eng470 engineering honours thesis final report · school of engineering and information technology...

SCHOOL OF ENGINEERING AND INFORMATION

TECHNOLOGY

ENG470 ENGINEERING

HONOURS THESIS FINAL

REPORT SEPARATION OF SOLVENT FROM

MICROALGAL HYDROCARBON USING

NANOFILTRATION

Reported by: King Zheng Lim

SUPERVISORS

PROFESSOR PARISA ARABZADEH BAHRI - PROFESSOR OF

ENGINEERING, SCHOOL OF ENGINEERING AND INFORMATION

TECHNOLOGY

DR. NAVID MOHEIMANI - SENIOR LECTURER

A report submitted to the School of Engineering and Energy, Murdoch University in partial fulfilment of the requirements for the unit ENG470 Engineering Honours Thesis.

0 | P a g e ENG 470 ENGINEERING HONOURS THESIS

Executive Summary

The need for searching an alternative technology to separate solvent efficiently

from the post-extraction process in the algae fuel production process has been long

researched for, and little to no convincing findings were found to rectify the current energy

crisis. This report aims to evaluate the viability of implementing nanofiltration technology

that could replace the use of a distillation column in the post-extraction process. Aspen

Plus was used to assess the thermodynamic feasibility of utilising chemical process unit

operations. This includes the following: investigation of the effect of thermodynamic

property methods to generate a more realistic separation process based on the nonideality

of the feed mixture, optimization of the simulation via sensitivity analysis, and an overall

energy balance to determine its sustainability based on the calorific value of the

hydrocarbon extracted from an algae culture. Nanofiltration experiments were carried out

to establish the applicability of the membrane purchased from Sterlitech and possibly fill a

current void in research for utilising the Duracid membrane in a heptane solution. The

experiments covered: the effect of different contact times with heptane, the effect of

pressure and feed concentration variance. A stirred cell was used to facilitate the

experiment, and several parameters were done to determine the characteristics of the

membrane, which included permeating de-ionised water, heptane, and squalene-heptane.

Results showed that prolonged contact times with heptane worsen the permeating

performance of the membrane over time, and a maximum of 6% rejection value was

attained when using Duracid membrane. Higher operating pressure and lower feed

concentration also enhanced the permeate flux. Possible explanation for such occurrence

includes the nanofiltration driving force, membrane polarity difference to the solvent, and

membrane swelling. Although GCMS showed a little rejection value for retaining squalene

in heptane solution, the finding is significant that could prove solvent separation via

nanofiltration is possible and future work is needed to improve the outcome. Alternative

separation technology and solvent resistant nanofiltration membrane had been proposed,

and that could serve as another starting point for an efficient separation process.


List of Nomenclature and Abbreviations

AP Aspen Plus

DC Distillation column

DI De-ionised

FS Flash separator

GCMS Gas chromatography mass spectrometry

kJ kilojoules

Lmh Litre/(m2.hour)

MRDF Molar ratio of distillate flow rate to feed flow rate

MWCO Molecular weight cut-off

NF Nanofiltration

NRTL Non-random two-liquid

PFD Process flow diagram

P&ID Piping and instrumentation diagram

RR Reflux ratio

SA Sensitivity analysis

SRNF Solvent resistant nanofiltration

TFC Thin film composite

UNIFAC Universal Quasichemical functional-group activity coefficients

% v/v Volume percentage

Applied pressure

Osmotic pressure


Table of Content

1 Introduction .................................................................................................................................................... 9

1.1 Background and industrial context .............................................................................................. 9

1.2 Study aims and objectives ............................................................................................................. 11

1.3 Thesis overview ................................................................................................................................ 12

2 Aspen Plus Modelling ............................................................................................................................... 13

2.1 Introduction ........................................................................................................................................ 13

2.2 Literature review .............................................................................................................................. 13

2.2.1 Thermodynamic property methods ................................................................................ 13

2.2.2 IDEAL method .......................................................................................................................... 13

2.2.3 Non-Random Two-Liquid (NRTL) model ..................................................................... 14

2.2.4 UNIFAC method ....................................................................................................................... 14

2.3 Documentation for AP modelling – Results and discussion ........................................... 15

2.3.1 Feed composition calculation ............................................................................................ 15

2.3.2 Preliminary model .................................................................................................................. 17

2.3.3 Effect of process thermodynamic property method ................................................ 18

2.3.4 SA on heptane recovery for the preliminary model ................................................. 20

2.3.5 Final model ................................................................................................................................ 24

2.3.6 SA on heptane recovery for the final model ................................................................ 27

2.3.7 Energy balance ......................................................................................................................... 30

2.3.8 Sensitivity of the simulation ............................................................................................... 33

3 Membrane separation process – Nanofiltration (NF) ................................................................. 35

3.1 Introduction ........................................................................................................................................ 35

3.2 Literature review .............................................................................................................................. 35

3.2.1 Solvent resistance nanofiltration (SRNF) ..................................................................... 36

3.2.2 Membrane filtration technique – Dead-end filtration ............................................. 38

3.2.3 Benefits of implementing SRNF ........................................................................................ 39

3.2.4 Influence of membrane property ..................................................................................... 40

3.3 Materials and methods ................................................................................................................... 44

3.3.1 Chemicals ................................................................................................................................... 44

3.3.2 Nanofiltration membrane .................................................................................................... 44


3.3.3 Filtration experiment set-up and procedure ............................................................... 45

3.3.4 HP4750 Stirred Cell assembly, maintenance and operation ................................ 47

3.3.5 Chemical analysis .................................................................................................................... 47

3.3.6 Membrane permeance analysis ........................................................................................ 47

3.4 Nanofiltration performance – Results and Discussion ..................................................... 49

3.4.1 Permeating DI water ............................................................................................................. 49

3.4.2 Permeating heptane ............................................................................................................... 51

3.4.3 Permeating a binary solution of squalene and heptane ......................................... 55

3.5 GCMS results ....................................................................................................................................... 60

3.5.1 Permeating squalene-heptane solution at 30 bar ..................................................... 60

3.5.2 Permeating squalene-heptane solution at 50 bar ..................................................... 62

3.6 Summary of the findings................................................................................................................ 65

4 Conclusion ..................................................................................................................................................... 66

4.1 Recommendations for future work ........................................................................................... 67

References .............................................................................................................................................................. 70

Appendixes ............................................................................................................................................................. 77

Appendix A: Feed Composition Calculations ................................................................................ 77

Appendix B: Aspen Plus Program Input Setups .......................................................................... 78

Appendix B.1: Input Entry for flash separator and distillation column in the

Initial Stage of Separation Process ................................................................................................ 78

Appendix B.2: Setting Change on Thermodynamic Property Method ....................... 80

Appendix B.3: Input Entry for Sensitivity Analysis on ‘FLASH’ Temperature ....... 81

Appendix B.4: Input Entry for Sensitivity Analysis on ‘RADFRAC’ Reflux Ratio

and Molar Ratio of Distillate to Feed Flow Rate ..................................................................... 82



Appendix C: HP4750 Stirred Cell Features and Specifications ........................................... 87

Appendix D: HP4750 Stirred Cell Components ........................................................................... 88

Appendix E: HP4750 Stirred Cell Assembly .................................................................................. 89

Appendix F: GC-MS Method Parameters .......................................................................................... 93


List of Figures

Figure 1: PDF and P&ID of the initial stage of solvent separation using flash separator

(‘FLASH’ model).................................................................................................................................................... 17

Figure 2: PDF and P&ID of the initial stage of solvent separation using RADFRAC distillation

column (‘RADFRAC’ model) ............................................................................................................................ 18

Figure 3: Heptane flow rate in top stream and squalane flow rate in bottom stream as a

function of ‘FLASH’ temperature (constant pressure 1 bar) ............................................................. 21

Figure 4: Heptane flow rate in top stream as a function of ‘RADFRAC’ reflux ratio (constant

molar ratio of distillate to feed flow rate at 0.5 and pressure at 1 bar) ........................................ 22

Figure 5: Heptane flow rate in top stream as a function of ‘RADFRAC’ MRDF (constant

reflux ratio of 1 and pressure at 1 bar) ....................................................................................................... 23

Figure 6: PDF and P&ID of the final stage of solvent separation using two flash separators

(‘FLASH’ model).................................................................................................................................................... 25

Figure 7: PDF and P&ID of the final stage of solvent separation using one distillation

column and one flash separator (‘RADFRAC’ model) ........................................................................... 26


function of ‘FLASH2’ temperature (‘FLASH’ model, constant pressure 1 bar)........................... 27


function of ‘FLASH’ temperature (‘RADFRAC’ model, constant pressure 1 bar)....................... 29


(‘FLASH’ model).................................................................................................................................................... 31


(‘RADFRAC’ model) ............................................................................................................................................. 31

Figure 12: Schematic view of TFC membrane (Marchetti et al. 2014) .......................................... 37

Figure 13: Molecular structure of PES, PA and PI ("Polyethersulfone Cas 25667-42-9 - RTP

Company" 2016; "Proteins" 2016; "Polyimides" 2016) ...................................................................... 38

Figure 14: Molecular structure of PDMS (Gilbert 2012) ..................................................................... 38

Figure 15: Configuration of dead-end filtration ...................................................................................... 39

Figure 16: Membrane swelling mechanism (Farid 2010) .................................................................. 42

Figure 17: Image of HP4750 Stirred Cell (Sterlitech 2015) ............................................................... 44

Figure 18: Diagram of experimental set-up .............................................................................................. 46

Figure 19: Scatter plot of cumulative permeate volume in DI water for Set 1 (Blue), Set 2

(Red) and Set 3 (Green) at 20 bar with its respective trend line and its R2 value .................... 49

Figure 20: Scatter plot of permeate flux in DI water for Set 1 (Blue), Set 2 (Red) and Set 3

(Green) at 20 bar .................................................................................................................................................. 50


Figure 21: Scatter plot of cumulative permeate volume in heptane for different soaking

times at 30 bar – Set 1 (30 min), Set 2 (60 minutes) and Set 3 (90 minutes) with its

respective trend line and its R2 value .......................................................................................................... 51

Figure 22: Scatter plot of permeate flux in heptane for different soaking times at 30 bar –

Set 1 (30 min), Set 2 (60 minutes) and Set 3 (90 minutes) ................................................................ 52

Figure 23: Scatter plot of permeate flux in heptane for different soaking times at 30 bar ... 54

Figure 24: Scatter plot of cumulative permeate volume for different squalene

concentrations at 30 bar ................................................................................................................................... 56

Figure 25: Scatter plot of permeate flux for different squalene concentrations at 30 bar .... 57

Figure 26: Scatter plot of cumulative permeate volume for different squalene

concentrations at 50 bar ................................................................................................................................... 59

Figure 27: Scatter plot of permeate flux for different squalene concentrations at 50 bar .... 59

Figure 28: Scatter plot of GCMS results for different squalene concentration at 30 bar ....... 61

Figure 29: Scatter plot of GCMS results for different squalene concentration at 50 bar ....... 62

Figure 30: A spreadsheet of feed composition calculation ................................................................. 77

Figure 31: Input requirements for ‘FLASH’ column under Specification tab ............................. 78

Figure 32: Input requirement for ‘RADFRAC’ column under Configuration tab ....................... 78

Figure 33: Feed and component input requirement for ‘RADFRAC’ column under Feed

Basis .......................................................................................................................................................................... 79

Figure 34: Input requirement for ‘RADFRAC’ column under Streams tab................................... 79

Figure 35: Setting Change on Thermodynamic Property .................................................................... 80

Figure 36: Sensitivity analysis input requirement for flash separator temperature in

‘FLASH’ model ....................................................................................................................................................... 81

Figure 37: Variable definition and input requirement for flash separator sensitivity analysis

outputs in ‘FLASH’ model ................................................................................................................................. 81

Figure 38: Sensitivity analysis input requirement for ‘RADFRAC’ reflux ratio .......................... 82

Figure 39: Variable definition and input requirement for ‘’RADFRAC’ sensitivity analysis

outputs ..................................................................................................................................................................... 82

Figure 40: Sensitivity analysis input requirement for ‘RADFRAC’ MRDF .................................... 83

Figure 41: Variable definition and input requirement for ‘’RADFRAC’ sensitivity analysis

outputs ..................................................................................................................................................................... 83

Figure 42: Sensitivity analysis Input requirement for 'FLASH2' reactor temperature in

‘FLASH’ model ....................................................................................................................................................... 84

Figure 43: Variable definition and input requirement for ‘FLASH2’ tank sensitivity analysis

outputs in ‘FLASH’ model ................................................................................................................................. 84

Figure 44: Sensitivity analysis Input requirement for 'FLASH2' reactor temperature in

‘’RADFRAC’ model................................................................................................................................................ 85


Figure 45: : Variable definition and input requirement for ‘FLASH2’ tank sensitivity

analysis outputs in ‘’RADFRAC’ model ........................................................................................................ 85

Figure 46: Input requirements for stream ‘1SQUAL’ for water content variable ..................... 86

Figure 30: HP4750 parts and components (Sterlitech Corp 2015) ................................................ 88

Figure 31: Outer O-ring (left) and inner O-ring (right) insertion .................................................... 89

Figure 32: Membrane (left) and porous membrane support disk (right) insertion ................ 89

Figure 33: Cell Bottom fitting (left) and high pressure coupling assembly (right) .................. 89

Figure 34: Permeate Tube assembly (left) and Stir Bar insertion (right) .................................... 90

Figure 35: Gasket assembly (left), Cell Top installation (middle) and high pressure

assembly (right) ................................................................................................................................................... 90

Figure 36: High pressure hose attachment (left) and pressure regulator connection (right)

..................................................................................................................................................................................... 90

Figure 37: HP4750 System Configuration (Sterlitech 2015) ............................................................. 92

List of Tables

Table 1: Stream table for the initial separation process with ‘FLASH’ model under NRTL

method ..................................................................................................................................................................... 19

Table 2: Stream table for the initial separation process with ‘FLASH’ separator under

UNIFAC method .................................................................................................................................................... 19

Table 3: Stream table for the initial separation process with ‘RADFRAC’ column under

IDEAL, NRTL and UNIFAC method ............................................................................................................... 20

Table 4: Stream table for the initial separation process with ‘RADFRAC’ column (Reflux

ratio = 1, MRDF = 0.99) ..................................................................................................................................... 24

Table 5: Stream table for the final stage separation process using two flash separators

(‘FLASH’ model).................................................................................................................................................... 25

Table 6: Stream table for the final stage separation process using one distillation column

and one flash separator (‘RADFRAC’ model) ........................................................................................... 26

Table 7: Stream table for the final stage separation process using two flash separators after

sensitivity analysis (‘FLASH’ model) ........................................................................................................... 28

Table 8: Stream table for the final stage separation process using two flash separators after

sensitivity analysis (‘RADFRAC’ model) ..................................................................................................... 30

Table 9: Heptane, squalane recovery and overall heat duty as a function of water being

introduced in the feed stream (‘FLASH’ model)...................................................................................... 33

Table 10: Heptane, squalane recovery and overall heat duty as a function of water being

introduced in the feed stream (‘RADFRAC’ model) ............................................................................... 33

Table 11: Physico-chemical properties of n-heptane and squalene ............................................... 44


Table 12: Technical specifications for GE Osmonics Duracid NF membrane (Sterlitech

2015) ......................................................................................................................................................................... 45

Table 13: List of equipment and method condition used for GCMS ............................................... 47

Table 14: Physical properties of solvents used (Engineeringtoolbox 2016) .............................. 53

Table 15: Comparison of total permeate volume with respect to operating pressure ........... 59

Table 16: Summary of the nanofiltration process outcome operating at 30 bar ...................... 61

Table 17: Summary of the nanofiltration process outcome operating at 50 bar ...................... 63

Table 18: Different Solvent Resistant Nanofiltration and Their Properties Provided by its

Respective Manufacturers (Othman et al 2009; Sterlitech 2015; Evonik 2015). ..................... 67

Table 19: HP4750 Features and Technical Specifications (Sterlitech 2015) .............................. 87

Table 20: GC-2010 Gas Chromatograph parameters ............................................................................ 93

Table 21: MS Mass Spectrometer parameters ......................................................................................... 93

Table 22: GCMS-QP2010 Gas Chromatograph-Mass Spectrometer parameters ....................... 94

Table 23: AOC-20i/S Auto Injector and Auto Sampler parameters ................................................ 94

List of Equations

Equation 1: Expression of calorific value determination .................................................................... 32

Equation 2: Expression of nanofiltration driving force ....................................................................... 35

Equation 3: Volume percentage determination ...................................................................................... 46

Equation 4: Expression of permeate flux ................................................................................................... 48

Equation 5: Expression of rejection value ................................................................................................. 48

Equation 6: Van’t Hoff’s first equation of osmotic pressure relating to solute concentration

..................................................................................................................................................................................... 58

Equation 7: Expression of driving force with effect to concentration ........................................... 58

Equation 8: Expression of driving force with effect to applied pressure ..................................... 60


Acknowledgments

I would like to acknowledge the support given to me by my supervisors, Professor

Parisa Bahri, and Dr. Navid Moheimani, who have provided me a chance to take this thesis

project. In spite of having busy schedules throughout the semesters, both have offered me a

considerable amount of time, kindness, and encouragement for the duration of this project

at Murdoch University. This work would not be possible without their support and

guidance throughout the course of this thesis project.

I would like to thank Dr. Linda Li for her equipment setup, as well as her time to

provide me advice. I would also like to thank Mr. Andrew Foreman, who has provided me

constant help with the chemical and experimental aspects of the project. Without their

help, this thesis would not be a success.

Thank you to my colleagues from Algae R&D Centre at Murdoch University for your

encouragement and for sharing your invaluable experience and knowledge to help me

through this journey.

Last but not least, to my friends, my special ones and family, thank you for being

understanding throughout this year with constant motivation and providing me emotional

support whenever I needed.


1 Introduction

1.1 Background and industrial context

With the demand for energy ever increasing, both regionally and nationally, there

is a continued and vital emphasis to search for alternative sources of such energy. It is, in

fact, crucial to serving the essential needs for all daily application, as nowadays the society

places a continued strain on scarce resources (McKendry 2002; Rosato, Sibilio and Ciampi

2013). As a matter of fact, in view of climate change and the ever-limiting resource such as

fossil fuels, it has become apparent that the use of sustainable biomass for materials and

energy production are becoming increasingly imperative. In fact, it has been found that

fossil fuel reserves are gradually decreasing, and it is anticipated that they will be

completely exhausted in the near future, raising concerns for energy security

(Bart, Palmeri and Cavallaro 2010). According to the Key World Energy Statistics compiled

by International Energy Agency (IEA) (2015), the world’s electrical energy generation by

fuel spanning from 1971 to 2012 had increased by almost four folds due to

industrialization, globalisation and concerns over energy security.

Upon reviewing several alternative energy sources, oil production from microalgae,

especially biodiesel, is perceived to be one of the most attractive renewable sources

researchers have come across (McKendry 2002; Borowitzka and Moheimani 2010), as

opposed to the ever limiting, non-renewable resources, fossil fuel. Many studies have

claimed that microalgae have the potential to be the future biotechnological oil production

as they utilise light more efficiently than higher plants to build carbon-based molecules,

such as lipids or oils (Borowitzka and Moheimani 2010). Algae oil production plant does

not require using arable land for agriculture because algae can grow in a harsh

environment such as hypersaline water source (Fon Sing et al. 2011). Thus, this provides a

solution for both food and energy crisis.

In a conventional algae oil production, a separation technology must be

implemented to separate and purify the product, recover and recycle compounds, and

separate contaminants from effluent before discharging. A recent study on


commercialising algae oil production revealed that it required a tremendous amount of

energy input in the downstream processing, particularly in the harvesting stage and the

extracting stage, which was very costly (Moheimani et al. 2011). The conventional algae oil

extraction process, which utilises a distillation column to separate the solvent from the

aqueous mixture, is also energetically unfeasible (Moheimani et al. 2011; Chaudry, Bahri

and Moheimani 2015). This is because distillation uses almost as much as 49% of the

industry’s overall energy consumption and as high as 95% of separation energy

(Oak Ridge National Laboratory 2005). Hence, distillation is thought to be an inefficient

separating process.

Another hurdle in realising conventional algae fuel production from cultured algae

is efficient harvesting of the algal cells (Aiche 2015). During this phase, cultured algae are

‘dewatered’ or killed to extract the oil from the culture, and a large amount of water must

be processed already having a concentrated algal biomass (Aiche 2015). According to

recent biological studies, an improved algal oil (or hydrocarbon) extraction process has

been proposed and it utilises the concept of liquid-liquid extraction. This is a transfer of

one solute in a feed solution to another immiscible solvent. Such a concept has been

termed as ‘non-destructive’ extraction or ‘milking’ in the recent studies, and it shows a

promising result of efficiently extracting microalgal hydrocarbon without inputting any

extra energy (Frenz, Largeau and Casadevall 1989). Unlike the conventional algae oil

production, where killing the algae and re-cultivating a new batch of algae culture is

necessary, the milking process re-uses the same algae culture over as many times as

possible. The milking process can be done by continuously extracting the algal oil from the

same culture using a biocompatible solvent, such as heptane or dodecane, without

sacrificing the cells (Moheimani et al. 2013). Such a harvesting method not only does it not

require any extra fertilisers but it also does not affect the algae culture growth and

hydrocarbon production throughout repeated milking process (Frenz, Largeau and

Casadevall 1989). The microalgal hydrocarbon, called botryococcenes, produced by a green

microalga Botryococcus braunii (Race B) or BOT-22 was particularly focused in this study.


1.2 Study aims and objectives

The sole aim of this thesis was to investigate an alternative technology of solvent

separation by implementing nanofiltration (NF), in particular, solvent resistant

nanofiltration (SRNF). This method was anticipated to overcome drawbacks of current

techniques of utilising distillation column (DC) for separating organic solvent from a

commercial scale of algae fuel production process. This study also investigated the

effectiveness of solvent recovery using chemical process unit operations to determine its

feasibility from the calculated energy profile. Several objectives had been proposed and

were set to be achieved throughout this thesis work.

1. Design a separation process that separates a mixture of algal hydrocarbon and

heptane solution using Aspen Plus (AP),

2. Optimise the separation process developed in AP using different thermodynamic

property methods and carry out a sensitivity analysis on AP,

3. Develop simple energy balance based on the separation process developed,

4. Investigate the effect of organic solvent on the membrane used for NF experiment

such as solvent contact time,

5. Identify the effect of pressure and concentration change on the NF experiment,

6. Diagnose the issues found from the NF experiments and determine the applicability

of utilising the membrane purchased.

By bringing together and analysing NF membrane testing and comparison with the

conventional DC regarding its energy requirement, this report aims to provide a clear,

quantitative view of the efficiency and its solvent recovery rate from using a commercial

nanofilter. The conducted results will not only fill a current void in research by providing

new innovative ways of separating solvent, but it potentially also reduce the energy

requirement significantly for the refinery stage.


1.3 Thesis overview

The structure of this study is as follows:

Chapter 2: Covers the modelling aspects of the separation process, which includes:

I. Literature review on thermodynamic property methods used for

simulation calculations,

II. Evaluation of the modelling criteria and designs,

III. Methodology and design documentation of the model and simulation

evaluation,

IV. Energy balance of the separation process.

Chapter 3: Covers the nanofiltration aspects of the separation process, which includes:

I. Literature review on NF applications, its benefits and factors

influencing the performance of NF process,

II. The methodology that had been followed including materials and

equipment used,

III. The relationship of the permeate flux profile against different operation

conditions such as pressure and concentration,

IV. Evaluation of the chemical analysis for the nanofiltration experiments

using GCMS and the characteristics of the membrane purchased.

Chapter 4: Summary of the findings that were conducted and the issues that were

diagnosed with possible strategies that could be implemented, which

included:

I. Other remedial recommendations that could be useful for further

research,

II. Alternative nanofiltration membrane for the organic solvent separation,

III. Alternative separation technology utilised in both laboratory scale and

commercial scale.


2 Aspen Plus Modelling

2.1 Introduction

To analysis the separation process in a commercial plant, a chemical process

optimisation computer software package named Aspen Plus (AP) was used. Such

simulation was necessary as it aided in investigating the effect of changes that could be

imposed on the separation process by using various unit operators, as well as determining

the correctness and efficiency of the separation process before the system is constructed.

As a result, it allows users to explore the merits of alternative designs without physically

building the systems and significantly diminishes the overall cost of building.

Furthermore, by comparing the energy requirement for the separation process to that of

the nanofiltration separation, it could provide users with practical feedback when

designing the separation process. Literature review on the use of different thermodynamic

property methods employed in AP was conducted to understand its functionality better for

the purpose of this modelling.

2.2 Literature review

2.2.1 Thermodynamic property methods

To investigate the significance change due to implementing different calculation

methods, three thermodynamic property methods, namely, IDEAL, NRTL, and UNIFAC, was

considered to predict the performance of the process.

2.2.2 IDEAL method

IDEAL method is a system composed of ideal gases and liquids that obey the ideal

gas law . The activity coefficient for the ideal liquid phase in this method is

set to be 1 (Hussain 2016). It is noted that the activity coefficient is a factor used in

thermodynamics to measure the non-ideality of a mixture of chemical substances. In an

ideal condition, chemical interaction such as the polarity of liquid involved is assumed to


be negligible when the liquid phase consists of a mixture of molecules of similar size and

character. However, such assumption could cause the system outcomes to be inaccurate

because different material interacts differently to other materials, for example,

water/alcohol mixtures (Husssain 2016).

2.2.3 Non-Random Two-Liquid (NRTL) model

The Non-Random Two-Liquid model is an activity coefficient model, in which the

activity coefficient of a compound i is correlated with its mole fractions in the

concerning liquid phase (Renon and Prausnitz 1968). NRTL model has been commonly

applied in the chemical engineering field to calculate phase equilibria due to its reliability

on application to partially miscible in addition to completely miscible systems (Renon and

Prausnitz 1968). Consequently, NRTL often provides a good representation of

experimental data for non-ideal mixtures or partially miscible systems.

2.2.4 UNIFAC method

“The UNIFAC method (Universal Quasichemical Functional-group Activity

Coefficients) is a semi-empirical system for the prediction of non-electrolyte activity in

non-ideal mixtures,” as defined by Fredenslund, Jones, and Prausnitz (1975). To calculate

activity coefficients, UNIFAC uses the functional groups existing on the molecules that

make up the liquid mixture. By utilising interactions for each of the functional groups

present on the molecules, as well as some binary interaction coefficients, the activity of

each of the solutions can be determined (Fredenslund, Jones and Prausnitz 1975).

Nowadays, due to its application to a wide variety of non-electrolyte liquid mixtures

containing polar or non-polar liquids, this method is frequently applied for phase equilibria

in many thermodynamic calculations, such as chemical reactor design, and distillation

calculations (Abrams and Prausnitz 1975).


2.3 Documentation for AP modelling – Results and discussion

To prove solvent separation using DC is energetically intensive, an AP modelling

was used to determine the energy required for a separation system that involves heptane

and squalene. The model should be simulated as close as possible to the post-extraction

process in a typical algae fuel production, where heptane, a biocompatible organic solvent

was used to dissolve the algal hydrocarbon, botryococcenes.

This simulation aims to design, model and optimise a separation process that

separates a mixture of algal hydrocarbon and heptane solution into two separate streams.

To achieve the desired separation and address the explicit goals for the simulation, a list of

design criteria and parameters was developed and explored. This included:

1. Identify feed media composition that was to be separated,

2. Investigate the influence of different thermodynamic property methods on AP,

3. Explore the use of different process unit operations for the separation process,

4. Optimise the separation process using sensitivity analysis (SA),

5. Minimise the heat duty done by the implemented process unit operators,

6. Achieve a minimum of 99.98% solvent and hydrocarbon recovery,

7. Operate all the unit operators slightly less than the atmospheric pressure (1 bar).

2.3.1 Feed composition calculation

Before developing the simulation, a preliminary calculation to determine the feed

composition was carried out because a variance in mass fraction could cause a dramatic

change in the simulation outcome. This stimulation was necessary because it could

represent a real world system as close as possible to verify its feasibility and produce a

more realistic outcome. The calculation was done based on the findings made by

Moheimani et al. (2013), using dry weight (DW) of B.braunii BOT-22 wet cultures and its

total oil content as a starting point. Combined with Schnurr, Espie and Allen’s finding

(2013), who found that the biomass content of liquid cultures is between 0.02% and 0.06%

total solids, it was calculated that the mass fractions of hydrocarbon in BOT-22 and


heptane were 0.001 and 0.999, respectively, based on 1L of BOT-22 culture at its stationary

phase. The results of these calculations can be found in Appendix A.

Calculating the algae cell, water and hydrocarbon content could be difficult as the

moisture content at different algae growth stage varies over time. Hence, rather than

complicating the calculations by considering the water content in the algae culture, it could

be assumed that during the milking procedure, the aqueous phase that contains B. braunii

and the media, which comprises of water and the trace minerals, shall be removed

altogether, or at least 99.9% of water could be withdrawn. This simplifies the modelling

process and allows a simple binary solution of botrococcenes and heptane being separated

in the simulation. Also, for the simplicity of the simulation, it was assumed that all the

botryococcenes produced by BOT-22 in the liquid culture were squalene, rather than

considering the trace compounds found in botryococcenes.

Due to the structural similarity of botryococcenes to squalene, plus, rather than

using the actual algal hydrocarbon for modelling, it was assumed that squalene should be

utilised for the simulation. However, since AP does not have the component squalene on

the software database and limited thermodynamic properties of squalene were found

within the literature, squalane had been used instead for the ‘Component’ inputs. Although

such assumption could potentially pose an inaccuracy in the stimulation due to their

difference in thermodynamic properties, it sufficed for the purpose of this estimation. It is

also worth mentioned that the boiling point for squalene and squalane is 421.3 °C and

470.3 °C, respectively, where the difference is 49.0 °C (Haynes 2014; Lookchem 2016).

Because of such small difference in boiling point and the fact that heptane has relatively

low boiling (98.38 °C) when compared to both squalene and squalane, it seemed like a

good idea for such simulation to be carried out on the hypothetical separation process.


2.3.2 Preliminary model

Using the information extracted from the literature review, combined with the

preliminary calculations done in the previous section, two AP models was developed to

explore the use of different process unit operations for the separation process. One model

utilised a flash separator (FS) unit of type ‘Flash2’, labelled as ‘FLASH’ model, while the

other used a DC of type ‘Radfrac’, labelled as ‘RADFRAC’ model.

Initially, a stream of 0.1 kg/hr squalene, labelled as ‘FEED’, was mixed with a

stream of 99.9 kg/hr pure heptane, labelled as ‘HEPTANE’, to make up a product stream of

100 kg/hr as feed basis. The operational condition of the input streams before the mixer

was set at 25 °C and 1 bar. Subsequently, the product stream was charged to one FS and

one DC separately. The process unit operations were set up as shown in the Process Flow

Diagram (PFD) and its Piping and Instrumentation Diagram (P&ID) shown below, Figure 1

and Figure 2. It is noted that the number in each of the hexagon box represents the

pressure for each stream, and the unit of pressure is in ‘atm’.

Figure 1: PDF and P&ID of the initial stage of solvent separation using flash separator (‘FLASH’ model)

FLASH1

MIXER1 1

3MIX

1

4TOP

1

5BOTTOM

1

1FEED 1

2HEPTANE


Figure 2: PDF and P&ID of the initial stage of solvent separation using RADFRAC distillation column (‘RADFRAC’ model)

The figure above graphically displays the preliminary stage of the separation, and

no SA has been taken place yet. In this initial model, the operational parameters for ‘FLASH’

were set at 100 °C and 1 bar. Block ‘RADFRAC’ required more inputs than that of FS, so at

this stage, ‘RADFRAC’ was operated at 1 bar with a molar ratio of distillate flow rate to feed

flow rate (MRDF) at 0.5 and its reflux ratio (RR) at 1. The input requirements for ‘FLASH’

and ‘RADFRAC’ are provided in Appendix B.1.

2.3.3 Effect of process thermodynamic property method

As mentioned previously, several simulation tests was undertaken to achieve the

desired solvent recovery; this included simulations under the influence of different

thermodynamic property methods such as IDEAL, UNIFAC and NRTL. Their significant

impacts under these property methods, highlighted in tables, were then compared based

on the output streams composition yielded from different unit operators. As each method

was explored, their individual settings were recorded in Appendix B.2 for easy reference.

First, IDEAL method was established and implemented to both ‘FLASH’ and

‘RADFRAC’ models. Upon investigation, it was found that little to no changes in the

separation process were observed in both models. The only significant difference found

was for the ‘FLASH’ model; while the ‘RADFRAC’ model did not show any difference

MIXER1

RADFRAC

3MIX

4TOP

5BOTTOM

1FEED

2HEPTANE


Sample Test Stream ID 1FEED 2HEPTANE 3MIX 4TOP 5BOTTOM Temperature C 25.0 25.0 25.0 100.0 100.0 Pressure atm 0.987 0.987 0.987 0.987 0.987 Vapor Frac 0.000 0.000 0.000 1.000 0.000 Mole Flow kmol/hr < 0.001 0.997 0.997 0.993 0.004 Mass Flow kg/hr 0.100 99.900 100.000 99.517 0.483 Volume Flow cum/hr < 0.001 0.146 0.147 30.812 0.001 Enthalpy Gcal/hr > -0.001 -0.053 -0.053 -0.041 > -0.001 Mass Flow kg/hr

WATER

HEPTANE

99.900 99.900 99.517 0.383

SQUAL-01 0.100

0.100 < 0.001 0.100 Mass Frac

WATER

HEPTANE

1.000 0.999 1.000 0.793 SQUAL-01 1.000

0.001 176 PPB 0.207

Mole Flow kmol/hr

WATER

HEPTANE

0.997 0.997 0.993 0.004 SQUAL-01 < 0.001

< 0.001 trace < 0.001

Sample Test Stream ID 1FEED 2HEPTANE 3MIX 4TOP 5BOTTOM Temperature C 25.0 25.0 25.0 100.0 100.0 Pressure atm 0.987 0.987 0.987 0.987 0.987 Vapor Frac 0.000 0.000 0.000 1.000 0.000 Mole Flow kmol/hr < 0.001 0.997 0.997 0.992 0.005 Mass Flow kg/hr 0.100 99.900 100.000 99.432 0.568 Volume Flow cum/hr < 0.001 0.146 0.147 29.683 0.001 Enthalpy Gcal/hr > -0.001 -0.053 -0.053 -0.041 > -0.001 Mass Flow kg/hr WATER

HEPTANE

99.900 99.900 99.432 0.468

SQUAL-01 0.100

0.100 trace 0.100 Mass Frac

WATER

HEPTANE

1.000 0.999 1.000 0.824 SQUAL-01 1.000 0.001 55 PPB 0.176 Mole Flow kmol/hr

WATER

HEPTANE

0.997 0.997 0.992 0.005 SQUAL-01 < 0.001

< 0.001 trace < 0.001

regarding stream composition regardless of the thermodynamic property changes. Table 1

and Table 2 show the stream table generated from using NRTL and UNIFAC methods on

the ‘FLASH’ model, respectively, and Table 3 lists the results for the ‘RADFRAC’ model

using all the property methods.

Table 1: Stream table for the initial separation process with ‘FLASH’ model under NRTL method

Table 2: Stream table for the initial separation process with ‘FLASH’ separator under UNIFAC method


Table 3: Stream table for the initial separation process with ‘RADFRAC’ column under IDEAL, NRTL and UNIFAC method

From Table 1 and Table 2, it can be seen that the change in heptane composition in

‘5BOTTOM’ stream was insignificant, only amounting a difference of 0.085 kg/hr mass flow

and 3.1% difference in the mass fraction, as highlighted in blue and red box respectively.

This suggested that the activity coefficient of the mixture (heptane and squalane) did not

vary much when comparing different thermodynamic property outcome. From Table 3, as

mentioned, the change in thermodynamic property did not influence the change in heptane

composition; however, it was noted that the heptane composition was split equally into

both ‘4TOP’ and ‘5BOTTOM’ streams, as indicated in red box shown in Table 3.

Having said that, for a realistic simulation, UNIFAC was chosen for the entirety of

this simulation because this method takes account for the polarity of the liquid mixture and

it has been used regularly in separation process (Fredenslund, Jones and Prausnitz 1975).

2.3.4 SA on heptane recovery for the preliminary model

With the process set up by the given PFD and P&ID shown in Figure 1 and Figure 2,

both ‘FLASH’ and ‘RADFRAC’ model yielded nearly 100% of squalane separation from the

mixed stream ‘3MIX’, only with an exception of some heptane still contained in the output

Sample Tes t

Stream ID 1FEED 2HEPTANE 3MIX 4TOP 5BOTTOM

Temperature C 25.0 25.0 25.0 98.0 98.0

Pressure atm 0.987 0.987 0.987 0.987 0.987

Vapor Frac 0.000 0.000 0.000 1.000 0.000

Mole Flow kmol/hr < 0.001 0.997 0.997 0.498 0.499

Mas s Flow kg/hr 0.100 99.900 100.000 49.950 50.050

Volume Flow cum/hr < 0.001 0.146 0.147 15.381 0.081

Enthalpy Gcal/hr > -0.001 -0.053 -0.053 -0.021 -0.025

Mas s Flow kg/hr

WATER

HEPTANE 99.900 99.900 49.950 49.950

SQUAL-01 0.100 0.100 trace 0.100

Mas s Frac

WATER

HEPTANE 1.000 0.999 1.000 0.998

SQUAL-01 1.000 0.001 trace 0.002

Mole Flow kmol/hr

WATER

HEPTANE 0.997 0.997 0.498 0.498

SQUAL-01 < 0.001 < 0.001 trace < 0.001


stream ‘5BOTTOM’. ‘FLASH’ model yielded a significant heptane separation, which

accounted for about 99.53% heptane separation from stream ‘3MIX’ using UNIFAC method;

while ‘RADFRAC’ model yielded 50% heptane separation under the operational parameter

shown in Appendix B.2. Therefore, to optimise the solvent separation up to a recovery of

99.98%, SA had been carried out.

2.3.4.1 ‘FLASH’ model

To determine the optimum temperature for ‘FLASH’, SA was implemented under

the label of ‘TEMPF1’ created in ‘Model Analysis Tools’ (Appendix B.3). The SA performed

for the flash pressure was held to be constant, and the reactor temperature was varied

from 90 °C to 160 °C. The responding variables, heptane flow rate in the top stream ‘4TOP’,

labelled as ‘TOPHEPT’, and squalane flow rate in the bottom stream ‘5BOTTOM’, labelled as

‘BOTSQUAL', was monitored to determine the optimum reactor temperature, and shown in

Figure 3. Note that the feed basis for both heptane and squalane in the mixed stream was

99.9 kg/hr and 0.1 kg/hr, respectively.

Figure 3: Heptane flow rate in top stream and squalane flow rate in bottom stream as a function of ‘FLASH’ temperature (constant pressure 1 bar)

Sensitivity Results Curve

VARY 1 FLASH1 PARAM TEMPC

BO

TSQ

UA

L K

G/H

R

TO

PH

EP

T K

G/H

R

90 95 100 105 110 115 120 125 130 135 140 145 150 155 1600.072

0.074

0.076

0.078

0.080

0.082

0.084

0.086

0.088

0.090

0.092

0.094

0.096

0.098

0.100

0

10

20

30

40

50

60

70

80

90

100

TOPHEPT KG/HR

BOTSQUAL KG/HR


As can be seen in Figure 3, initially, there was no heptane detected in the top

stream until there was a sharp increase in flow rate after the flash temperature reached

96 °C. Heptane flow rate reached a steady flow rate of 99.9 kg/hr at a temperature of

100 °C and squalane did not vaporise into the top stream before reaching a temperature of

100 °C (indicated by the dashed line). Therefore, no further changes had been

implemented as the process was at its optimum condition. This condition will be used for

further modelling.

2.3.4.2 ‘RADFRAC’ model

Similar to optimising ‘FLASH’ temperature, two parameters, RR and its MRDF were

used for SA to optimise heptane separation. A ‘Model Analysis Tools’ under the label of ‘RR’

was created and the input requirements can be referred as Appendix B.4. In this test, MRDF

was held constant at 0.5 and the column temperature at 1 bar. Heptane flow rate in the top

stream ‘4TOP’, labelled as ‘TOPHEPT’, was monitored in accordance with the changing

reflux ratio from ‘RADFRAC’ column, while RR varied from 0.5 to 5. Figure 4 shows the

graph of the SA.

Figure 4: Heptane flow rate in top stream as a function of ‘RADFRAC’ reflux ratio (constant molar ratio of distillate to feed flow rate at 0.5 and pressure at 1 bar)


VARY 1 RADFRAC COL-SPEC MOLE-RR

TO

PH

EP

T K

G/H

R

0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.048.0

48.5

49.0

49.5

50.0

50.5

51.0

51.5

52.0

TOPHEPT KG/HR


From the graph above, it was clear that the RR for ‘RADFRAC’ column did not affect

the phase equilibrium for the separation process. The reason for such occurrence was not

clear except for the fact that MRDF was held constant at 0.5. However, it was believed that

the amount of squalane presented in the mixed stream was too dilute to pose any effect to

the heptane separation. As a result, RR was set to 1.0 for the course of the simulation.

Next, a ‘Model Analysis Tools’ under the label of ‘MR’ was created for the MRDF

(Appendix B.4). In this test, MRDF was manipulated from 0.10 to 0.99, and the heptane

flow rate in the top stream ‘4TOP’, labelled as ‘TOPHEPT’, was recorded. Figure 5 shows

the graph of the SA.

Figure 5: Heptane flow rate in top stream as a function of ‘RADFRAC’ MRDF (constant reflux ratio of 1 and pressure at 1 bar)

SA shows that as MRDF increased, the amount of heptane flow in the top stream

increased accordingly. This was expected because the molar ratio determines the desired

amount of light key component to being recovered. Since heptane was chosen to be the

light key component, the higher the MRDF, the greater the amount will be recovered.

Hence, the value of 0.99 was chosen for the MRDF in this simulation.


VARY 1 RADFRAC COL-SPEC D:F

TO

PH

EP

T K

G/H

R

0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.60 0.65 0.70 0.75 0.80 0.85 0.90 0.95 1.000

5

10

15

20

25

30

35

40

45

50

55

60

65

70

75

80

85

90

95

100

TOPHEPT KG/HR


With the new MRDF being implemented and RR of 1, a stream table was produced,

Table 4. Now the amount of heptane in the bottom stream had been significantly reduced

by a factor of 50 when the MDRF was set at 0.99 while maintained a 100% squalane

separation from the mixed stream (indicated as the red box).

Table 4: Stream table for the initial separation process with ‘RADFRAC’ column (Reflux ratio = 1, MRDF = 0.99)

2.3.5 Final model

Having optimised the preliminary models for using ‘FLASH’ tank and ‘RADFRAC’

column, there was still some small amount of heptane left in the bottom stream, which

amounted to 99.53% and 99.0% heptane recovery from the mixed stream in the ‘FLASH’

and the ‘RADFRAC’ model, respectively. Upon reviewing the possible combination of

implementing different unit operators for a better solvent recovery, an addition of type

‘Flash2’ FS was applied to both models. The bottom stream in both models was connected

as the feed stream to the newly added FS. Another mixer was added to both models to

combine the two top streams, ‘4TOP’ and ‘6TOP’ from each FS and the DC, and the mixed

stream was labelled as ‘8HEPTANE’. The bottom stream from the second FS will only

contain squalane, hence the label ‘7SQUAL’. The new PFD and its P&ID is as shown in

Sample Test

Stream ID 1SQUAL 2HEPTANE 3MIX 4TOP 5BOTTOM

Temperature C 25.0 25.0 25.0 98.0 98.9

Pressure atm 0.987 0.987 0.987 0.987 0.987

Vapor Frac 0.000 0.000 0.000 1.000 0.000

Mole Flow kmol/hr < 0.001 0.997 0.997 0.987 0.010

Mass Flow kg/hr 0.100 99.900 100.000 98.901 1.099

Volume Flow cum/hr < 0.001 0.146 0.147 29.345 0.002

Enthalpy Gcal/hr > -0.001 -0.053 -0.053 -0.041 -0.001

Mass Flow kg/hr

WATER

HEPTANE 99.900 99.900 98.901 0.999

SQUAL-01 0.100 0.100 trace 0.100

Mass Frac

WATER

HEPTANE 1.000 0.999 1.000 0.909

SQUAL-01 1.000 0.001 trace 0.091

Mole Flow kmol/hr

WATER

HEPTANE 0.997 0.997 0.987 0.010

SQUAL-01 < 0.001 < 0.001 trace < 0.001


Figure 6 and Figure 7. In this final model, the additional FS for both ‘FLASH’ and ‘RADFRAC’

model, labelled as ‘FLASH2’ and ‘FLASH’, respectively, were set at 100 °C and 1 bar.

Before optimising operational parameter such as the reactor temperature, the

models were re-initialised, re-ran, and stream tables were generated in the following

tables, Table 5 and Table 6 for ‘FLASH’ model and ‘RADFRAC’ model, respectively.

Figure 6: PDF and P&ID of the final stage of solvent separation using two flash separators (‘FLASH’ model)

Table 5: Stream table for the final stage separation process using two flash separators (‘FLASH’ model)

FLASH1

MIXER1

FLASH2

MIXER2

1

3MIX

1

4TOP

1

5BOTTOM

1

1SQUAL 1

2HEPTANE16TOP

1

7SQUAL

1

8HEPTANE

Sample Tes t

Stream ID 1SQUAL 2HEPTANE 3MIX 4TOP 5BOTTOM 6TOP 7SQUAL 8HEPTANE

Temperature C 25.0 25.0 25.0 100.0 100.0 100.0 100.0

Pressure atm 0.987 0.987 0.987 0.987 0.987 0.987 0.987 0.987

Vapor Frac 0.000 0.000 0.000 1.000 0.000 0.000 1.000

Mole Flow kmol/hr < 0.001 0.997 0.997 0.992 0.005 0.000 0.005 0.992

Mas s Flow kg/hr 0.100 99.900 100.000 99.432 0.568 0.000 0.568 99.432

Volume Flow cum/hr < 0.001 0.146 0.147 29.683 0.001 0.000 0.001 29.683

Enthalpy Gcal/hr > -0.001 -0.053 -0.053 -0.041 > -0.001 > -0.001 -0.041

Mas s Flow kg/hr

WATER

HEPTANE 99.900 99.900 99.432 0.468 0.468 99.432

SQUAL-01 0.100 0.100 trace 0.100 0.100 trace

Mas s Frac

WATER

HEPTANE 1.000 0.999 1.000 0.824 0.824 1.000

SQUAL-01 1.000 0.001 55 PPB 0.176 0.176 55 PPB

Mole Flow kmol/hr

WATER

HEPTANE 0.997 0.997 0.992 0.005 0.005 0.992

SQUAL-01 < 0.001 < 0.001 trace < 0.001 < 0.001 trace


Figure 7: PDF and P&ID of the final stage of solvent separation using one distillation column and one flash separator (‘RADFRAC’ model)

Table 6: Stream table for the final stage separation process using one distillation column and one flash separator (‘RADFRAC’ model)

According to Table 5, it can be seen that the second FS was not able to perform any

separation when the reactor temperature was set at 100 °C since there were no materials

flowing through the top stream ‘6TOP’, as indicated in the yellow box. Meanwhile, when

implementing one FS to ‘RADFRAC’ model, it only separates 33 % of heptane from

‘5BOTTOM’ stream into ‘6TOP’ stream (indicated by the red box in Table 6). However, in

FLASH

MIXER1 RADFRAC

MIXER2

1

3MIX

1

4TOP

1

5BOTTOM

1

1SQUAL 1

2HEPTANE

16TOP

1

7SQUAL

1

8HEPTANE

Sample Test


Tempera ture C 25.0 25.0 25.0 97.9 99.3 100.0 100.0 98.0

Pressure atm 0 .987 0 .987 0 .987 0 .987 0 .987 0 .987 0 .987 0 .987

Vapor Fra c 0 .000 0 .000 0 .000 1 .000 0 .000 1 .000 0 .000 1 .000

Mole Flow kmol/hr < 0 .001 0 .997 0 .997 0 .990 0 .007 0 .002 0 .005 0 .992

Mass Flow kg/hr 0 .100 99.900 100.000 99.202 0 .798 0 .230 0 .568 99.432

Vo lume Flow cum/hr < 0 .001 0 .146 0 .147 29.434 0 .001 0 .069 0 .001 29.502

Enthalpy Gcal/hr > -0.001 -0.053 -0.053 -0.041 > -0.001 > -0.001 > -0.001 -0.041

Mass Flow kg/hr

WATER

HEPTANE 99.900 99.900 99.202 0 .698 0 .230 0 .468 99.432

SQUAL-01 0 .100 0 .100 trace 0 .100 trace 0 .100 trace

Mass Frac

WATER

HEPTANE 1 .000 0 .999 1 .000 0 .875 1 .000 0 .824 1 .000

SQUAL-01 1 .000 0 .001 trace 0 .125 55 PPB 0 .176 trace

Mole Flow kmol/hr

WATER

HEPTANE 0 .997 0 .997 0 .990 0 .007 0 .002 0 .005 0 .992

SQUAL-01 < 0.001 < 0 .001 trace < 0.001 trace < 0.001 trace


‘RADFRAC’ model, nearly 100% of squalane from ‘5BOTTOM’ stream had been successfully

separated to the bottom stream ‘7SQUAL’, which is highlighted in the blue box.

2.3.6 SA on heptane recovery for the final model

Having some trace of heptane still left in ‘6TOP’ and ‘7SQUAL’ stream, another SA

was carried out for both models. Similar SA procedure was taken, shown in Appendix B.5.

2.3.6.1 ‘FLASH’ model

The condition for performing the SA around the second FS was as follows: tank

pressure at constant and the tank temperature varied from 90 to 200 °C. The responding

variables, heptane flow rate in the top stream ‘6TOP’, labelled as ‘TOPHEPT’. Squalane flow

rate in the bottom stream ‘7BOTTOM’, labelled as ‘BOTSQUAL' was monitored to determine

the optimum reactor temperature (Figure 8). Note that the feed basis for both heptane and

squalane in the mixed stream was 0.468 kg/hr and 0.1 kg/hr, respectively.

Figure 8: Heptane flow rate in top stream and squalane flow rate in bottom stream as a function of ‘FLASH2’ temperature (‘FLASH’ model, constant pressure 1 bar)


VARY 1 FLASH2 PARAM TEMPC

BO

TS

QU

AL K

G/H

R

TO

PH

EP

T K

G/H

R

90 95 100 105 110 115 120 125 130 135 140 145 150 155 160 165 170 175 180 185 190 195 2000.0982

0.0984

0.0986

0.0988

0.0990

0.0992

0.0994

0.0996

0.0998

0.1000

0.000

0.025

0.050

0.075

0.100

0.125

0.150

0.175

0.200

0.225

0.250

0.275

0.300

0.325

0.350

0.375

0.400

0.425

0.450

0.475

TOPHEPT KG/HR

BOTSQUAL KG/HR


From Figure 8, initially, no heptane was detected in the top stream until the tank

temperature reached 100 °C. This was to be expected since the stream mainly consisted of

heptane and its boiling point is 98.42 °C. The increase in heptane flow rate began to form a

plateau around 0.450 kg/hr mark after reaching 145 °C. Squalane did not vaporise into the

top stream before temperature reached 130 °C. As such, the optimum temperature for the

second FS was determined to be 145 °C (as indicated by the dashed line). Table 7 below

shows the stream table generated from using the new operational parameters. (‘FLASH1’

temperature = 100 °C, ‘FLASH2’ temperature = 145 °C, both FS pressure = 1 bar)

Table 7: Stream table for the final stage separation process using two flash separators after sensitivity analysis (‘FLASH’ model)

The resulting mixed stream, ‘8HEPTANE’, contained 99.88 kg/hr of heptane, which

amounted to 99.98% heptane recovery (as indicated by the red box). Less than 0.001 kg/hr

of squalane was detected in stream ‘8HEPTANE’, which could suggest that little to none of

the squalane had been stripped from the FS. Meanwhile, in the bottom stream from the

second tank, stream ‘7SQUAL’ contained primarily squalane that accounted for almost

100% recovery from the feed stream ‘3MIX’ (as indicated by the blue box).

Sample Tes t


Temperature C 25.0 25.0 25.0 100.0 100.0 145.0 145.0 100.2

Pressure atm 0.987 0.987 0.987 0.987 0.987 0.987 0.987 0.987

Vapor Frac 0.000 0.000 0.000 1.000 0.000 1.000 0.000 1.000

Mole Flow kmol/hr < 0.001 0.997 0.997 0.992 0.005 0.004 < 0.001 0.997

Mas s Flow kg/hr 0.100 99.900 100.000 99.432 0.568 0.448 0.119 99.881

Volume Flow cum/hr < 0.001 0.146 0.147 29.683 0.001 0.151 < 0.001 29.835

Enthalpy Gcal/hr > -0.001 -0.053 -0.053 -0.041 > -0.001 > -0.001 > -0.001 -0.041

Mas s Flow kg/hr

WATER

HEPTANE 99.900 99.900 99.432 0.468 0.448 0.019 99.881

SQUAL-01 0.100 0.100 trace 0.100 < 0.001 0.100 < 0.001

Mas s Frac

WATER

HEPTANE 1.000 0.999 1.000 0.824 1.000 0.162 1.000

SQUAL-01 1.000 0.001 55 PPB 0.176 80 PPM 0.838 414 PPB

Mole Flow kmol/hr

WATER

HEPTANE 0.997 0.997 0.992 0.005 0.004 < 0.001 0.997

SQUAL-01 < 0.001 < 0.001 trace < 0.001 trace < 0.001 trace


2.3.6.2 ‘RADFRAC’ model

Similar to ‘FLASH’ model optimisation, the condition for SA was as follows: tank

pressure held at constant 1 bar and the tank temperature varied from 90 to 200 °C. The

responding variables, heptane flow rate in the top stream ‘6TOP’, labelled as ‘TOPHEPT’.

Squalane flow rate in the bottom stream ‘7BOTTOM’, labelled as ‘BOTSQUAL' was

monitored to determine the optimum reactor temperature (Figure 9). Note that the feed

basis for both heptane and squalane in the mixed stream was 0.698 kg/hr and 0.1 kg/hr,

respectively.

Figure 9: Heptane flow rate in top stream and squalane flow rate in bottom stream as a function of ‘FLASH’ temperature (‘RADFRAC’ model, constant pressure 1 bar)

A similar trend can be seen when compared to Figure 8. Heptane formed a plateau

at 0.670 kg/hr mark after reaching 145 °C, and squalene in the bottom stream, ‘7SQUAL’,

stayed constant at 0.1 kg/hr until it reached 145 °C. Hence, the FS, ‘FLASH’, used in

‘RADFRAC’ model should be at 145 °C. Table 8 below shows the stream table from using

the new operational parameters. (‘FLASH1’ temperature = 100 °C, ‘FLASH2’ temperature =

145 °C, flash tank pressure = 1 bar)


VARY 1 FLASH PARAM TEMPC

BO

TSQ

UA

L K

G/H

R

TO

PH

EP

T K

G/H

R

90 95 100 105 110 115 120 125 130 135 140 145 150 155 160 165 170 175 180 185 190 195 2000.0975

0.0980

0.0985

0.0990

0.0995

0.1000

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

0.50

0.55

0.60

0.65

0.70

TOPHEPT KG/HR

BOTSQUAL KG/HR


Table 8: Stream table for the final stage separation process using two flash separators after sensitivity analysis (‘RADFRAC’ model)

According to Table 8, the separation performance was similar to that of the

optimised ‘FLASH’ model; 99.98% heptane recovery from the mixed stream ‘4TOP’ and

‘6TOP’, highlighted as the red box, and 100% squalane separation in stream ‘7SQUAL’,

highlighted as the blue box. As a result from all the SA being imposed, both models had

achieved a minimum of 99.98% heptane separation, as well as nearly 100% squalane

separation.

2.3.7 Energy balance

To determine the feasibility of utilising DC or FS to separate algal hydrocarbon

from heptane, energy balance analysis was done by comparing the energy profile in the

models to the calorific value of the algal hydrocarbon.

AP is capable of calculating heat required for each unit operators to perform the

process. Hence, from the optimised models, the heat requirement, or termed heat duty

from AP, are shown in Figure 10 and Figure 11, as indicated by the variable Q in blue font.

The unit for the calculated heat duty is in kJ/kg.

Sample Test


Tempera ture C 25.0 25.0 25.0 97.9 99.3 145.0 145.0 98.3

Pressure atm 0 .987 0 .987 0 .987 0 .987 0 .987 0 .987 0 .987 0 .987

Vapor Fra c 0 .000 0 .000 0 .000 1 .000 0 .000 1 .000 0 .000 1 .000

Mole Flow kmol/hr < 0 .001 0 .997 0 .997 0 .990 0 .007 0 .007 < 0.001 0 .997

Mass Flow kg/hr 0 .100 99.900 100.000 99.202 0 .798 0 .679 0 .119 99.881

Vo lume Flow cum/hr < 0 .001 0 .146 0 .147 29.434 0 .001 0 .229 < 0.001 29.665

Enthalpy Gcal/hr > -0.001 -0.053 -0.053 -0.041 > -0.001 > -0.001 > -0.001 -0.042

Mass Flow kg/hr

WATER

HEPTANE 99.900 99.900 99.202 0 .698 0 .679 0 .019 99.881

SQUAL-01 0 .100 0 .100 trace 0 .100 < 0.001 0 .100 < 0.001

Mass Frac

WATER

HEPTANE 1 .000 0 .999 1 .000 0 .875 1 .000 0 .162 1 .000

SQUAL-01 1 .000 0 .001 trace 0 .125 80 PPM 0 .838 543 PPB

Mole Flow kmol/hr

WATER

HEPTANE 0 .997 0 .997 0 .990 0 .007 0 .007 < 0.001 0 .997

SQUAL-01 < 0.001 < 0 .001 trace < 0.001 trace < 0.001 trace


From Figure 10 and Figure 11, the heat duty required for this separation process

implemented from ‘FLASH’ and ‘RADFRAC’ model was 49,901 kJ/kg and 49,545 kJ/kg,

respectively. The heat duty was relatively similar, accounting for only 0.71% difference

regarding value.

Figure 10: PDF and P&ID of the final stage of solvent separation using two flash separators (‘FLASH’ model)

Figure 11: PDF and P&ID of the final stage of solvent separation using two flash separators (‘RADFRAC’ model)

Notice, from Figure 11, the total heat duty was calculated as follows: heat from the

condenser, would be compensated with the heat from the reboiler, . This was

assumed that the heat taken from condensing stream ‘4TOP’ could be transferred to stream

FLASH1

Q=49704

MIXER1

FLASH2

Q=197

MIXER2

25

1

3MIX

100

1

4TOP

100

1

5BOTTOM

25

1

1SQUAL

25

1

2HEPTANE

145

16TOP

145

1

7SQUAL

100

1

8HEPTANE

Temperature (C)

Pressure (atm )

Q Duty (kJ/hr)

FLASH

Q=418

MIXER1 RADFRAC

QC=-31724

QR=80851

MIXER2

25

1

3MIX

98

1

4TOP

99

1

5BOTTOM

25

1

1SQUAL

25

1

2HEPTANE

145

16TOP

145

1

7SQUAL

98

1

8HEPTANE

Tempera ture (C)

Pressure (atm)

Q Duty (kJ/hr)


‘5BOTTOM’ via a heat exchanger. Hence, the value 49,545 kJ/kg was computed based on

the overall heat requirement. Also, another assumption was made based on the fact that no

energy will be neither loss nor gain from external factors.

Using the heat duty obtained from the simulation as the basis of heat requirement

for separating 0.1kg of squalane, an energy balance was conducted to determine the

efficiency of operating the separation process. According to Zhang et al. (1990), the

enthalpy of combustion of liquid squalane, , is -19,801.3 kJ/mol. Using this

information and divided by its molecular weight of 422.81 g/mol, its calorific value is

46,830.6 kJ/kg. The following shows the calculation of the calorific value of squalane:

(

)

(

)

(

)

Equation 1: Expression of calorific value determination

If 0.1 kg/hr of squalane was to be separated, its heating energy was only

4,683.06 kJ/hr. When compared to the heat duty of the separation process, both the

simulation model requires almost ten times the amount of heating energy obtained from

squalane. In other words, the energy derived from separating squalane was not able to

compensate the heat requirement for operating the separation process. A similar outcome

could be obtained if squalene was used in the model as opposed to squalane. According to

finding conducted by NIIR Board of Consultants and Engineers (2003), the calorific value

for squalene is 19,400 Btu/lb, which is equivalent to 45,244 kJ/kg. Since its calorific value

of squalene is similar to that of squalane, which amounts to a heating value of 4,524.4

kJ/hr, the stimulation still suggested that the separation process was inefficient.

In conclusion, this proves that the separation process using either FS or DC would

not be feasible to operate the separation process itself since it required a tremendous

amount of energy to sustain the plant itself. It is worth to mention that this calculation was

only based on a single stream separation process, as there was no optimising technique


being implemented to construct a more feasible process. For instances, effluent of top

streams from the flash separators could be recycled back to the feed streams, the amount

of solvent used in the algae oil extraction process could be reduced, or the feed streams

could be concentrated either in a batch or semi-batch evaporation process, separate and

recycle the evaporated solvent back to the extraction process.

2.3.8 Sensitivity of the simulation

The above separation process was based on the fact that during the solvent

extraction process, 100% of the aqueous phase was removed from the partitioning. In

other words, the solvent extraction was assumed to be 100% efficient. However, in a real

world application, this would not be the case. There is bound to have some trace of water

still left in the organic phase during separation. Hence, water will be introduced to the feed

stream, ‘1SQUAL’. To test the effect of water in the extract on the overall heat requirement,

the simulation was re-initialised, re-ran and the following Table 9 and Table 10 summarise

the results from implementing ‘FLASH’ and ‘RADFRAC’ model.

Table 9: Heptane, squalane recovery and overall heat duty as a function of water being introduced in the feed stream (‘FLASH’ model)

Water (kg/hr) Heptane recovery

(%) Squalane Recovery (%) Heat Duty (kJ/kg)

0.0 (Control) 99.98 100.0 49,901.0

1.0 99.98 100.0 52,439.0

2.0 99.98 100.0 55,015.0

3.0 99.98 100.0 57,595.0

4.0 99.98 100.0 60,176.0

5.0 99.98 100.0 62,757.0

Table 10: Heptane, squalane recovery and overall heat duty as a function of water being introduced in the feed stream (‘RADFRAC’ model)

Water (kg/hr) Heptane recovery

(%) Squalane Recovery (%) Heat Duty (kJ/kg)

0.0 (Control) 99.98 100.0 49,545.0

1.0 99.98 100.0 47,504.0

2.0 99.98 99.0 47,662.0

3.0 99.98 99.0 49,125.0

4.0 99.98 98.0 51,388.0

5.0 99.98 98.0 54,373.0


As expected, according to Table 9, with ‘FLASH’ model, as more water was

introduced into the separation process, the higher the heat duty was. As the simulation

suggested, 5 kg/hr of water added increased the heat duty of the process almost by 26% of

the control heat duty. In fact, for each increment of 1kg/hr of water in the system, the

overall heat duty raised almost by a factor of 1.05. This was due to an increase in overall

heat capacity of the mixture since water has a higher heat capacity, 4.18 kJ/kg.K as

opposed to heat capacity of heptane 2.24 kJ/kg.K and squalane 2.10 kJ/kg.K. Although the

heat duty for the process was increased as the amount of water introduced increased, both

the solvent and squalane recovery remained the same. This suggested that FS could handle

a presence of water in the system while achieve the same outcome, except of increasing

heat requirement.

In the ‘RADFRAC’ model, the heat duty decreased by 4.1% when 1 kg/hr of water

was introduced. However, the heat duty slightly increased after 2 kg/hr of water added,

and the heat duty increased at least by a factor of 1.03 over the addition of water starting at

3 kg/hr. Upon investigation throughout the simulation, it was noticed that the amount of

heptane did not separate as much as to the original model, which had no water in the

system. Having said that, the heptane recovery did not differ as the amount of water in the

system increased. However, as shown in Table 10, the squalane recovery decreased slightly

by 1% in every addition of water. This suggested that DC was sensitive to the presence of

water, and this could cause a detrimental effect on the hydrocarbon separation.

That being said, both models were able to achieve a minimum of 99.98% heptane

separation, which proved to be an invaluable information when determining the ability to

strip solvent from a mixture of the homogenous solution.


3 Membrane separation process – Nanofiltration (NF)

3.1 Introduction

The commercial scale algae fuel production requires an enormous amount of

energy, especially in the post-extraction process. Distillation column was used

conventionally for stripping the essential oil produced by the algae from a solvent. To bring

the lighter key component, that is the solvent, to a boiling point, heat energy must be

supplied to carry out phase change and eventually evaporate off it from the mixture to

isolate the heavy key component that is the algae oil. Recent studies have shown that

implementing nanofiltration process could be an alternative method of separating solvent

without going through a phase change (Othman et al. 2009; Kim et al. 2014). This chapter

aims to provide an insight of how nanofiltration works, its benefits and limitations, and the

experiments that had been conducted to evaluate its applicability to separate solvent in an

organic phase.

3.2 Literature review

Nanofiltration (NF) is a pressure-driven process, whereby it is under the influence

of a pressure gradient of both sides of the filtering membrane (Bhanushali et al. 2002). It

also refers to as a filtration process that has pore sizes ranging from 0.1 nm to 10 nm

(Farid 2010). It could selectively retain dissolved components at the nanometer scale,

which have the molecular weight between 300 g mol-1 and 1000 g mol-1 (or Dalton, Da,

where 1 Dalton = 1 g mol-1). The driving force for a NF is the difference of pressure applied

and the osmotic pressure, and it can be expressed as Equation 2.

Equation 2: Expression of nanofiltration driving force

Studies have shown that NF has the advantages of low energy consumption,

relatively low investment, high permeation flux and unique separation competence

(Tarleton, Robinson and Low 2009). NF has also been considered to be the new filtration


process that is often used to lower total dissolved solids in water and remove disinfection

by-product compounds such as synthetic minerals and organic compounds (Letterman

1999). It is widely used in the food processing industry, and it has been shown to provide a

viable alternate technique to separate and purify chemical streams.

In recent studies, a relatively new technology that utilises solvent resistant

membrane to separate organic solvent from an organic mixture without going through

phase changes has regularly been implemented in oil upgradation or refinery stage

(Kim et al. 2014). Such technology, termed solvent resistance nanofiltration (SRNF), has

gained recognition for its application in separating and purifying organic compounds as it

was considered to be one of the novel approaches for extracting organic compounds

(Schäfer et al. 2005; Kim et al. 2014). Its application not only reduces solvent consumption

by reusing the solvent after nanofiltration, but it also reduces the energy demand in the

separation process, in comparison to the separation process in a distillation column

(Sulzer 2015).

3.2.1 Solvent resistance nanofiltration (SRNF)

SRNF membrane has made a significant breakthrough in membrane process as it

provides high attainments in resulting a higher flux and salt rejection, creating huge

interest in mechanical separation production sectors (Lau et al. 2012). SRNF process also

has been finding a wider applicability in a non-aqueous medium, which includes

pharmaceutical industry in pesticides removal, food processing in nutrients concentration

and petroleum refinery in chemical removal (Othman et al. 2009; Kim et al. 2014). This

applied technology has recently received much greater attention due to its socio-

economical urges such as an increased concern for the environment and the search for

cleaner and more energy-efficient technologies (Basu et al. 2009). Hence, this leads to a

development of SRNF membrane to separate the organic solvent from a non-aqueous

mixture (Bhanushali et al. 2001).


The application of SRNF has not been extensively examined due to its very recent

development, a lack of knowledge and its implementation feasibility (Darvishmanesh,

Degrève and Van der Bruggen 2009). However, according to some studies (Schmidt et al.

1999; Van der Bruggen et al. 2004; Van der Bruggen et al. 2006; Li et al. 2008), it has been

shown that introducing solvent-resistant materials in NF membrane has proved to be

promising in industrial uses of the SRNF system. Another hurdle one could reason is that

there is a limited number of commercial solvent-resistant membranes available in the

market due to some issues such as membrane property and implemented filtration system.

In many cases, unlike aqueous NF that involves separation of charged solutes from

other compounds in aqueous phase, organic solvent NF separates molecules in organic-

organic systems (Tarleton, Robinson and Low 2009). As the name suggests, the materials

used to fabricate SRNF must be solvent resistant and preserve their separation

characteristics in an organic solvent, provided that the membrane is appropriately used

(Marchetti et al. 2014). One of the types of SRNF used is the thin film composite (TFC)

membrane. TFC membrane consists of an ultrathin layer on a porous support and a non-

woven backing, which can be seen in Figure 12.

Figure 12: Schematic view of TFC membrane (Marchetti et al. 2014)

TFC membrane is flexible and can be designed for a particular application.

Therefore, it can be independently optimised for the particular application due to its

layered structure that can be manufactured separately (Peyravi, Rahimpour and

Jahanshahi 2012). This membrane is commonly made via a membrane synthesis technique

called interfacial polymerisation (IP), which occurs at an interface between two immiscible

solutions, an aqueous solution containing one monomer and an organic solution containing


a second monomer (Odian 2004). The commonly used polymers for synthesising the

membrane are polyethersulfone (PES), polyamide (PA) and polyimide (PI).

Figure 13: Molecular structure of PES, PA and PI ("Polyethersulfone Cas 25667-42-9 - RTP Company" 2016; "Proteins" 2016; "Polyimides" 2016)

Further review of the application of TFC membranes found that polyamide-based

TFC membranes by interfacial polymerisation were mainly operated for aqueous

application, and filtration in non-polar media was not suitable

(Cadotte and Petersen 1981). Only when nonreactive Polydimethylsiloxane (PDMS),

commonly referred as silicones, was integrated to the polymerization reaction could result

in high nonpolar solvent permeance (Cadotte and Peteren 1981).

Figure 14: Molecular structure of PDMS (Gilbert 2012)

3.2.2 Membrane filtration technique – Dead-end filtration

Filtration technique is categorized by the direction of the feed flow. Dead-end

filtration has the configuration of the feed flowing perpendicular to the membrane. It is a

simpler configuration that requires less maintenance cost (Nobel and Terry 2004).


However, its drawback is poor filtration performance due to a high resistance to filtrate

flow caused from retained particles accumulating on the surface of the membrane

(Nobel and Terry 2004).

Figure 15: Configuration of dead-end filtration

3.2.3 Benefits of implementing SRNF

As mentioned above, NF process has been found to be widely applied in

non-aqueous media for its potential to be energy-efficient and environment-friendly, as

compared to the traditional separation process. According to Bhanushali and

Bhattacharyya (2003), the principle of conventional membrane process is to recover,

recycle solvents and compounds of interest from a complex non-aqueous system as

efficiently as possible. SRNF, in particular, has the potential to replace industrial energy-

intensive processes as the filtrated solvents could potentially be re-used and recycled over

and over again where it is appropriate (Aerts et al. 2004; Lin, Rhee and Koseoglu 1997;

Vankelecom et al. 2004). Such industrial processes include distillation, evaporation, waste

generating extractions, chromatographic separations and crystallisations.

Not only does NF process reduce solvent consumption by reusing the solvent, the

filtered solvents and compounds of interest would also have fewer undesirable side effects

than traditional separations methods (Sulzer 2015). SRNF only utilises pressure difference

and its membrane pore size to separate compounds of interest without going through any

phase changes, which could degrade or alter the molecular structure of the compounds to

be filtered in the media. NF membrane process also aids in lowering energy consumption,


improving product quality, lowering operation and maintenance costs, and lowering

emissions to the environment operations as compared to the traditional chemical

engineering unit operations (Bhanushali and Bhattacharyya 2003).

3.2.4 Influence of membrane property

Despite all promising perspectives for NF, not only in reducing solvent

consumption but also in lowering operational costs and emissions to the environment, NF

still has some unresolved problems and some undesirable factors that could hinder large

scale production.

3.2.4.1 Influence of membrane fouling and molecular size

One of the main factors in any membrane process is membrane fouling. This

happens when particles in the media adhere to the membrane’s surface, which is termed

adsorption, causing severe flux drop and poor filtration quality (Van der Bruggen, Mänttäri

and Nyström 2008; Violleau et al. 2005). The size and concentration of colloidal particles

play a significant role in membrane fouling, and fouling could occur either caused by

particle accumulation or build-up of a cake layer within membrane pores or membrane

surface (Zhu and Elimelech 1997). Intuitively, a higher colloid concentration in media

could lead to an increase in fouling. As a result, accumulation of colloids either on the

membrane or within the membrane could deteriorate both the membrane itself along with

the performance of filtration.

3.2.4.2 Influence based on molecular structure and nature

Another factor that affects the permeability of NF membrane is the molecular size,

shape and chemical nature of the components in the media as different pore diameter on

the membrane significantly influences the performance of the NF process. Membranes are

commonly quantified by their nominal molecular weight cut-off (MWCO), which is the

smallest molecular weight species for which the membrane attains more than 90%


rejection (Farid 2010). According to Machado et al. (1999; 2000) and Geens et al. (2005), in

a binary permeation of two species of a homologous series, the species with lower

molecular weight tends to permeate preferentially. Robinson et al. (2004) had

demonstrated that the chemical nature played a significant part by observing the relative

permeability of hydrocarbon pairs of similar shape and size, for instance, n-hexane and

cyclohexane. Despite the fact that both compounds have an equal number of carbon atoms,

the permeability of n-hexane was about three times that of cyclohexane, in other words,

separation is based on the effect of size exclusion.

3.2.4.3 Influence based on solvent polarity and temperature

Solvent polarity can greatly affect the outcome of membrane filtration. Solvent

polarity could be defined as the molecule that has permanent dipole moment due to its

atomic arrangement. Polar solvent such as water has one end with positive charge

(i.e., H+ atom) and the opposite end with negative charge (i.e., O2- atom), while non-polar

solvent such as heptane has zero dipole moment, whereby the dipoles cancelled out.

Based on the findings from studying the polarity of the solvents such as water,

ethanol, and n-hexane on the rejection mechanism in NF conducted by Van der Bruggen et

al. (2002), it was found that the rejection behaviour was favoured with decreasing solvent

polarity with hydrophobic membranes; conversely, the rejection behaviour was reduced

with decreasing polarity for hydrophilic membranes. Similarly, Burshe et al. (1997)

mentioned that the rejection rate increased with increasing solvent polarity from studying

the polarity effect of water, methanol, ethanol, isopropanol and n-butanol on rejection

mechanisms. Moreover, based on a study of the effect of polarity on the separation

mechanism of ethanol/hexane and ethanol/heptane system in PDMS membranes, Farid

and Robinson (2009) concluded that the polar solvent (ethanol) is more selective at low

concentration. However, the non-polar solvent (hexane or heptane) is more selective with

increasing concentration of the polar solvent.


Not only does solvent polarity affect the filtration process, temperature could also

greatly affect solvent flux on the permeate side (Machado et al. 1999). It was found that an

increase in temperature rises permeate flux either through a drop in solvent viscosity or an

increase in the solvent diffusion coefficient (Machado et al. 1999; Machado et al. 2000).

3.2.4.4 Influence of membrane swelling

Membrane swelling in non-aqueous media has often been reported, either in a

beneficial or undesirable way (Darvishmanesh, Degrève and Van der Bruggen 2009).

Membrane swelling is a dissolution process of a polymeric membrane in a defined solvent,

which could result in deformation of the membrane polymer network (Billmeyer 1984). A

series of three distinct processes is used as a visual aid to illustrate the mechanism of

membrane swelling, which is shown below (Figure 16).

Figure 16: Membrane swelling mechanism (Farid 2010)

1. Solvent absorption – The polymer surface absorbs the solvent in.

2. Solvent penetration – The polymer surface being penetrated by the solution, which

the solvent molecules first occupy the free volume and then diffuse into the

polymer.


3. Polymer expansion – The polymer structure expands as a result from the trapped

solution in the pores, swelling the network of the polymer chains.

As mentioned prior, membrane swelling can influence the transport mechanism of

different types of membrane, namely dense and porous membrane. Firstly, the expansion

of free volume in a dense membrane could cause the membrane pores to increase, allowing

larger molecules to pass through, thus, increasing membrane permeability, decreasing

selectivity and lowering rejection (Ebert 2005; Farid 2010). Secondly, the compaction of

membrane pores in a porous membrane could lead to an increase in selectivity and

decrease in permeability, results in higher rejections (Ebert 2005; Farid 2010).

Study has found that membrane swelling is a good indication for permeation as the

so-called channels from the membrane are formed, thus increasing solvent flux in organic

solvents such as n-alkanes, i-alkanes and cyclic compounds, through a dense PDMS

composite NF membrane (Robinson et al. 2004). However, it was argued that swelling for

porous membrane could cause the membrane to be ‘less open’, resulted in higher rejection

(Robinson et al. 2005).

3.2.4.5 HP4750 Stirred Cell

The HP4750 Stirred Cell used in this experiment has a high durability against

pressure due to its stainless steel (316L) cell body construction that can withstand a

maximum rating of 1000 psig (6900 kPa). With this feature, this stirred cell is capable of

performing a wide selection of membrane separation and stimulating the flow dynamics of

microfiltration, ultrafiltration, reverse osmosis and nanofiltration. Moreover, this stirred

cell is also chemically resistant to a wide range of liquid and gas chemicals, making it an

ideal choice to filter both aqueous and non-aqueous solutions.

This stirred cell is considered suitable for simulating the flow dynamics of NF

systems, in particular, a dead-end filtration, where the feed flow is perpendicular to the

membrane, resulting in the retained particles accumulating on the surface of the

membrane (Nobel and Terry 2004).


Its features and technical specifications are provided in Appendix C.

Figure 17: Image of HP4750 Stirred Cell (Sterlitech 2015)

3.3 Materials and methods

3.3.1 Chemicals

The solvent used for dissolving squalene was n-heptane, which was purchased

from Rowe Scientific Pty Ltd, Perth. The n-heptane purchased was a technical grade.

Squalene was used to facilitate the concentration variation for the nanofiltration

performance, and it was purchased from VWR International Pty Ltd. Table 11 shows the

essential physical properties of the chemicals used in this experiment.

Table 11: Physico-chemical properties of n-heptane and squalene

Chemicals n-heptane Squalene

Chemical structure

Molecular weight 100.21 g/mol 410.72 g/mol

Density 679.5 kg/m3 854.0 – 856.0 kg/m3

Flash point -4.0 °C 200.0 °C

Boiling point 98.4 °C 470.3 °C

3.3.2 Nanofiltration membrane

The NF membrane used for the filtration experiment was GE Osmonics KH Duracid

Series TFC NF Membrane, and it was purchased from Sterlitech Corp. Table 12 shows the

technical specification of the studied membrane:


Table 12: Technical specifications for GE Osmonics Duracid NF membrane (Sterlitech 2015)

Series Feed Type pH

range Flux Pressure

MgSO4 Rejection

MWCO

Duracid Industrial/ Commercial

Acid Purification,

Mineral Concentration

0 – 9

10 – 19 Gfda/

17 – 32.3 Lmhb

225 psi / 1551 kPa / 15.51 bar

98.0 % ~150 –

200 Daltons

a Gfd – gallons/ft2/day; b Lmh – litre/m2/hour;

The purchased membrane was a flat sheet measuring 30.5 cm by 30.5 cm, and it

was cut into a circular disc of 46 cm diameter using a print-out that had a circle of diameter

46 cm as a guide. For each experiment trial, a new membrane was used, and the membrane

was immersed in deionized (DI) water for at least 24 hours before any experimental work.

3.3.3 Filtration experiment set-up and procedure

Dead-end filtration experiments were performed with a stirred cell; model

StelitechTM HP4750 Stirred Cell. The stirred cell was pressurised by industrial grade

nitrogen gas and the maximum operating pressure for this cell was Pa

(1000 psi or 69 bar). The effective membrane area of the stirred cell was m2,

allowing an active membrane diameter of 4.31 cm. This stirred cell had a processing

volume of 300 mL, while its liquid hold-up volume was 1 mL.

For the filtering process, the applied pressure in this experiment was 20 bar, 30 bar

and 50 bar, respectively. Meanwhile, the pressure on the permeate side was approximated

to be at atmospheric pressure under all conditions as the permeate tube was being held in

the atmosphere.

Prior to filtration, the compaction process mentioned in the previous section was

carried out. All experiments were performed in batch mode, whereby the feed solution was

charged through the membrane in the cell, leaving the larger product on the membrane

surface. The permeate samples flowed out from the bottom of the cell and were collected at

a 1-minute interval for every trial over 1 to 1.5 hours, and the cumulative volume was

measured using a measuring cylinder.


Filtration experiment was done using DI water and a mixture of organic solution as

the feed media. The organic solution comprised of squalene and heptane was used as the

solvent. For the purpose of evaluating the performance of the nanofiltration in organic

solution, different concentration of squalene was tested at 1.0 %, 3.0 % and 5.0 % v/v. The

concentration of the squalene samples was based on volume percentage of the squalene

content and the volume percentage is defined as Equation 3.

Equation 3: Volume percentage determination

Note: The solute throughout this experiment was squalene and the solvent used to make

up the solution was heptane.

The experiments were conducted in pairs to check the replication of the membrane

performance. All experiments were conducted at ambient temperature of . A

schematic view of the experimental set-up is shown in Figure 18.

Figure 18: Diagram of experimental set-up


3.3.4 HP4750 Stirred Cell assembly, maintenance and operation

Before assembling the stirred cell, all of the necessary components should be

verified and present, and the complete set of the stirred cell is shown (Appendix D). All the

assembling procedures and precautions are described in Appendix E.

3.3.5 Chemical analysis

To investigate the solute rejection in the nanofiltration process, the feed and

separation permeate samples were analysed using Shimadzu Gas Chromatography system

that comprised of GCMS-QP2010S gas chromatograph-mass spectrometer (GC-MS), GC-

2010 gas chromatograph and AOC-20i+S auto-injector and an auto-sampler. For each

chemical analysis, an approximate 1 mL of sample was collected in a 4 mL screw top glass

vial. The equipment and method conditions used for running the GCMS analysis are shown

in Table 13. Appendix F shows the detail method parameters for running the GCMS

analysis.

Table 13: List of equipment and method condition used for GCMS

Parameters Description

Column BP-5, 30 m long, 0.25 µm thickness and 0.25 mm

internal diameter

Carrier gas Ultra-high purity helium gas

Injector port temperature 300 °C

Column oven temperature Kept at 220 °C for 1 minute, ramped to 260 °C at

the rate 2.0 °C min-1

Total run time 35 minutes

Mass spectra range 45.0 to 1000 (mass to charge) m/z

3.3.6 Membrane permeance analysis

The performance of the nanofiltration membrane was examined after the filtration

experiment. The cumulative weight of permeate recorded from each experiment was used


to determine the filtration system efficiency such as the permeate flux and the rejection

value. The permeate flux, (L/m2.hr or Lmh) was obtained using Equation 3.

Equation 4: Expression of permeate flux

where is the cumulative volume difference (L), is the time difference (min), and is

the active membrane area (m2).

While the rejection value, could be obtained with the following equation:

Equation 5: Expression of rejection value

where and is the permeate concentration and feed concentration (% vol),

respectively.


3.4 Nanofiltration performance – Results and Discussion

Prior to solvent separation using nanofiltration, two tests were carried out to verify

its capability to permeate different types of solvents, permeating polar and non-polar

solvent. It was necessary to determine whether the membrane purchased from

Sterlitech Co. was applicable for the purpose of this experiment and to investigate the

factors that could affect the membrane performance using different solvents.

3.4.1 Permeating DI water

The filter membrane was tested using de-ionised water as feed media. This was

done to verify if filtration was possible from using the pre-soaking method. After pre-

soaking the filter overnight, the stirred cell was fitted with the filter and was charged with

100mL of deionised (DI) water at a constant pressure of 20 bar by N2 gas. This set-up was

repeated three times to evaluate the reliability of the results. The following Figure 19 and

Figure 20 show the cumulative permeate volume for three replicates and its flux over a

period of 10 minutes, respectively.

Figure 19: Scatter plot of cumulative permeate volume in DI water for Set 1 (Blue), Set 2 (Red) and Set 3 (Green) at 20 bar with its respective trend line and its R2 value

y = 0.4109x + 0.0909 R² = 0.9982

y = 0.4127x + 0.0455 R² = 0.9994

y = 0.4209x + 0.0318 R² = 0.9991

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

0 2 4 6 8 10 12

Cu

mu

lati

ve V

olu

me

(m

L)

TIme (min)

Permeate Volume Set 1, 2 & 3 - DI Water

Set 1

Set 2

Set 3

Linear (Set 1)

Linear (Set 2)

Linear (Set 3)


Figure 20: Scatter plot of permeate flux in DI water for Set 1 (Blue), Set 2 (Red) and Set 3 (Green) at 20 bar

According to Figure 19, it can be seen that the cumulative permeate volume was

relatively consistent for all of the filtration performed. An average R-square value of 0.998

was achieved when permeating DI water. Likewise, from Figure 20, the permeate flux

stabilised after filtering for 4 minutes and yielded an average permeate flux of 17.33 Lmh.

At the beginning of the experiment the permeate flux in Set 1 was slightly higher than the

other sets. However, it was clear that the filter could retain a stable and consistent

permeate flux over time. This was to be expected, as the molecular weight of water

(18.01 Dalton) is smaller than the MWCO of the membrane (200 Daltons), which suggested

that water could permeate through the nanofilter with consistent results. Thus, this

resulted in a relatively higher permeate flux (Kim, Jegal and Lee 2002). Such linear

relationship between the permeate volume and the time taken suggested that the pre-

soaking method was necessary as it removed the conditioning agent on the surface of the

filter upon manufacturing the filter (Vandezande, Gevers and Vankelecom 2008).

It is worth mentioning that there was little to no literature review to compare the

permeance results obtained for the Duracid membrane. However, the results shown by

permeating DI water through the filter suggested that there was no significant impact from

0.00

5.00

10.00

15.00

20.00

25.00

30.00

0 2 4 6 8 10 12

Pe

rme

ate

Flo

w R

ate

(Lm

h)

TIme (min)

Permeate Flux Set 1, 2 & 3 - DI Water

Set 1

Set 2

Set 3


membrane-solvent interaction, as the filter did not change in physical appearance upon

contacting with DI water. According to the technical specification for the membrane

purchased from Sterlitech, refer to Table 12, the permeate flux fell within the expected

range, which implied that the filter was functioning properly.

3.4.2 Permeating heptane

The filter was prepared using the same method as described in Section 3.3.3. Since

three filters were pre-soaked in heptane, only one filter can be used at a time. Filters were

tested by its particular total soaking time in heptane, which was 30, 60 and 90 minutes. It

was noted that when the stirred cell was charged at 20 bar, there was no solution

permeating from the stirred cell outlet. Hence, the stirred cell was fitted with the filter and

was charged with 100mL of heptane solution at a constant pressure of 30 bar by N2 gas.

The permeate performance of the filters was recorded accordingly, and is shown in Figure

21 and Figure 22.

Figure 21: Scatter plot of cumulative permeate volume in heptane for different soaking times at 30 bar – Set 1 (30 min), Set 2 (60 minutes) and Set 3 (90 minutes) with its respective trend line and its R2 value

y = 0.0864x + 0.1109 R² = 0.9979

y = 0.0737x + 0.1615 R² = 0.9921

y = 0.059x + 0.1904 R² = 0.9874

0.0

0.5

1.0

1.5

2.0

2.5

3.0

0 5 10 15 20 25 30

Cu

mu

lati

ve V

olu

me

(m

L)

Time (min)

Permeate Volume Set 1 & 2 - Heptane

Set 1 (30 min)

Set 2 (60 min)

Set 3 (90 min)


As shown in Figure 21, the total cumulative permeate volume decreased as the

soaking time in heptane solution increased. It was noted that the longer the soaking time in

heptane, the harder it is for the heptane to permeate through. Observed from Set 3, the line

of best line yielded a relatively weak measure of correlation compared to other sets. Its

final cumulative permeate volume was 1.9 mL over the period of 20 minutes, which was

about 70.3 % of the final cumulative permeate volume for Set 1 (2.7 mL). Noted from the

R-square values, it can be seen that the linear correlation deviated over prolonged contact

time with heptane. Such trend was not expected, as preliminary experimentation did not

take into account of the different effect after soaking in heptane solution over a different

period of time.

Figure 22: Scatter plot of permeate flux in heptane for different soaking times at 30 bar – Set 1 (30 min), Set 2 (60 minutes) and Set 3 (90 minutes)

As a result from a decreased in cumulative permeate volume as seen from Figure

21, the final permeate flux had decreased over the increasing soaking time from 3.7 Lmh

(Set 1) to 2.6 Lmh (Set 3). It can be seen that due to the different soaking time in heptane

solution, the permeate flux for using the filter was not only consistent, but also displaying a

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

8.00

9.00

0 5 10 15 20 25 30

Pe

rme

ate

Flo

w R

ate

(Lm

h)

TIme (min)

Permeate Flux Set 1 & 2 - Heptane

Set 1 (30 min)

Set 2 (60 min)

Set 3 (90 min)


decreasing trend. Moreover, the permeate flux for filtering heptane solution was noticeably

lower (3.17 ± 0.55 Lmh) when compared to filtering DI water (17.33 ± 0.11 Lmh).

Table 14: Physical properties of solvents used (Engineeringtoolbox 2016)

Some reasons could explain such phenomena in the filtration trials. Upon

investigation, it was found that the differences in the physical properties of solvents, as

shown in Table 14, could affect the results of the permeate flux (Kim, Jegal and Lee 2002).

The physical properties included molecular weight, dielectric constant, and viscosity.

According to their studies, despite viscosity of water being higher than heptane, it was

observed that the polar solvent (water) had resulted in a higher flux using polyamide TFC

membrane, while the nonpolar solvent (heptane) resulted in lower flux

(Kim, Jegal and Lee 2002). This was mainly due to heptane having significantly lower

dielectric constant, thus its high hydrophobicity. Dielectric constant is a measure of a

substance’s ability to insulate electric charges from each other. It measures the polarity of

the material, and that is, the higher the dielectric constant, the higher polarity the solvent,

the greater the ability to stabilise charges (Hardinger 2016). Hence, due to such factor, the

permeate flux from permeating heptane resulted in lower flux compared to permeating

water.

According to Van der Bruggen et al. (2002), non-polar solvent such as n-heptane

affected negatively the solvent flux through hydrophilic membranes. Since the membrane

manufacturer did not disclose any information in regards to the materials used for

fabricating Duracid membrane, it could be postulated that Duracid membrane is a

hydrophilic membrane due to such low permeate flux in heptane. A similar study

suggested that the polarity and the hydrophobicity of membrane surface play a crucial role

in solvent permeation (Jimenez-Solomon et al. 2013). According to these studies, the

Solvents Molecular Weight (g mol-

1)

Dielectric Constant (at

20°C)

Viscosity (cP)

(at 27°C)

Water 18.02 80.1 0.890

Heptane 100.21 1.9 0.376


support membrane of TFC membrane had a significant impact on the physicochemical

properties of different solvents, particularly with n-hexane, a non-polar solvent.

The filter manufacturer had prescribed the method of soaking the filter in DI water

only. However, upon consulting with the Process Development Product Manager from

Sterlitech, it was recommended that the Duracid membrane was the best membrane they

could offer for this experiment. It is also worth mentioning that due to insufficient data for

the membrane’s compatibility with heptane from Sterlitech, the Product Manager

suggested that Duracid membrane could be tested for its applicability to the nonpolar

organic solution and investigate its filtration outcome, thus, the usage of heptane as the

solvent.

A further investigation on the effect of a longer soaking time in heptane was carried

out. The filter membrane was pre-soaked in DI water for overnight, followed by soaking

the membrane in heptane for 100 minutes and 120 minutes. A chart of its permeate flux

was generated along with the previous finding to illustrate the effect of soaking time

(Figure 23).

Figure 23: Scatter plot of permeate flux in heptane for different soaking times at 30 bar

0.00

2.00

4.00

6.00

8.00

10.00

12.00

0 5 10 15 20 25 30 35

Pe

rme

ate

flo

wra

te (

Lmh

)

Time (min)

Permeate Flux - Heptane

30 min

60 min

90 min

100 min

120 min


It was found that there was a decreasing trend of the permeate flux as a function of

soaking time in heptane. Based on the observation, it can be seen that the membrane that

had been immersed in heptane for 120 minutes resulted in the highest permeate flux. Such

occurrence was not expected, as the previous trial experiments did not match with the

findings that suggested the longer the soaking time, the more resistive the membrane

could be, that is lower permeate flux.

It was hypothesised that the prolonged contact time with heptane after per-soaking

in DI water had negatively affected the polymeric arrangement of the membrane surface.

However, since there was limited information in regards to the characteristics of the

membrane purchased such as the surface-coated material and the monomers used for

fabricating the membrane, it was hard to correlate the solvent performance with the

membrane characteristics (Kim, Jegal and Lee 2002). It was unclear as to why the filter

membrane behaved in such a way that the permeate flux varied so much under the slight

variation of soaking time. Nonetheless, it could be postulated that the membrane was

‘damaged’ when it was immersed for too long.

Literature review found that the external surface characteristics of PA TFC

membranes are commonly known for its hydrophilicity, meaning PA TFC membranes are

commonly used in aqueous applications. In order to increase its permeability of nonpolar

solvents, its surface properties needed to be modified via surface chemistry to increase its

hydrophobicity (Jimenez Solomon, Bhole and Livingston 2013).

3.4.3 Permeating a binary solution of squalene and heptane

Having studied the effect of permeating heptane using the Duracid membrane, the

experiment further investigated the effect of permeating squalene in heptane solution to

examine the potential for solvent separation. Similar to permeating heptane, preliminary

tests showed that no permeate was observed when 1%, 3% and 5%v/v squalene solution

(heptane as solvent) was charged in the stirred cell at a pressure of 20 bar. Therefore, the


applied pressure was increased from 20 bar to 30 and 50 bar. A set with no squalene in the

feed solution, labelled as ‘Control’, was included to serve as a control variable.

3.4.3.1 Permeating squalene-heptane solution at 30 bar

Figure 24 and Figure 25 show the filtration performance of the filter membranes

operated at 30 bar. Its respective soaking time in heptane had been labelled accordingly.

Figure 24: Scatter plot of cumulative permeate volume for different squalene concentrations at 30 bar

It can be seen that 3% v/v squalene yielded the highest cumulated permeate

volume among all the experiment sets, as shown in Figure 24. The final permeate volume

from permeating 3% v/v squalene was almost three times as much as that of the control

(8.8 mL from 3% v/v compared with 3.4 mL from control). Such significant difference

could be noted from the pre-soaking time in heptane solution. As indicated, the membrane

used for permeating 3% v/v had soaked for the longest time among them all, almost 6

hours of immersion in heptane solution. It was clear that the filter membrane was soaked

in heptane for too long that the membrane ‘damaged’ and allowed easier permeation.

y = -1E-04x2 + 0.0337x + 0.2323 R² = 0.9894

y = -0.0004x2 + 0.1267x + 0.1793 R² = 0.9995

y = -6E-05x2 + 0.0215x + 0.1196 R² = 0.9909

y = -0.0002x2 + 0.052x + 0.2206 R² = 0.9952

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

9.0

10.0

0 20 40 60 80

Cu

mu

lati

ve v

olu

me

(m

L)

Time (min)

Permeate Volume

1% v/v (3 hr 45 min)

3% v/v (5 hr 50 min)

5% v/v (3 hr 30 min)

Control (heptane only, 1 hr40 min)


Figure 25: Scatter plot of permeate flux for different squalene concentrations at 30 bar

From Figure 25, it can be seen that the permeate flux for permeating 3% v/v was

significantly higher than the other experimental sets and twice as much as the control set.

Several experiments were carried out to test the performance of the filter

membrane when soaked in heptane for a longer time. In general, the membrane cannot be

used after being immersed in heptane for too long. It was found that after an immersion of

over 5 hours, the membrane was damaged from permeating heptane solution. From the

observation, once pressure started to charge into the stirred cell, the membrane was

unable to retain any heptane solution. Similar outcome was observed when the membrane

was reused after its first filtration process.

Regarding the effect of prolonged soaking time in heptane, it can be seen that the

higher the feed concentration, the lower the final permeate volume was (Figure 24). 1%

v/v squalene solution had a lower final permeate volume than that of control, and 5% v/v

squalene had the lowest of them all. Such occurrence was expected mainly due to an

increase in the osmotic pressure in the feed solution, which consequently reduced the

driving force of the nanofiltration. The following equation shows the Van’t Hoff’s equation

that relates osmotic pressure and solute concentration:

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

8.00

9.00

0 20 40 60 80

Pe

rme

ate

flo

w r

ate

(Lm

h)

Time (min)

Permeate flux 1% v/v (3 hr 45 min)

3% v/v (5 hr 50 min)

5% v/v (3 hr 30 min)

Control (heptaneonly, 1 hr 40 min)

3.9 Lmh

1.55 Lmh

1.14 Lmh

0.75 Lmh


Equation 6: Van’t Hoff’s first equation of osmotic pressure relating to solute concentration

Where, Π is the osmotic pressure, is the molar concentration of solute, is the ideal

gas constant, and is the temperature.

From Equation 6, the osmotic pressure increases proportionally as the molar

concentration of squalene increases, provided that pressure remains constant. As such, the

driving force, will be reduced. Hence, the observed permeate

volume and permeate flux for 1% v/v and 5% v/v squalene were lowered comparatively to

the control set.

Equation 7: Expression of driving force with effect to concentration

3.4.3.2 Permeating squalene-heptane solution at 50 bar

A similar procedure from the previous section was carried out for operating the

stirred cell at 50 bar, however, with an exception of the soaking time of the membrane in

heptane for not longer than 4 hours. Figure 26 and Figure 27 show the filtration

performance of the filter membranes operated at 50 bar, labelled with its respective

soaking time in heptane.

In general, higher operating pressure resulted in an increase in final permeate

volume for all of the experimental sets when compared to previous findings. Table 15

illustrates the difference in total permeate volume for each set operated at 30 bar and 50

bar.


Figure 26: Scatter plot of cumulative permeate volume for different squalene concentrations at 50 bar

Figure 27: Scatter plot of permeate flux for different squalene concentrations at 50 bar

Table 15: Comparison of total permeate volume with respect to operating pressure

y = -0.0016x2 + 0.2672x + 0.4165 R² = 0.9982

y = -0.0015x2 + 0.1816x + 0.2333 R² = 0.9976

y = -0.0006x2 + 0.0809x + 0.2624 R² = 0.9926

y = -0.0013x2 + 0.2753x + 0.4089 R² = 0.999

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

0 20 40 60

Cu

mu

lati

ve v

olu

me

(m

L)

Time (min)

Permeate Volume

1% v/v (1 hr 10 min)

3% v/v (3 hr)

5% v/v (2 hr)

Control (heptane only, 30min)

0.00

5.00

10.00

15.00

20.00

25.00

0 10 20 30 40 50 60

Pe

rme

ate

flo

w r

ate

(Lm

h)

Time (min)

Permeate Flux

1% v/v (1 hr 10min)

3% v/v (3 hr)

5% v/v (2 hr)

Control (heptaneonly, 30 min)

30 bar 50 bar Differences by factor

Control (heptane only) 3.4 mL 12.3 mL 3.62

1% v/v 2.5 mL 10.9 mL 4.36

3% v/v 9.5 mL 6.1 mL 0.64

5% v/v 1.6 mL 3.2 mL 2


According to the table above, all the experimental sets (except 3% v/v) showed a

significant increase in total permeate volume when operated at higher pressure. This can

be explained by the fact that increasing applied pressure to the system will increase the

driving force for the filtration process, provided that the osmotic pressure of the solution

stays constant for each solute concentration. For 3% v/v squalene-heptane solution, the

comparison was unable to establish due to the fact that the membrane was damaged for a

longer soaking time, as mentioned previously (Figure 24 and 25). The following equation

illustrates the idea of the aforementioned explanation:

Equation 8: Expression of driving force with effect to applied pressure

Notice that from Figure 26, the ‘Control’ yielded the highest final permeate volume,

which suggested that the decrease in driving force due to an increase in osmotic pressure

in the feed solution was consistent. Furthermore, since the membranes did not soak in

heptane for more than 4 hours, the permeance results showed a consistent performance in

accordance with the effect of pressure and squalene concentration increase.

3.5 GCMS results

Upon review on the permeance of squalene-heptane solution, it is crucial to

perform a rejection test using the results obtained from GCMS analysis to determine

whether the membrane can separate squalene from the heptane solution.

3.5.1 Permeating squalene-heptane solution at 30 bar

A graphical representation of the GCMS results from the nanofiltration performed

at 30 bar is shown in Figure 28.

From the chemical analysis, it showed that the membrane did not separate

squalene from the feed solution successfully. The peak area of squalene detected from

GCMS analysis for the feed (Before NF) and the permeate (After NF) did not produce a


significant solute rejection due to its similarities. Its respective rejection value was

calculated using Equation 5 and Table 16 summarises the outcome of the nanofiltration

process.

Figure 28: Scatter plot of GCMS results for different squalene concentration at 30 bar

Table 16: Summary of the nanofiltration process outcome operating at 30 bar

From the table above, it was noted that the squalene-heptane concentration of

3% v/v yielded the highest rejection value among them all. Referring to previous findings

(Figure 24 and Figure 25), when permeating 3% v/v squalene-heptane solution with the

filter membrane pre-soaked for 5 hours 50 minutes, the permeate flux was the highest.

Here, the GCMS results showed its rejection value was the highest as well. Thus, this

suggested that higher permeate flux resulted in higher rejection value. However, according

1.0

3.0

5.0

0.0

50,000,000.0

100,000,000.0

150,000,000.0

200,000,000.0

250,000,000.0

300,000,000.0

350,000,000.0

400,000,000.0

0.0 1.0 2.0 3.0 4.0 5.0 6.0

Pe

ak a

rea

of

squ

ale

ne

Concentration of squalene-heptane solution (% v/v)

Conc. Before & After NF

Before NF

After NF

Concentration

Peak area of

squalene in Feed

(Before NF)

Peak area of

squalene in

Permeate (After NF)

Rejection

value

Permeate

flux

1.0% v/v 163,417,513 161,493,759 1.2% 1.14 Lmh

3.0% v/v 286,497,258 264,489,450 7.7% 3.90 Lmh

5.0% v/v 333,965,981 315,256,960 5.6% 0.73 Lmh


to Darvishmanesh et al. (2011), they found that using a hydrophobic membrane

manufactured from SOLSEP, higher permeate flux of oil-hexane solution did not result in

higher oil rejection, but instead a relatively constant rejection value was shown for 10%,

20% and 30% w/w oil concentration. It was unclear as to why high permeate flux could

result in higher rejection value.

Nonetheless, from the GCMS results, it can be concluded that the filter membrane

used did not perform well in separating squalene from heptane solution due to such poor

rejection value (less than 10%).

3.5.2 Permeating squalene-heptane solution at 50 bar

Similarly, a scatter plot of GCMS results for the nanofiltration performed at 50 bar

had been generated and it can be referred to Figure 29.

Figure 29: Scatter plot of GCMS results for different squalene concentration at 50 bar

A similar trend can be observed from Figure 29 when compared to Figure 28. As

observed, the membrane did not appear to be separating squalene from the feed solution

as the peak area of squalene from the feed (Before NF) yielded similar results to the

1.0

3.0

5.0

-

10,000,000.00

20,000,000.00

30,000,000.00

40,000,000.00

50,000,000.00

60,000,000.00

0.0 1.0 2.0 3.0 4.0 5.0 6.0

Pe

ak a

rea

of

squ

ale

ne

Concentration of squalene-heptane solution (% v/v)

Peak Area vs Conc. Before & After NF

Before NF

After NF


permeate (After NF). Its corresponding rejection value had been computed, Table 17,

showing a similar trend from Table 16, with an exception of the minor difference in

rejection value.

Table 17: Summary of the nanofiltration process outcome operating at 50 bar

Likewise, permeating 3% v/v squalene-heptane solution yielded the highest

rejection value of 6.1%. According to the permeate flux profile on rejection value, both

parameters did not show any correlation to describe the effect of solute concentration to

the rejection value. According to Darvishmanesh et al. (2011), it was demonstrated that

increasing oil concentration decreased the permeability of TFC membrane, while the

retention of the membrane stayed constant over 10%, 20% and 30% w/w oil

concentration. It was not clear as to why the results of the rejection value to squalene-

heptane concentration were inconsistent with Darvishmanesh.

However, similar to the outcome from previous section (Section 3.5.1 and 3.5.2),

the separation performances for permeating 1.0 %, 3.0 % and 5 % v/v squalene-heptane

solution were not successful due to the low rejection value (less than 10%). One of the

possible explanations for the low rejection value could be due to membrane swelling.

Heptane, being a non-polar solvent, could have been repelled due to the hydrophobic

interaction with the Duracid membrane, causing surface repulsion, presuming the

membrane surface has a hydrophilic characteristic (Farid 2010). It was postulated that

when the membrane swelled, the polymer chains that make up the membrane structure

were stretched due to surface repulsion from the hydrophobicity from heptane

(Tarleton, Robinson and Salman 2006). As a result of that, free volume in the space

Concentration Peak area of squalene

in Feed (Before NF)

Peak area of

squalene in

Permeate (After NF)

Rejection

value

Permeate

flux

1.0% v/v 7,318,756 7,239,073 1.1% 7.74 Lmh

3.0% v/v 35,944,452 33,744,414 6.1% 4.18 Lmh

5.0% v/v 56,160,475 53,896,920 4.0% 2.19 Lmh


between the polymers increased, therefore, increased solvent permeability and lowered

rejection.


3.6 Summary of the findings

To sum up, based on the observations from permeating DI water, heptane and

squalene-heptane, it can be concluded that Duracid membrane was, in fact, a hydrophilic

membrane due to its high permeability in DI water. Because of its membrane nature,

Duracid membrane did not show consistent permeance for both heptane and squalene-

heptane solution. One of the factors that could cause a variance in results was due to

heptane being a non-polar solvent and hydrophobic to the Duracid membrane.

Consequently, this could lead to surface repulsion on the Duracid membrane. Another

factor was due to membrane swelling; an occurrence where the free volume in between the

polymer that made up the membrane structure was occupied by heptane molecules, hence

restricting permeability and selectivity. From the GCMS result, a maximum rejection value

of 6 % was achieved, which suggested that the Duracid membrane had retained only 6 % of

squalene in the heptane solution. With all the evidence putting together, it was concluded

that Duracid membrane was not suitable for separating this non-polar organic-

hydrocarbon system and the membrane will be ‘damaged’ when come into contact with

heptane for too long.


4 Conclusion

With vast amounts of research and development being conducted around the

necessity to provide improvements in the current commercial scale algae fuel production

process, the limited research on the SRNF application have restricted the growth of more

eco-friendly and efficient algae fuel production. It was the aim of this thesis to investigate

an alternative technique of separating microalgal hydrocarbon from a biocompatible

solvent, in particular, heptane. Its secondary objective also included an investigation of the

efficiency for operating a chemical process separating the mixture of hydrocarbon and

organic solvent using a computer simulation. Through experimentation, model simulation

and simultaneous literature review, this report has revealed results that could be useful for

future work as a reference and serves as a starting point for further development.

To evaluate the thermodynamic feasibility of the commercial algae fuel production,

Aspen Plus was employed to model a separation process using two types of unit

operations, namely flash separator and distillation column. After several modifications to

the original proposal, the effect of thermodynamic property methods and optimisation

using sensitivity analysis, a heat duty required to carry out the process had been computed.

Upon conducting preliminary energy balance around the simulation, it was found that the

conventional method was not feasible as the process was not able to sustain itself.

However, the simulation was able to achieve at least 99.98% heptane recovery and attain

100% hydrocarbon recovery. Further modelling will be required to implement effluent

recycle to achieve an outcome that could provide positive energy output, as well as to seek

for an alternative way to extract algae fuel and concentrate the extraction more efficiently.

Having proved that separation via phase change is not energetically efficient, an

alternative technology of implementing nanofiltration was carried out. Since no

information in regards to the materials made for the membrane purchased was disclosed,

it was hard to correlate its nanofiltration performance with the effect of solvent contact

time. However, it was found that the membrane was not suitable for permeating non-polar

solvent, and the permeance was greatly correlated to the solvent soaking time. Some


plausible reasons had been proposed including the effect of polarity and the occurrence of

membrane swelling. The chemical analysis also did not show any positive results, which

the membrane only accounted for a maximum solute rejection value of 6 %. Even though

such rejection value was low compared to literature value for implementing different types

of nanofiltration membrane, it is still a relatively useful piece of finding that shows

nanofiltration in the organic phase is possible. In spite of the limited convincing finding

that could show membrane filtration is better than other concentration methods,

undoubtedly, more work and in-depth research are needed to develop further in favour to

the algae fuel production.

4.1 Recommendations for future work

1. Given the findings obtained from the NF experiments were not positive, it is necessary

to seek out for some other membrane manufacturers to provide the appropriate

membrane for the investigation. Some membrane manufacturers had been found

during the literature review, and these are summarised in Table 18.

Table 18: Different Solvent Resistant Nanofiltration and Their Properties Provided by its Respective Manufacturers (Othman et al 2009; Sterlitech 2015; Evonik 2015).

Membrane

type Manufacturer

Membrane

class Polymer Type

Pore Size,

MWCO

Tmax,

°C

pH

Tolerance

Desal-DL GE Osmonics - Polyamide 150-300 90 2-11

Desal-DK GE Osmonics - Polyamide 150-300 90 2-11

MPF-34 Koch Dense PDMSb 200 40 0-14

MPF-44 Koch Dense PDMSb 250 40 3-10

STARMEMTM

120 METa

Dense Polyimide 200 50 -

NF30 Nadir Dense Polyethersulfone 400 - -

STARMEMTM

122 METa

Semi-

porous Polyimide 220 50 -

DURAMEM® Evonik - P84® polyimide 150-900 50 -

a Membrane Extraction Technology, London, UK.; b Polydimethylsiloxane.


2. Given the modelling aspect did not yield a positive energy output that could allow the

chemical process to sustain itself, some techniques had been proposed to improve the

separation process. This includes

i. Due to a dilute mixture of squalene in the feed stream, it is necessary to

implement a recycle stream by recirculating bottom stream from either flash

separator or distillation column back to the feed stream to increase the squalene

concentration. This could reduce the amount of heating energy to vaporise

heptane from the feed stream and yield a better squalene recovery.

ii. A separation unit operator ‘Extract’ could be used for the solvent extraction

process to further development the solvent extraction process prior to the

solvent separation process. The mass and energy balance obtained for the overall

extraction and separation process could be used for performing a techno-

economic assessment to determine its feasibility.

3. Future research on ways to synthesise solvent resistant membrane could be another

recommendation for future work if no appropriate membrane could be found

(Darvishmanesh, Degrève and Van der Bruggen 2009; Jimenez Solomon, Bhole and

Livingston 2013; Lau et al. 2012; Tarleton, Robinson and Low 2009). This provides the

user to selectively choose the right materials to fabricate the membrane via a technique

called interfacial polymerization (IP). Extensive literature review, consultation with the

vendor for the appropriate materials must be carried out. Equipment used for the

process must also be considered, and help must be sought.

4. Two membrane technologies can also be researched on to determine its viability for

the purpose of solvent separation in a biological system. Technologies which includes:

i. Membrane distillation – a thermally driven separation that is enabled due to

phase change. A hydrophobic membrane is used as a barrier for the liquid phase,

allowing the vapour phase (e.g. water vapour) pass through the membrane's

https://en.wikipedia.org/wiki/Membrane

https://en.wikipedia.org/wiki/Liquid_phase


pores. The difference in partial vapour pressure is the driving force of the

process, which is commonly triggered by a temperature difference

(Drioli, Ali and Macedonio 2015). However, one of its limitations for utilising

membrane distillation is that the process solution must be aqueous

(Lawson and Lloyd 1997). Another limitation is that the solution should not be

too concentrated (Lawson and Lloyd 1997).

ii. Pervaporation (or pervaporative separation) – a membrane process for mixture

of liquids by partial vaporisation through a polymeric or zeolite membrane

(Feng and Huang 1997). When the membrane is in contact with a liquid mixture,

one of the components from the mixture can be selectively removed due to its

faster diffusivity in the membrane. Consequently, the permeable species in the

permeate side can be concentrated, similar to the less permeable species in the

feed (Shao and Huang 2007). It is considered to be a promising alternative

membrane separation technology as it is economical, safe and ecofriendly

(Smitha 2004). This technology separates liquid organic mixtures via three major

methods: dehydrating aqueous-organic mixture, removing trace volatile organics

from aqueous solution, and separating organic-organic solvent mixture

(Smitha 2004). Its application includes removal of organic solvents from

industrial waste effluent and purification of organic solvent ("Introduction To

Pervaporation And Vapor Permeation" 2016).


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Appendixes

Appendix A: Feed Composition Calculations

The following spreadsheet was developed to facilitate the feed composition calculations

DW 0.89 g/L *From Navid et al 2013b total oil % 30% of DW *From Navid et al 2013b

HC % 49% of total oil % *From Navid et al 2013b

HC % 14.7% of DW

HC 0.13083 g/L HC = hydrocarbon, assuming all of them are bot-oil

ρ of bot-oil 835 g/L

if culture volume 1000 mL Algae 0.89 g DW

HC 0.13083 g DW HC 0.156683 mL

liquid content 99.94%

*From Schnurr et al 2013 Solid content 0.06%

*From Schnurr et al 2013

ρ of fresh water 1000 g/L liquid content 999.4 g Based on the liquid content and the cell density (DW)

For every 1L culture

heptane 200 mL Based on 1:0.2 ratio (Culture:heptane) ρ of heptane 684 g/L

heptane 136.8 g

HC 0.10 % heptane 99.90 % 100 %

Figure 30: A spreadsheet of feed composition calculation


Appendix B: Aspen Plus Program Input Setups

Appendix B.1: Input Entry for flash separator and distillation column in the

Initial Stage of Separation Process

The input entry for FS and DC can be made by going under the ‘Blocks’ tab. As

mentioned previously, the reflux ratio for this simulation was set at 1 initially and the

column pressure profile was set to 1 bar. For the purpose of extracting heptane from the

mixture stream, the main component to be separated should be heptane under ‘Feed basis’.

The following figure shows the overall input specification that needed to be entered in the

RADFRAC column.

Figure 31: Input requirements for ‘FLASH’ column under Specification tab

Figure 32: Input requirement for ‘RADFRAC’ column under Configuration tab


Figure 33: Feed and component input requirement for ‘RADFRAC’ column under Feed Basis

Figure 34: Input requirement for ‘RADFRAC’ column under Streams tab


Appendix B.2: Setting Change on Thermodynamic Property Method

Setting change on thermodynamic property method can be done by selecting the

method that is desired under ‘Global’ tab in ‘Properties’ section in Data Browser. This is can

be seen by referring it to Figure 43. Notice that property methods such as NRTL and

UNIFAC can be changed just by clicking the drop box on ‘base method’.

Figure 35: Setting Change on Thermodynamic Property


Appendix B.3: Input Entry for Sensitivity Analysis on ‘FLASH’ Temperature

A sensitivity test was created under ‘Model Analysis Tools’, with the sets of inputs

that needed to be filled in, such as the manipulated variable, its type and the manipulated

variable limits. Figure 44 and Figure 45 show the input requirement for the sensitivity

analysis.

Figure 36: Sensitivity analysis input requirement for flash separator temperature in ‘FLASH’ model

Figure 37: Variable definition and input requirement for flash separator sensitivity analysis outputs in ‘FLASH’ model


Appendix B.4: Input Entry for Sensitivity Analysis on ‘RADFRAC’ Reflux Ratio

and Molar Ratio of Distillate to Feed Flow Rate

Firstly, to optimize the reflux ratio, a sensitivity test was created under ‘Model

Analysis Tools’, with the sets of inputs that needed to be filled in. Figure 46 and Figure 47

shows the input requirement for the sensitivity analysis.

Figure 38: Sensitivity analysis input requirement for ‘RADFRAC’ reflux ratio

Figure 39: Variable definition and input requirement for ‘’RADFRAC’ sensitivity analysis outputs


Next, the molar ratio of distillate to feed flow rate (MRDF) was optimized using a

‘Model Analysis Tools’. The following figures show the input requirement for the sensitivity

analysis.

Figure 40: Sensitivity analysis input requirement for ‘RADFRAC’ MRDF

Figure 41: Variable definition and input requirement for ‘’RADFRAC’ sensitivity analysis outputs



The following figures show the sensitivity analysis input requirement parameters

for the second flash tank in ‘FLASH’ model.

Figure 42: Sensitivity analysis Input requirement for 'FLASH2' reactor temperature in ‘FLASH’ model

Figure 43: Variable definition and input requirement for ‘FLASH2’ tank sensitivity analysis outputs in ‘FLASH’ model


Next, the reactor temperature for ‘RADFRAC’ model was optimized using a ‘Model

Analysis Tools’. The following figures show the input requirement for the sensitivity

analysis.

Figure 44: Sensitivity analysis Input requirement for 'FLASH2' reactor temperature in ‘’RADFRAC’ model

Figure 45: : Variable definition and input requirement for ‘FLASH2’ tank sensitivity analysis outputs in ‘’RADFRAC’ model



The following figures show the input parameters for ‘1SQUAL’ stream in both

‘FLASH’ and ‘RADFRAC’ model.

Figure 46: Input requirements for stream ‘1SQUAL’ for water content variable


Appendix C: HP4750 Stirred Cell Features and Specifications

The following summarises the essential features and technical specification of the HP4750

Stirred Cell that is made by Sterlitech Corporation.

Table 19: HP4750 Features and Technical Specifications (Sterlitech 2015)

Parameter Description

Membrane size 47 to 49 mm diameter

Active membrane area m2 (43.12 mm diameter)

Processing Volume 300 mL

Hold-up volume 1 mL

Maximum Pressure 69 bar (69000 kPa or 1000 psig)

Maximum Temperature 121 °C (250 °F) @ 55 bar (55000 kPa or 800 psig)

pH range Membrane dependent

Connections:

Permeate Outlet

Pressure Inlet

1/8-inch diameter 316L SS tubing

¼ inch FNPT

Wetted materials of construction:

Cell Body

O-rings

Gaskets

Stir Bar

316L stainless steel

Buna-N

Buna-N

PTFE-coated magnet

Dimensions:

Cell Body diameter

Cell Top width*

Cell Bottom width*

Cell height

Assembled weight

5.1 cm

10.2

13.3

22.1

2.72 kg

Autoclavable Yes

* Measurement included assembling with clamp/coupling


Appendix D: HP4750 Stirred Cell Components

The HP4750 Stirred Cells was shipped with the following components and the complete set

can be referred as Figure 30.

Figure 47: HP4750 parts and components (Sterlitech Corp 2015)

1. Stainless steel cell body 2. Cell top 3. Cell bottom 4. Cell top coupling 5. Cell bottom coupling 6. Porous stainless steel membrane support disk 7. Two O-rings 8. Top gasket 9. Permeate tube 10. Stir bar assembly 11. Stir bar retriever


Appendix E: HP4750 Stirred Cell Assembly

The following figures illustrate the procedure on how to assemble the stirred cell

appropriately:

1. O-ring insertion:

Ensure that the O-rings were wetted with the fluid to be processed and the

insertion was properly fitted in the grooves

Figure 48: Outer O-ring (left) and inner O-ring (right) insertion

2. Membrane and porous membrane support disk insertion:

Ensure that the active side of the membrane, which usually have a shiny, coated

surface, facing toward the cell reservoir, while a dull side facing the other way

Followed by the stainless steel porous membrane support disk being placed on

top of the membrane to hold it in place.

Figure 49: Membrane (left) and porous membrane support disk (right) insertion

3. Cell Bottom and bottom clamp assembly:

Ensure that the alignment between the Cell Bottom and Cell Body is properly

done by fitting the circular ridge on the Cell Body onto the circular groove on the

Cell Bottom

Ensure that the high pressure coupling is properly tighten using the appropriate

wrench

Figure 50: Cell Bottom fitting (left) and high pressure coupling assembly (right)


4. Permeate Tube assembly and Stir Bar insertion:

Ensure that the Permeate Tube is tighten using the appropriate wrench

Ensure that the Stir Bar is lowered into the cell body using the Stir Bar Retriever,

preferably not dropping it. After the Stir Bar is in place, the feed solution can be

poured in and filtered out upon assembly completion.

Figure 51: Permeate Tube assembly (left) and Stir Bar insertion (right)

5. Cell top insertion and top clamp assembly:

Ensure that the gasket and the Cell Top are fitted accordingly

Ensure that the high pressure coupling is properly tighten using the appropriate

wrench

Figure 52: Gasket assembly (left), Cell Top installation (middle) and high pressure assembly (right)

6. High pressure hose and pressure regulator connection:

A thermoplastic, non-conductive 7N Series 6.4 mm Swagelok hose was attached

to the fitting on the Cell Top, connecting the other end of the hose to Victor

CutSkill® TPR250 ¼’’ flare fitting pressure regulator using the appropriate

wrench

Figure 53: High pressure hose attachment (left) and pressure regulator connection (right)


The pressure regulator was then assembled on an industrial grade nitrogen gas

cylinder, which was purchased from BOC Gases. A Permeate Collection Vessel was placed

under the Permeate Tube and the stirred cell was placed on a magnetic stirrer.

Before commencing any filtering process, the membrane was pre-conditioned by

gradually pressurizing the stirred cell to check for leaks and to ensure consistent

performance. Once the filtration process had been completed, the pressure source was

turned off and the stirred cell was depressurized by opening the pressure discharge port

slowly via the relief valve. It was highly recommended not to depressurize the stirred cell

by loosening the coupling, as it would cause sudden burst upon opening the stirred cell.

Once the stirred cell was depressurized to ambient pressure, the cell was emptied,

cleaned with heptane and dried with paper towel. Upon reviewing the choice of the

appropriate cleaning regime for the stirred cell from the HP4750 Operation Manual

(Sterlitech Corp 2015), it was found that n-heptane was chemically compatible to the

material used for gasket and O-rings.

As a safety precaution, during the assembly, operation and cleaning processes, the

stirred cell was kept in a fume hood to ensure no heptane vapour escaped into the

environment.

Figure below illustrates the schematic view of the HP4750 Stirred Cell system:


Figure 54: HP4750 System Configuration (Sterlitech 2015)


Appendix F: GC-MS Method Parameters

Model used in the GC-MS chemical analysis:

GCMS-QP2010S Gas Chromatograph-Mass Spectrometer

GC-2010 Gas Chromatograph

AOC-20i+S Auto Injector and Auto Sampler

The following tables summarise the method parameter used for the chemical analysis of

the feed and permeate solution:

Table 20: GC-2010 Gas Chromatograph parameters


Column Oven Temperature 220.0 °C

Injection Temperature 300.0 °C

Injection Mode Split

Flow Control Mode Linear Velocity

Pressure 118.9 kPa

Total Flow 54.0 mL/min

Column Flow 1.0 mL/min

Linear Velocity 38.9 cm/sec

Purge Flow 3.0 mL/min

Split Ratio 50.0

High Pressure Injection Off

Carrier Gas Saver Off

Splitter Hold Off

Oven Temperature Program

Rate Temperature (°C) Hold Time (min)

- 220.0 1.00

2.00 260.0 1.00

External Wait No

Equilibrium Time 3.0 min

Table 21: MS Mass Spectrometer parameters


Start Time 1.50 min

End Time 11.00 min

ACQ Mode Scan

Event Time 0.50 sec

Scan Speed 2000

Start m/z 45.00

End m/z 1000.00


Table 22: GCMS-QP2010 Gas Chromatograph-Mass Spectrometer parameters


Ion Source Temperature 200.0 °C

Interface Temperature 200.0 °C

Solvent Cut Time 1.00 min

Detector Gain Mode Relative

Detector Gain 0.00 kV

Threshold 1000

Table 23: AOC-20i/S Auto Injector and Auto Sampler parameters


No. of Rinses with Pre-solvent 3

No. of Rinses with Solvent (post) 3

No. of Rinses wit Sample 2

Plunger Speed (Suction) High

Viscosity Comp. Time 0.2 sec

Plunger Speed (Injection) High

Syringe Insertion Speed High

Injection Mode Normal

Pumping Times 5

Injection Port Dwell time 0.3 sec

Terminal Air Gap No

Plunger Washing Speed High

Washing Volume 8 µL

Syringe Suction Position 0.0 mm

Syringe Injection Position 0.0 mm

Solvent Selection Only A

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