

0.020898438 217.923996

0.020703125 386.3705444 PP 0

0.020507813 455.2966309 NOBC 0

0.0203125 704.4728394 C6 1

0.020117188 330.5545044 C7 1

0.019921875 89.52977753 C8 1

0.019726563 456.6725769 C9 1

0.01953125 364.1968689 C10 1

0.019335938 220.3947906 C11 1

0.019140625 267.0543518 C12 1

0.018945313 337.0260925 FP1 1

0.01875 246.9345703 FP2 1

Appendices

174

0.018554688 460.9109802 FP3 1

0.018359375 290.5318298 FP4 1

0.018164063 368.2280579 FP5 1

0.01796875 233.395462

0.017773438 218.7448425

0.017578125 81.34256744

0.017382813 426.1618958

0.0171875 207.6192932

0.016992188 319.343811

0.016796875 457.0608215

0.016601563 281.1471863

0.01640625 258.8962708

0.016210938 390.9786682

0.016015625 420.4814453

0.015820313 499.5676575

0.015625 240.9592285

0.015429688 522.4503784 PREXA1 0

0.015234375 312.4052429 PREXK1 100

0.015039063 110.3498611 PREXA2 0

0.01484375 677.1757202 PREXK2 100

0.014648438 618.7169189 PREXA3 0

0.014453125 511.7521362 PREXK3 100

0.014257813 98.89109802 PREXA4 0

0.0140625 435.5617676 PREXK4 100

0.013867188 238.7025604 PREYA1 0

0.013671875 195.4999695 PREYK1 100

0.013476563 135.7706757 PREYA2 0

0.01328125 566.0339966 PREYK2 100

0.013085938 545.1677246 PREYA3 0

0.012890625 303.1686096 PREYK3 100

0.012695313 798.43573 PREYA4 0

0.0125 88.90397644 PREYK4 100

0.012304688 49.86899567 PREZA1 0

0.012109375 328.4577942 PREZK1 100

0.011914063 438.9898987 PREZA2 0

0.01171875 385.4032288 PREZK2 100

0.011523438 132.2007446 PREZA3 0

0.011328125 408.8601685 PREZK3 100

0.011132813 369.9115601 PREZA4 0

0.0109375 565.9788208 PREZK4 100

0.010742188 462.2780151 XB0A 0

0.010546875 270.3238525 XB0K 100

0.010351563 87.88369751 YB0A 0

0.01015625 202.5294037 YB0K 100

0.009960938 316.1564636 ZB0A 0

0.009765625 189.2915039 ZB0K 100

0.009570313 906.8520508 PREBA4 0

0.009375 486.893219 PREBK4 0

0.009179688 610.1662598 PPTH 4

0.008984375 215.4837189 PPRF 50

0.008789063 447.9555969 PPAF 1

0.00859375 310.1137695 PPPF 0

0.008398438 74.51745605 DEC90 5

0.008203125 210.2084503 CPD WALTZ16

Appendices

175

0.008007813 437.8165283 GSLICEX 1

0.0078125 594.2328491 GSLICEY 0

0.007617188 574.9415894 GSLICEZ 0

0.007421875 465.2231445 GPHASEX 0

0.007226563 393.682373 GPHASEY 1

0.00703125 187.5591888 GPHASEZ 0

0.006835938 257.3603516 GREADX 0

0.006640625 175.2765808 GREADY 0

0.006445313 710.3255005 GREADZ 1

0.00625 565.4083252 GREAD 0

0.006054688 729.3746338 GPHASE 3000

0.005859375 577.6845093 GSLICE 0

0.005664063 794.4776611

0.00546875 1312.459351 GD 0

0.005273438 343.3006897

0.005078125 479.5255127

0.004882813 541.0355835 INC2D 0

0.0046875 252.5053253 SF2D 0

0.004492188 457.0461731

0.004296875 63.99576187

0.004101563 804.342041

0.00390625 1104.436768

0.003710938 238.9017792

0.003515625 509.0552673

0.003320313 606.7443848

0.003125 296.3849182

0.002929688 938.7177124

0.002734375 668.4386597

0.002539063 805.7462769

0.00234375 487.1318054

0.002148438 159.5255127

0.001953125 350.0638123 PREAMP 0

0.001757813 932.3417358 TRIGGER 0

0.0015625 1205.988403 MATRIX 0

0.001367188 1292.137329 VER

0.001171875 1034.407227 XB0 0

0.000976563 1579.183472 YB0 0

0.00078125 1156.689453 ZB0 0

0.000585938 2448.749023 XOFFSET 0

0.000390625 3178.046631 YOFFSET 0

0.000195313 4778.706543 ZOFFSET 0

-0 5354.563477 D13 1

-0.000195313 6861.38623 D14 1

-0.000390625 10203.0752 D15 1

-0.000585938 12625.44238 D16 1

-0.00078125 14986.51465 D17 1

-0.000976563 17383.39844 D18 1

-0.001171875 20411.51367 D19 1

-0.001367188 23389.24023 D20 1

-0.0015625 26401.67773 D21 1

-0.001757813 28490.0957 D22 1

-0.001953125 32217.39844 D23 1

-0.002148438 35771.36719 D24 1

-0.00234375 40188.22656 D25 1

Appendices

176

-0.002539063 44372.60547 D26 1

-0.002734375 46932.16406 D27 1

-0.002929688 49850.41016 D28 1

-0.003125 51432.00781 D29 1

-0.003320313 52623.30078 D30 1

-0.003515625 54323.87109 D31 1

-0.003710938 54133.65234 D32 1

-0.00390625 55423.57422 C13 0

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-0.0046875 52664.49609 C17 0

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-0.007421875 54193.69531 C31 0

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-0.011132813 53867.96875 G27 0

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-0.01171875 53934.20703 G30 0

-0.011914063 54018.78516 G31 0

-0.012109375 54103.00391 G32 0

-0.012304688 53055.08594 ACQUISITION 3

-0.0125 53720.07813 RG1 0

-0.012695313 52913.59375 RG2 0

-0.012890625 52866.49219 RG3 0

Appendices

177

-0.013085938 52882.53516 RG4 0

-0.01328125 52445.50781 RG5 0

-0.013476563 52509.47266 RG6 0

-0.013671875 51982.69531 RG7 0

-0.013867188 52229.24609 RG8 0

-0.0140625 52443.86719 RG9 0

-0.014257813 51896.01563

-0.014453125 51390.45313

-0.014648438 51423.19531

-0.01484375 51531.4375 SH6

-0.015039063 50914.86719 SH7

-0.015234375 51152.53125 SH8

-0.015429688 50340.16797 SH9

-0.015625 50630.42969 SH10

-0.015820313 49852.1875 FP6 1

-0.016015625 50141.96484 FP7 1

-0.016210938 49351.76563 FP8 1

-0.01640625 49426.18359 FP9 1

-0.016601563 47901.70313 FP10 1

-0.016796875 47713.21094

-0.016992188 48119.74609 QCSHIM1 0

-0.0171875 46632.67188 QCSHIM2 0

-0.017382813 46327.55078 QCSHIM3 0

-0.017578125 46253.17578 QCSHIM4 0

-0.017773438 45186.98828 QCSHIM5 0

-0.01796875 44775.22656 QCSHIM6 0

-0.018164063 44419.78516 QCSHIM7 0

-0.018359375 43496.98047 QCSHIM8 0

-0.018554688 42409.6875 QCLEDS 0

-0.01875 41994.76563 QCVAR1 0

-0.018945313 41409.15234 QCVAR2 0

-0.019140625 40405.63281 QCVAR3 0

-0.019335938 39557.54688 QCVAR4 0

-0.01953125 39128.41016 QCVAR5 0

-0.019726563 38525.40625 QCVAR6 0

-0.019921875 37301.58984 QCVAR7 0

-0.020117188 36431.74609 QCVAR8 0

-0.0203125 35357.97656 QCVAR9 0

-0.020507813 34027.35938 QCVAR10 0

-0.020703125 32940.22656 QCVAR11 0

-0.020898438 31373.81445 QCVAR12 0

-0.02109375 31195.00781 QCVAR13 0

-0.021289063 29763.16602 QCVAR14 0

-0.021484375 28778.35938 QCVAR15 0

-0.021679688 27258.39844 QCVAR16 0

-0.021875 26537.80859 QCVAR17 0

-0.022070313 25192.63672 QCVAR18 0

-0.022265625 23943.50586 QCVAR19 0

-0.022460938 22603.57813 QCVAR20 0

-0.02265625 21495.38477

-0.022851563 20265.10938

-0.023046875 18813.36133

-0.023242188 17161.41797

-0.0234375 16217.45117

Appendices

178

-0.023632813 14893.75

-0.023828125 13373.7207

-0.024023438 12434.21191

-0.02421875 11603.54004

-0.024414063 10116.63086

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-0.025 7864.899902

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-0.028710938 1113.75061

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-0.033984375 183.5008392

Appendices

179

-0.034179688 288.9416504

-0.034375 635.0218506

-0.034570313 313.3622742

-0.034765625 393.3266296

-0.034960938 366.3001099

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-0.035742188 201.2223969

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-0.036132813 307.4041138

-0.036328125 282.476532

-0.036523438 250.1537018

-0.03671875 77.53498077

-0.036914063 207.5929718

-0.037109375 313.0016785

-0.037304688 431.5242004

-0.0375 92.57585144

-0.037695313 102.2893906

-0.037890625 63.34154892

-0.038085938 281.0473022

-0.03828125 177.0000458

-0.038476563 240.5339355

-0.038671875 461.6824646

-0.038867188 410.431427

-0.0390625 220.1817017

-0.039257813 394.8927917

-0.039453125 628.7907715

-0.039648438 432.1952515

-0.03984375 659.0006714

-0.040039063 533.9472656

-0.040234375 444.8866272

-0.040429688 728.8408203

-0.040625 143.0076141

-0.040820313 797.6348877

-0.041015625 270.8814087

-0.041210938 698.2357788

-0.04140625 180.1802216

-0.041601563 616.2109985

-0.041796875 194.5447083

-0.041992188 81.12782288

-0.0421875 77.44223022

-0.042382813 119.5436478

-0.042578125 426.4387817

-0.042773438 42.64378357

-0.04296875 770.3602905

-0.043164063 98.08128357

-0.043359375 251.3215179

-0.043554688 574.9602051

-0.04375 615.6561279

-0.043945313 168.6746368

-0.044140625 626.1096191

-0.044335938 451.0788879

-0.04453125 603.8342896

Appendices

180

-0.044726563 647.328186

-0.044921875 366.8519287

-0.045117188 345.2692261

-0.0453125 166.2787933

-0.045507813 117.9697495

-0.045703125 168.8075867

-0.045898438 446.1061707

-0.04609375 180.3927155

-0.046289063 206.8076782

-0.046484375 224.3544617

-0.046679688 179.0219421

-0.046875 366.4333801

-0.047070313 468.4237976

-0.047265625 368.434906

-0.047460938 224.0099335

-0.04765625 68.20970917

-0.047851563 390.3452454

-0.048046875 536.6691284

-0.048242188 349.6353149

-0.0484375 185.2005005

-0.048632813 467.0690308

-0.048828125 338.796875

-0.049023438 36.50217819

-0.04921875 329.5714722

-0.049414063 281.6910706

-0.049609375 639.5336914

-0.049804688 303.3779907

-0.05 365.1196594