REMOTE DETECTION NMR IMAGINGOF CHEMICAL REACTIONS ANDADSORPTION PHENOMENA

ANNE SELENT

NMR Research UnitUniversity of OuluFinland

Academic dissertation to be presented with the assent of the Doctoral Training Committeeof Technology and Natural Sciences of the University of Oulu for public discussion in theAuditorium L10, Linnanmaa, on November 24th, 2017, at 12 o’clock noon.

REPORT SERIES IN PHYSICAL SCIENCES Report No. 115OULU 2017 • UNIVERSITY OF OULU

OpponentProfessor István Furó, KTH School of Chemical Science and Engineering, Sweden

ReviewersProfessor Patrick Giraudeau, University of Nantes, FranceDoctor Nikolaus Nestle, BASF SE, Germany

CustosDocent Ville-Veikko Telkki, University of Oulu, Finland

ISBN 978-952-62-1704-8 (Paperback)ISBN 978-952-62-1705-5 (PDF)ISSN 1239-4327Juvenes PrintOulu 2017

Selent, Anne: Remote Detection NMR Imaging of Chemical Reactions and Adsorp-tion PhenomenaNMR Research Unit, University of Oulu, P.O. Box 3000, FI-90014University of Oulu, FinlandReport Series in Physical Sciences No. 115 (2017)

Abstract

The subject of this thesis is the characterization of chemical reactions and adsorptionby means of remote detection (RD) method of nuclear magnetic resonance (NMR). Thethesis consists of three related topics: In the first one, novel RD NMR based methods forcharacterizing chemical reactions were presented. In the second topic RD NMR methodswere used to study the performance of new kind of microfluidic reactors. The third projectconcentrated on the development of a novel way to quantify the adsorption of flowing gasmixtures in porous materials. Even though all the topics cover quite different areas ofresearch, they have few common nominators: remote detection NMR, microfluidics andmethod development.

Microfluidic devices are of interest for many areas of science (such as molecular biology,disease diagnosis, chemistry) as they offer great promises for future technologies. Smalldimensions enable, among many other things, the benefits of small sample volumes, largesurface to volume ratio, efficient heat exchange and precise control of flow features andchemical reactions. The efficient evolution of microfluidic processes requires also thedevelopment of new innovative ways to characterize the performance of microfluidicdevices. In this work, remote detection NMR is utilized for the purpose. RD is a methodwhere the encoding and detection of information are separated physically. In many cases,the encoding and detection are performed with two separate RF coils while a fluid ispassing through the studied system.

In the first part of the thesis work, we introduced the concept of remote detection ex-change (RD-EXSY) NMR spectroscopy. We demonstrated that the RD-EXSY method canprovide unique chemical information. Furthermore, the time-of-flight (TOF) information,which is a natural side product of the experimental setup used, can be converted intoindirect spatial information, showing the active reaction regions in a microfluidic device.Additionally, we demonstrated that by applying the principles of Hadamard spectroscopyin the encoding of the indirect spectral dimension we were able to produce with highefficiency RD-EXSY TOF images with direct spatial information. This allows even moreaccurate characterization of the active regions.

The second topic concentrates on the development of microfluidc hydrogenation reactors.In the project atomic layer depositon (ALD) method was used for the first time to depositboth catalyst nanoparticles and support material on the surface of wall-coated microreactors.As a model reaction continuous flow propene hydrogenation into propane was studiedby means of remote detection NMR. Reaction yield, mass transport phenomena and theactivity of the catalyst surface were determined from the RD NMR data.

Thirdly we presented a novel method for gas adsorption measurements in porousmaterials using RD TOF NMR. Traditional adsorption measurements are carried out atstatic conditions for a single gas component, as multi-component adsorption measurementsare challenging and time-consuming. We investigated adsorption of continuously flowing

propane and propene gases as well as their mixture in packed beds of mesoporous materials.The unique time-of-flight information obtained using the RD NMR method was utilized inthe determination of flow velocity, which was then converted into amount of adsorbed gas.

Keywords: nuclear magnetic resonance spectroscopy, magnetic resonance imaging, remotedetection, flow, microfluidic, lab-on-a-chip, porous materials, adsorption, hydrogenation.

To Marcin and Emilia

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My sunshine in the rain

Acknowledgements

The work presented in this thesis was carried out in the NMR research unit at the Universityof Oulu, Finland. I would like to thank the former head of Department of Physics, ProfessorEmeritus Jukka Jokisaari, his successor, late Professor Matti Weckström, the present leaderof the NMR research unit, Professor Juha Vaara, and the head of the experimental subgroup,Docent Ville-Veikko Telkki, for placing the facilities at my disposal.

I gratefully acknowledge the financial support given by the Graduate School of Compu-tational Chemistry and Molecular Spectroscopy (LASKEMO), Oulu University PharmacyFoundation and Tauno Tönning Foundation. The University of Oulu Graduate School(UniOGS) and University of Oulu Academics (OYA) are acknowledged for providingtravel grants.

This thesis would not have been possible without the support and aid from manyindividuals who were directly or indirectly involved in this work. First I would like toexpress my deepest gratitude to my advisor and supervisor Docent Ville-Veikko Telkki,whose mentoring, optimism, patience and immense knowledge has made it feasible for meto complete this thesis. Thank you, Ville.

I wish to emphasize the significant role of Professor Emeritus Jukka Jokisaari for mycareer. It was Professor Jokisaari who offered me the opportunity to work in the NMRresearch unit, while I was just a young woman in high school. I feel deeply privileged forthe trust he gave to me. Additionally to this, together with Ville-Veikko Telkki, professorJokisaari supervised my bachelor and master thesis and I have participated to several NMRcourses kept by him. I am deeply grateful for professor Jokisaari for all the time and efforthe has used to guide me. Thank you, Jukka!

Docent Emeritus Juhani Lounila is also thanked for all the fascinating lectures he hasheld about the theory behind the NMR phenomena. I would like to express my deepestrespect for his devotion to the field.

I am grateful for my follow-up group members docent Wei Cao and doctor SannaKomulainen who were especially nice, cooperative and efficient in their participation.Additionally, I would like to express my appreciation for doctors Sanna Komulainen andPetr Štepánek for evaluating the thesis manuscript before the official reviewers. Yourremarks were most helpful.

The official pre-reviewers, appointed by the University of Oulu Graduate School(UniOGS), professor Patrick Giraudeau and doctor Nikolaus Nestle, are thanked for

their fast, precise and insightful comments. Your statements were very encouraging, andthey gave me lot’s of positive energy for the defence day.

I wish to thank doctor Vladimir Zhivonitko for all the patience, valuable advisesand comments concerning the measurements and data interpretation during the years.Additionally, I wish to acknowledge the help and counseling, which Marcin Selent providedin the construction of the experimental setups.

The group of Professor Sami Franssila from Aalto University is acknowledged for afruitful cooperation. I would like to thank all the co-authors of the articles included in thisthesis: Ville Rontu, Gianmario Scotti, Jarmo Leppäniemi, Sami Franssila, Ville-VeikkoTelkki, Vladimir Zhivonitko and Igor Koptyug.

NMR laboratory manager Anu Kantola and her substitutes Susanna Ahola and Jianfeng(Peter) Zhu are recognized for their priceless help during the moments of despair while Iwas working with the cranky ‘old 300’. The staff of the former workshop of the Physicsdepartment is thanked for the practical solutions concerning issues with the experimentalwork.

The members of the NMR research unit, past and present, are thanked for the inspiringand loving spirit that has ruled in our working environment. I wish to especially thankVille’s angels (Anu, Sanna and Susanna) for all the enjoyable and relaxing evenings wehave spent together. I also want to thank Juha, Juho, Perttu and Ville for keeping the coffeeroom discussions at ’high level’ (especially on Fridays). During my time in the NMRgroup I have had the pleasure to work with many talented individuals and it is impossibleto name you all here. Asad, Awais, Jani, Jarkko, Jirí, Jouni, Matti, Otto, Pekka, Petr, Päivi,Pär, Teemu and all the others, your help and support has been priceless. Thank you all!Last but not least, I wish to express my deepest gratitude for Sanna, with whom I haveshared not only an office and passion for science but also the everyday joys and woes forthe past few years.

I am particularly grateful to my parents and relatives for all their help and supportthroughout my studies and life in general. Mom, dad, Raimo and Tuija thank you for allthe encouragement you have provided. Grandmother Lea: thank you for being a wonderfulexample of a strong independent woman.

All my friends are acknowledged for their support and friendship. Special thanks goesto Katja and Nuha for sharing with me numerous studying and ‘coffee with bun’ moments.

I have been involved with the NMR group for 11 years already and during the time thegroup has not only offered me a place to study and to do research but through it, I havealso discovered the love of my life. You, Marcin, together with our lovely daughter Emilia,have been with me every step of this journey and you have made it both surprising and fun.You two are the main reason I have made it so far. Thank you for everything!

Oulu, November 2017 Anne Selent

List of original papers

The present thesis consists of an introductory part and the following original papers, whichare referred to in the text by their Roman numerals:

I V.-V. Telkki, V. V. Zhivonitko, A. Selent, G. Scotti, J. Leppäniemi, S. Franssilaand I. V. KoptyugLab-on-a-chip Reactor Imaging with Unprecedented Chemical Resolution byHadamard-Encoded Remote Detection NMR.Angewandte Chemie International Edition 53,11289-11293 (2014).

II V. Rontu, A. Selent, V. V. Zhivonitko, G. Scotti, I. V. Koptyug, V.-V. Telkki andS. FranssilaEfficient Catalytic Microreactors with Atomic Layer Deposited Platinum nanopar-ticles on Oxide Support.Chemistry- A European Journal, Accepted version published in electronic formwith the DOI:10.1002/chem.20170339 (2017).

III A. Selent, V. V. Zhivonitko, I. V. Koptyug and V.-V. TelkkiQuantifying the adsorption of flowing gas mixtures in porous materials byremote detection NMR.Microporous and Mesoporous Materials, Accepted version published in elec-tronic form with the DOI:10.1016/j.micromeso.2017.05.040 (2017).

The NMR experiments in Paper I were performed by the author of the thesis together withV.-V. Telkki. Data analysis was performed together with V.-V. Telkki and V. V. Zhivonitko.The group of professor Franssila built the microfluidic reactors used in Papers I and II. Theauthor carried out most of the RD NMR experiments for Paper II in cooperation with V. V.Zhivonitko and V.-V. Telkki. Image processing and the data analysis was done by the authorwith V.-V. Telkki and V. V. Zhivonitko. For Papers II and III the author made the probeand flow system modifications. For Paper III the author performed the sample preparation

and the measurements. Data analysis was be done together with V. V. Zhivonitko and V.-V.Telkki. The manuscript of the Paper I was commented and contributed by the author. Theauthor wrote the initial version of the Paper III and also the initial version of the NMR partfor the Paper II. All manuscripts were prepared as a teamwork.

Contents

AbstractAcknowledgementsList of original papersContents1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141.1.1 Microfluidic reactors . . . . . . . . . . . . . . . . . . . . . . . . 151.1.2 Adsorption . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

1.2 Outline of the thesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162 Nuclear magnetic resonance . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

2.1 Basics of NMR Spectroscopy . . . . . . . . . . . . . . . . . . . . . . . . 182.2 Fine structure of the NMR spectrum . . . . . . . . . . . . . . . . . . . . 20

2.2.1 Chemical shift . . . . . . . . . . . . . . . . . . . . . . . . . . . 212.2.2 Scalar spin-spin coupling . . . . . . . . . . . . . . . . . . . . . . 21

2.3 Relaxation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 222.4 Multidimensional NMR . . . . . . . . . . . . . . . . . . . . . . . . . . 25

2.4.1 Basics of two-dimensional NMR . . . . . . . . . . . . . . . . . . 252.4.2 EXSY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

2.5 Hadamard spectroscopy . . . . . . . . . . . . . . . . . . . . . . . . . . . 292.6 Sensitivity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 302.7 Parahydrogen-induced polarization . . . . . . . . . . . . . . . . . . . . . 31

2.7.1 Spin isomers of molecular hydrogen . . . . . . . . . . . . . . . . 312.7.2 Production of parahydrogen enriched gas . . . . . . . . . . . . . 322.7.3 NMR signal enhancement with parahydrogen . . . . . . . . . . . 34

3 Magnetic resonance imaging . . . . . . . . . . . . . . . . . . . . . . . . . . . 373.1 Basics of MRI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 373.2 Imaging equation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 393.3 Spin-echo imaging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 393.4 Gradient-echo imaging . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

4 Remote detection NMR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 434.1 Principles of RD NMR . . . . . . . . . . . . . . . . . . . . . . . . . . . 434.2 Information carriers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

4.3 Application of RD method to microfluidics . . . . . . . . . . . . . . . . 454.4 Travel time experiment . . . . . . . . . . . . . . . . . . . . . . . . . . . 464.5 Z-encoded time-of-flight imaging experiment . . . . . . . . . . . . . . . 474.6 Multidimensional TOF imaging . . . . . . . . . . . . . . . . . . . . . . 494.7 Indirect RD NMR spectrum . . . . . . . . . . . . . . . . . . . . . . . . . 50

5 Microfluidics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 525.1 Fluid dynamics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52

5.1.1 Viscosity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 525.1.2 Laminar flow . . . . . . . . . . . . . . . . . . . . . . . . . . . . 535.1.3 The Reynolds number . . . . . . . . . . . . . . . . . . . . . . . 535.1.4 The Péclet number . . . . . . . . . . . . . . . . . . . . . . . . . 545.1.5 Poiseuille law . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55

5.2 Microfluidics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 565.2.1 Microfluidic chips . . . . . . . . . . . . . . . . . . . . . . . . . 565.2.2 Using NMR to study microfluidics . . . . . . . . . . . . . . . . . 57

6 Imaging microfluidic chemical reactors with Hadamard-encoded RD NMR (I) . 596.1 Hydrogenation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 596.2 Microreactor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 606.3 Flow system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 616.4 NMR hardware . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 626.5 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64

6.5.1 Two-dimensional TOF imaging . . . . . . . . . . . . . . . . . . 646.5.2 RD-EXSY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 656.5.3 Spatially resolved Hadamard-encoded RD-EXSY . . . . . . . . . 67

6.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 717 Characterization of the catalytic performance of ALD deposited platinum nanopar-

ticles in microfluidic reactors (II) . . . . . . . . . . . . . . . . . . . . . . . . . 727.1 Microfluidic hydrogenation reactor . . . . . . . . . . . . . . . . . . . . 72

7.1.1 Atomic layer deposition . . . . . . . . . . . . . . . . . . . . . . 737.1.2 Piranha treatment . . . . . . . . . . . . . . . . . . . . . . . . . . 74

7.2 Microreactor fabrication . . . . . . . . . . . . . . . . . . . . . . . . . . 747.3 Nanoparticle characterization . . . . . . . . . . . . . . . . . . . . . . . . 747.4 Characterization of the reactor performance . . . . . . . . . . . . . . . . 77

7.4.1 Two-dimensional TOF imaging . . . . . . . . . . . . . . . . . . 777.4.2 Reaction yield . . . . . . . . . . . . . . . . . . . . . . . . . . . 787.4.3 Chips activity based on the first order kinetics . . . . . . . . . . . 827.4.4 Pairwise addition . . . . . . . . . . . . . . . . . . . . . . . . . . 83

7.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 838 Quantifying the adsorption of flowing gas mixtures in porous materials (III) . . 85

8.1 Adsorption on porous materials . . . . . . . . . . . . . . . . . . . . . . 858.2 NMR adsorption measurements . . . . . . . . . . . . . . . . . . . . . . 878.3 Remote detection NMR of gas adsorption . . . . . . . . . . . . . . . . . 888.4 Samples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 898.5 Measurements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91

8.5.1 Experimental setup for the RD NMR measurements . . . . . . . 918.5.2 Adsortion measurements with RD NMR . . . . . . . . . . . . . . 92

8.5.3 Reference adsorption experiments . . . . . . . . . . . . . . . . . 938.6 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93

8.6.1 Single gas adsorption results . . . . . . . . . . . . . . . . . . . . 938.6.2 Competitive gas adsorption results . . . . . . . . . . . . . . . . . 95

8.7 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 959 Summary and conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97Original papers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107

1 Introduction

1.1 Background

The subject of this thesis concerns with the characterization of chemical reactions andadsorption by means of remote detection (RD) method of nuclear magnetic resonance(NMR) spectroscopy. The NMR phenomenon was first introduced in the early 1940’s bytwo groups: Purcell, Torrey and Pound reported their experiments in December 1945 [1]and almost simultaneously in January of 1946 [2], but independently, a group consisting ofBloch, Hansen and Packard had reported a measurement of an NMR spectrum of water.The importance of the findings done by these two groups was emphasized as the Nobelcommittee awarded the Nobel Price in Physics in 1952 for both Bloch and Purcell ”for theirdevelopment of new methods for nuclear magnetic precision measurements and discoveriesin connection therewith”.

During the following years NMR spectroscopy has proven to be an important toolfor chemists, biochemists, physicist and engineers who are studying the structures andproperties of matter, chemical reactions, etc. The method is versatile, non-destructive andnon-invasive, and it can be applied to all forms of matter (gas, liquid and solid). However,probably the most well known application of the phenomena for the general public is themagnetic resonance imaging (MRI) used in modern medical diagnostics as it offers a great,non-invasive way to study the structure of a human body as well as the functionality ofbrains. The invention of MRI dates back to the 1970’s when Lauterbur [3] and Mansfieldpresented their ground-breaking ideas. Their contribution to medicine was acknowledgedin the form the Nobel Price in Medicine in 2003 ”for their discoveries concerning magneticresonance imaging”.

Even though the NMR effect has quite a notable history and it is proven to be oneof the most information rich spectroscopic techniques, the field is still progressing andthere is space for new innovative experiments. In this thesis the novel method of remotedetection NMR/MRI is utilized. RD is a signal detection scheme developed for NMRand MRI experimental setups by the group of Alexander Pines at University of California,Berkeley [4, 5]. In the RD setup the encoding of NMR or MRI information about thestudied system is physically separated from the a detection of the signal. Typically, thesesteps are performed with two different radio frequency (RF) coils. The sample itself isstationary and only the information encoded into the magnetization of a carrier fluid is

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moving from the encoding coil to the detector. This approach offers means to overcomethe inherent weak point of NMR, low sensitivity. In some cases, RD has proven to yield upto 103 times better signal to noise ratio (SNR) than is achievable with traditional NMRsetup.

1.1.1 Microfluidic reactors

Microfluidic devices have raised interest in many areas of science, medicine and industryin the last decade. Microfluidics deal with the control and manipulation of fluids inchannels with dimensions below one millimeter. [6] Small dimensions enable, for example,small sample volumes, large surface to volume ratio, efficient heat exchange and precisecontrol of flow properties and chemical reactions. These and many other features are whymicrofluidics offers great promises for future technologies. However, to enable precise fluidhandling, accurate knowledge of the flow properties inside these devices is needed. Variousdetection methods are already in use for this purpose but currently, most microfluidic flowmeasurements rely on optical detection, which requires optically transparent devices andinjection of tracers. NMR is an ideal non-invasive sensor that can give versatile informationabout the reaction and the reactor itself without the need of tracers or opaque devices.However, due to the low sensitivity of the NMR method the study of microfluidic devicesis quite challenging. The small volume of the channels compared to the whole volumeof the microfluidic chips causes low filling factor for the traditional NMR imaging setupas the NMR coil surrounds the whole device. One possible solution to this problem isminiaturization as the coils get more sensitive with decreasing diameter [7]. There arenumerous ways, how the miniaturization can be implemented, e.g. planar microcoils [8],microfluidic striplines [9], microcoils [10], surface coils [11] can be used.

The versatile toolbox offered by NMR can be also used for characterization of microflu-idic devises and related phenomena if the sensitivity is boosted with the remote detectionmethod. In this thesis work we demonstrated that the idea of traditional chemical exchangespectroscopy (EXSY) can be implemented to remote detection setup to acquire accurateinformation about active regions inside the reactor. Additionally, it can be used to followthe reaction pathways and intermediate products in the chip.

Microfluidic reactors are of interest for many industrial processes where catalysts areemployed. As there is a growing demand for sustainability in the world with limitedresources, the aim is to use noble metal catalysts in the most efficient way and to producea minimal amount of waste. Even the most basic reactions like hydrogenation can stillbe improved and one way to do so is to go towards microfluidic solutions. However,the sustainability may become an issue if the microfluidic processes are scaled up bynumbering up the amount of reactors. While one chip may be economical and ecologicalto use as compared to normal laboratories, it might not be any more these things in largerscale reactions e.g. due to the amount of energy which is needed to heat or cool eachreactor separately.

There are many new ideas for the production of microfluidic hydrogenation reactors.With this, there is a demand for novel ways to study and compare the activity of the designs.The usability of NMR in this type of studies was demonstrated in the thesis. New type of

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reactors were manufactured by using Atomic layer deposition (ALD) method to depositcatalyst nanoparticles on the reactor surfaces. Continuous flow propene hydrogenation wasinvestigated as a model reaction. The activity of the ALD chips was compared betweenchips manufactured with different, more traditional, methods.

1.1.2 Adsorption

Adsorption is a phenomenon which occurs when a fluid (liquid or gas) is allowed to reachan equilibrium state while in contact with a surface. Most of fluids have a habit to createa film of particles on the surface and thus the concentration of the fluid molecules tendsto be higher at the vicinity of the surface than in the free volume. However, some liquids,which have only a minor affinity to the surface, do not create any higher concentrations ofmolecules next to surfaces as compared to the bulk phase.

Gas adsorption plays fundamental role in many processes found in chemical industry.Traditionally, adsorption isotherms are measured in static equilibrium conditions. Theresulting isotherm illustrates the number of adsorbed gas molecules as a function ofpressure. The shape of the isotherm can give valuable information about the adsorptionprocess, pore/surface filling and the surface properties of the absorbent.

There is, however, an contradiction between the way the traditional isotherms aremeasured and what are the needs of end users. Many industrial applications proceedthrough stages of multi-component gas adsorption while the gas mixture is flowing througha porous material. Traditionally adsorption isotherms are, however, measured in staticconditions for a single gas component only as the measurement of multi-componentadsorption isotherms is very challenging and time-consuming. Because in many of theapplications the flow is an essential part of the process, a static measurement may givean inaccurate view for the adsorption phenomena of the dynamic system. Thus, a novelremote detection NMR based method for in situ analysis of adsorption of flowing gases inmesoporous materials is introduced in the thesis.

1.2 Outline of the thesis

This thesis has two main parts; the first contains introduction and theoretical backgroundof the topics and the second one summarizes the research work which led to the threepublications attached to the end of this thesis.

In Chapter 2, the fundamentals of nuclear magnetic resonance spectroscopy are in-troduced. The chapter goes through the very basics of the method, describing also theeffect of relaxation. The chapter also introduces the concept of multidimensional NMRspectroscopy with the special case of Hadamard spectroscopy. The insensitivity of NMR isdiscussed with a few solutions to the problem.

Chapter 3 concentrates on magnetic resonance imaging by going through some basictheory with the addition of a few examples of pulse sequences. Chapter 4 describes theremote detection NMR method. Chapter 5 introduces a few relevant concepts from the

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field of fluid dynamics and microfluidics.In chapters 6, 7 and 8 the experimental work of the thesis is summarized. Chapter 6

concentrates on the demonstration of the usability of the novel RD-EXSY NMR methodsin determining, among other things, active reaction regions inside a reactor. The studyconcerning the development of new microfluidic reactors and the characterization of theirperformance with the remote detection method is described in Chapter 7. In Chapter 8 thedemonstration of a novel remote detection NMR based adsorption measurement method isshown. Chapter 9 contains a brief summary of the results of the thesis.

2 Nuclear magnetic resonance

Spectroscopy is a name used for methods which study an interaction between electro-magnetic radiation and matter. Nuclear Magnetic Resonance, or NMR for short, is aphenomenon which occurs when a sample is placed in a static external magnetic fieldand an orthogonal radio frequency field is used to perturb the system from its equilibriumstate. The resulting response is an oscillating radio frequency field that is observed as freeinduction decay (FID) signal. The FID is then Fourier transformed to produce an NMRspectrum.

One major benefit of the NMR method is that all the phases of matter (solid, liquid,gas) can be studied. Due to the low quantum energy of the perturbing RF fields, NMR isa non-invasive, non-destructive method, which can investigate optically opaque samples.NMR spectroscopy can be used to study physical, chemical and biological features ofsamples and therefore the technique is used in many fields of science, medical diagnosticsand industry. NMR is an exceptionally versatile method in chemical analysis as it providesspectroscopic, dynamic, structural and spatial information. The method can be used toobtain detailed information about pore size distribution, morphology, chemical exchange,diffusion and adsorption phenomena, etc. [12–21] These advantages, among many others,make NMR also an excellent tool for investigation of porous materials and microfluidicdevices.

To understand the chapters describing the results of this thesis work it is essential togo through some basic theory of NMR. The fundamentals are covered in this chapter anddeeper insight on the topic can be found from references: [22–28].

2.1 Basics of NMR Spectroscopy

All matter is built from small building blocks called atoms. Atoms in turn are built fromnegatively charged electrons, positively charged protons and neutral neutrons. Neutronsand protons together compose a nucleus which is surrounded by an electron cloud. Themain characters in the story of NMR spectroscopy are the nuclei.

Every nucleus i has a property called spin that is as fundamental property as mass orcharge. The spin I is a quantum mechanical property and it comes in multiples of 1

2 . All

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unpaired protons, electrons and neutrons are spin- 12 particles and therefore, the spin of thenucleus depends on the combination of protons and neutrons (see Ref. [22]) which formit. For example, the electron spin of a deuterium atom (2H) is 1

2 whereas its nuclear spinI is 1. To compare, the electron and nuclear spin of 1H are both 1

2 as the nucleus of 1Hcontains only one proton. The total length of the spin impulse moment vector I is

|I| =√I(I + 1). (2.1)

The NMR phenomenon is observable only for the nuclei which possess a non zero spin(I 6= 0), because these nuclei also have a property called a magnetic dipole moment

µ = γ~I. (2.2)

Here, ~ is the reduced Planck’s constant ( h2π ). The relative orientation of µ and I dependson the sign of the gyromagnetic ratio γ, which is specific for every nucleus. If γ is positiveµ and I are parallel and otherwise they are anti-parallel.

When a nucleus is placed in an external magnetic field B0, the magnetic dipole mo-ment and the field interact. This interaction is called the Zeeman interaction and thecorresponding energy is

E = −µ ·B0. (2.3)

If we choose the external field direction to be aligned with the z-axis of the laboratoryframe, the energy can be expressed as

E = −µzB0 = −γ~IzB0. (2.4)

Under the influence of the external magnetic field the nucleus has 2I + 1 differentorientations. Therefore, the amount of possible energy levels is also 2I + 1. These levelsare specified by a quantum number m (m = I, I − 1, ...,−I) and the allowed transitionbetween these levels is defined by a 4m = ±1 rule. Energy for each spin-state can bewritten as

Em = −γ~mB0, (2.5)

and therefore the transition energies are

4E = γ~B0. (2.6)

In NMR spectroscopy experiments, nuclei with spin 12 are often preferred due to the

fact that they possess only two energy levels (spin up and spin down states). The followingdescription is written for I = 1

2 nuclei, if not mentioned otherwise, as only spin- 12 nucleiwere studied in this work.

If a sample has reached a thermal equilibrium in an external magnetic field, accordingto Boltzmann statistics, the lower energy state has a slightly higher population than thehigher energy state. The population of state m is

Nm = Ae−Em/kT , (2.7)

where k is the Boltzmann constant, T is the temperature of the sample in Kelvins and A isa constant. Because the effect of the magnetic moments of the spins on the upper energy

20

level is canceled by the spins on the lower energy state, only the minimal excess of spinson the lower state gives rise to the macroscopic magnetization vectorM , whose behavioris then studied in NMR experiments.

Based on the populations, the macroscopic magnetization M0 at thermal equilibrium is

M0 =Nγ2~2B0I(I + 1)

3kT, (2.8)

where N is the number of nuclei. From this equation it can be easily seen that the way toget higher macroscopic magnetization is either to use higher external magnetic field, largernumber of nuclei or lower temperature. These approaches are, however, not always feasibledue to limitations of the sample or the experimental setup. Luckily there are other waysto increase the intensity of the observed signal e.g. by using hyperpolarization methodsor by changing the method of detection of the signal. These approaches shall be furtherexplained in Chapters 2.7 and 4.

To be able to detect any information from the sample, theM has to be disturbed fromits equilibrium. In NMR this is done with a RF pulse whit a frequency, ν, that correspondsto the transition energy

ν =4Eh

=|γ|2πB0. (2.9)

This field dependent frequency is specific for each nucleus.After the perturbation ends the magnetization vector starts to return to its equilibrium

state due to relaxation effects (see Section 2.3). Meanwhile, the magnetization is precessingaround the external magnetic field with the Larmor frequency

ν0 =γB0

2π. (2.10)

The precession induces a current to the detection coil, which is called Free Induction Decay(FID) signal. This time domain signal f(t) is then Fourier transformed,

F {f(t)} = F (ν) =

∫ ∞−∞

f(t)e−i2πνtdt, (2.11)

and a frequency domain spectrum is obtained.

2.2 Fine structure of the NMR spectrum

In reality, the nucleus will not experience a pureB0 field but a sum ofB0 and the localfieldBloc due to several interactions caused by the surrounding electrons and nuclei. Thisgives NMR spectroscopy its biggest advantage: the ability to see the differences in the localsurroundings of the nucleus directly from the resulting NMR spectra as each environmentgives rise to its own resonance frequency. The interactions relevant for this thesis areexplained in more detail in the next subchapters.

21

2.2.1 Chemical shift

When a sample is placed in an external magnetic fieldB0, the field will force the electronssurrounding the nucleus to move. This movement will generate a current which in turnleads to a secondary magnetic field Bσ, which is in general opposing the external fieldaccording to Lenz rule. Therefore, the electron cloud will shield the nucleus and the fieldfelt by the nucleus is lower than the B0. This can be seen as a lowering of the signalsfrequency in the resulting spectra. The effect is described by a nuclear shielding tensor σ(magnitude of 10−6) and the effect is directly proportional toB0:

Bσ = −σ ·B0. (2.12)

Nuclear shielding causes the same nuclei in different chemical environments to havedifferent resonance frequencies

vi =|γi|2π

B0(1− σi). (2.13)

As these frequencies, vi, are directly proportional to the magnetic field strength, thismakes the comparison of spectra measured with different spectrometers with differentfield strengths difficult. Thus, the positions of the signals are given in chemical shiftscale δ, which is a field independent ratio. This feature makes the comparison of spectrabetween different NMR magnets straightforward. The chemical shift of a certain nucleus isdescribing the difference between a standard sample resonance frequency and the frequencygenerated by the studied nucleus. The chemical shift is given by

δ(ppm) = 106 × ν − νrefνref

, (2.14)

where ν is the frequency of the NMR signal and νref is the frequency of the referencecompound. Usually, for 1H and 13C measurements, tetramethylsilane (TMS) is used asreference. However, it is a habit to divide the frequency difference by the receiver frequencyνrx instead of νref . This can be done without big errors to the resulting chemical shiftvalues as the difference between νrx and νref is almost negligible. To display the chemicalshift a scale of parts per million (ppm) is frequently used to make the numbers moreconvenient. Chemical shift is highly sensitive to the changes in the chemical environment.Therefore, it is a great way to characterize the atoms’ surroundings. For example, one candistinguish if a hydrogen belongs to a CH3 or CH2 group.

2.2.2 Scalar spin-spin coupling

Scalar spin-spin or J-coupling is an effect which is caused by other, non-equivalent, nucleiin the same molecule. The coupling is a relatively local phenomenon as the effect canreach typically through only three bond lengths. However, in the case of multiple bondseven four or five bond lengths are possible. Nucleus j (I = 1

2 ) will disturb the surroundingelectron cloud and the bonding electrons will, in turn, change the shielding experiencedby the nucleus i (I = 1

2 ). This will cause the resonance peak of the nucleus i to shift by

22

± 12J , where J is the indirect spin-spin coupling constant. Therefore the resulting signal is

a doublet pattern where the distance of the peaks is equal to J (see Fig. 2.1, n=1) .As described above the scalar spin-spin coupling effect causes the resonance peak of the

nucleus i to split into multiple lines. A simple rule can be given for the splitting while Hi iscoupled to a group of equivalent spin- 12 nuclei (see Fig. 2.1). The number of the resultinglines is n+ 1 , where n is the amount of equivalent j nuclei. Furthermore, Pascal’s triangle(see Fig. 2.1) can be used to estimate the intensities of the splitted lines. Coupling to nucleipossessing larger values of I than 1

2 leads to more complicated patterns of splitted lines.Therefore, the method described here is valid only for couplings between spin- 12 nuclei.The magnitude of the J-coupling is given in Hz because the effect is independent of theexternal magnetic field strength.

Figure 2.1. The splitting and intensities of the signal arising from the nucleus Hi due tointeraction with different number, n, of equivalent I = 1

2 nuclei Hj .

2.3 Relaxation

If a physical system is disturbed from its equilibrium and then the perturbation is removed,the system always tries to recover back to its equilibrium state. This process is calledrelaxation. Here the relaxation, like it is seen in NMR spectroscopy, is described only in abasic level by going through concepts of longitudinal and transverse relaxation. A moredetailed description of relaxation can be found from refs. [24, 25, 27].

When a sample is inserted in the B0 field, a net magnetization, aligned with theexternal magnetic field (z-axis), will be built up. At the equilibrium situation there is onlymagnetization M0 along the longitudinal z-direction and no observable components in the

23

transverse xy-plane exist. Thence, relaxation drives the transverse magnetization to zeroand the longitudinal magnetization towards the equilibrium value M0.

The buildup of the macroscopic magnetization along the z-direction is called longi-tudinal relaxation. The buildup curve is exponential (see Fig. 2.2 a). The macroscopicmagnetization at time t after applying theB0 field is

Mz = M0

[1− e(

−tT1

)], (2.15)

where M0 is the macroscopic magnetization in thermal equilibrium and T1 is the longitu-dinal relaxation time constant. This constant describes the time it takes for the system toreach 63% of the thermal equilibrium magnetization. The longitudinal relaxation is causedby the energy exchange between the surroundings and the spins.

In NMR experiments, the magnetization vector is commonly flipped to the xy-plane inorder to detect the FID signal. The macroscopic magnetization then starts to precess withthe Larmor frequency. Due to transverse (or T2) relaxation, the coherence of the transverse(xy) component starts to decay (see Fig. 2.2 b). This relaxation process is described by thetransverse relaxation time T2. The decay of the transverse magnetization, Mxy , due to T2relaxation can be represented as

Mxy = M0e(−tT2

). (2.16)

Small fluctuating local fields experienced by the nuclei are the reason for both of therelaxation processes. This random oscillation originates from random thermal motion ofthe molecules. Both the longitudinal and transverse relaxation are caused by the transversecomponents of the local fields which are oscillating at the Larmor frequency. There areseveral relaxation mechanisms causing the changes in the local magnetic fields, but twoof them are generally considered as dominant for spin- 12 nuclei: dipolar mechanism andchemical shift anisotropy. Another important issue is relaxation caused by paramagnetic

Figure 2.2. Relaxation drives the magnetization components towards their equilibriumvalues. a) Longitudinal magnetization approaches its equilibrium value of M0, indicatedby the dashed line, due to T1 relaxation. b) Transverse magnetization approaches zero as aresult of T2 relaxation.

24

species like oxygen in the sample. However, this effect can be diminished by degassing orby drying the sample before the measurements.

If a group of spins experiences on top of the B0 field the z-component of the locallyvarying field, this causes the frequency of the precessions of the spins to be slightly differentfrom each other. Over time this causes the individual moments to get out of phase, causingthe net magnetization to shrink. The inhomogeneity of the B0 field also causes a similareffect, but as this contribution is time independent a spin-echo pulse sequence can be usedto refocus the spins to get rid of the inhomogeneity caused contributions.

The spin-echo NMR pulse sequence consists of two radio frequency pulses: a 90◦ pulsefollowed by a 180◦ pulse separated by a period tE (see Fig. 2.3 a). The first pulse flipsthe magnetization to the xy-plane (see Fig. 2.3 b). Thereafter, the magnetization fans outdue to local magnetic field inhomogeneities as the precession frequency of some spins isslower due to lower local magnetic field and of other spins higher due to higher field. Thesecond pulse inverts the magnetization vectors in the xy-plane so that the slower spins arenow ahead and the faster ones are behind the rotating frame. During the following period,the magnetization vectors of the fast spins catch up with the slow ones. At time tE afterthe second pulse, a complete refocusing of the moments has been achieved and an echo isobserved. This Spin-echo method can be useful in both NMR and MRI.

Additonally, if a train of echoes is measured with different echo times, the amplitudesof the echoes decrease as a function of the transverse relaxation time. Therefore theamplitudes can be used to estimate the T 2-value. However if the molecules of the systemare moving randomly around so that there is a notable amount of diffusion present in thesystem, the T 2-value estimated whit this method can be too short.

Figure 2.3. a) Spin-echo pulse sequence and b) the behavior of the magnetization atdifferent stages of the pulse sequence.

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2.4 Multidimensional NMR

So far we have talked about one-dimensional NMR, where the intensity of each signalis plotted against the frequency or chemical shift. When a spectroscopist talks abouttwo-dimensional NMR, methods are meant which plot intensity against two frequencyaxes. Therefore, each signal has two frequency coordinates. These coordinates can be usedto achieve many kind of information about the studied system. Multidimensional NMRmethods are highly useful, for example, in determining chemical structures of molecules.There are several different multidimensional methods available such as COSY (CorrelatedSpectroscopy), EXSY(Exchange Spectroscopy), HSQC (Heteronuclear single correlationspectroscopy), HETCOR (Heteronuclear Correlation). First 2D methods appeared in the1970’s and the field is still developing fast. In the subsection 2.4.2 the EXSY method isexplained in more detail as the Paper I describes a novel way to perform EXSY experiments.

2.4.1 Basics of two-dimensional NMR

The basic idea behind any 2D NMR experiment can be presented as a four part sheme;Preparation, evolution, mixing and detection like seen in Fig. 2.4. The experiment startswith a preparation period which prepares the magnetization for the evolution period withRF pulses. The complexity of the preparation pulse sequence depends from the 2D methodused but it may be as simple as a 90◦ pulse or as complex as a train of pulses and delaysdesigned to to generate for example a multiple-quantum coherence.

The preparation is followed by an evolution period during which the magnetizationis allowed to evolve freely. The length of this delay is typically marked with symbol t1.However, its value is not fixed. Instead, the length of the delay t1 is changed (incrementedor decreased) for every repetition of the pulse sequence with a fixed value4t1. Thereforeeach repetition generates different coherence at the end of the evolution period. Theintervals between each step have to be kept uniform to be able to perform Fourier transformon the measured values.

Next step is a mixing period, which transforms the achieved coherences into observablesignals which are detected during the detection period. The mixing period defines whatkind of information is obtained from the experiment as different pulses, gradients anddelays may be used during this step.

Let us look at the Fig. 2.4 a. In the schematics presented here the pulse sequence isrepeated six times. In the beginning the evolution delay is as close to zero as possible (inreality there is always some minuscule delay due to equipment restrictions) and for eachmeasurement step the delay is increased. After each complete pulse sequence (markedwith i)-vi)) the FID signal is recorded. The collected points of each FID are formingone row in a matrix like seen in Fig. 2.4 b. When all the desired values for the delay t1are measured, a two-dimensional data set is generated (Fig 2.4 b) where each row showsvalues measured at certain delay t1 and each column FID datapoints collected at certaintime t2 after the detection was started. In the case of one-dimensional NMR, the timedomain signal is Fourier transformed. Similarly the Fourier transform is performed forboth time dimensions t1 and t2 in the case of the 2D NMR. This is done by first Fourier

26

Figure 2.4. a) General idea of 2D NMR experiments. The sequence consists of four parts:Preparation, evolution, mixing and detection. In this example, the sequence is repeated 6times (i-vi) and each time the length of the evolution period is incremented by4t1. Theresulting FID are sampled during the detection period with time interval4t2 (samplingrate). The gathered intensities are then placed on the rows of a matrix like seen in b).The horizontal axis tells the detection time at which time each particular point of the FIDsignal was gathered. The vertical dimension indicates the length of the evolution period.The matrix is then Fourier transformed in both directions and as a result plot with twofrequency axis is obtained c). The intensities of the resulting signals are either indicated bya contour map or by adding a third dimension of intensity to the figure. A single Fouriertransformed column (1.) and row (2.) is shown next to an example 2D contour spectrum.

27

transforming each row and after this the columns are Fourier transformed. The final matrixis a two-dimensional spectrum as seen in 2.4 c. If we pick one matrix column (marked 1.in 2.4 c) we can see 1D spectrum that corresponds to some frequency value in the v2 axisand vice versa if we pick one row (marked as 2.) we can see 1D spectrum correspondingto a specific frequency v1.

The length of the detection period t2 is kept fixed thorough the measurements. Duringthis period the signal is gathered similarly like in 1D experiment. Sampling more points inthe direct (t2) dimension and therefore, making the resolution of the resulting spectrumbetter, does not change the total length of the experiment by much. On the other hand,for each additional data point in the indirect (t1) dimension, an extra repetition of thepulse sequence needs to be performed. This is highly time consuming and therefore thethe number of collected t1 data points is frequently kept around few hundreds. Thus, themain limitation of the multidimensional NMR experiments is the immense amount of timeneeded for achieving decent resolution in the indirect dimension.

2.4.2 EXSY

The movement of atoms or molecules between different chemical or physical environmentsis called chemical exchange. This exchange can be studied by NMR spectroscopy ifthe different environments are directly observable from NMR spectra via changes in thechemical shift, couplings or relaxation times.

Two-dimensional exchange spectroscopy, or 2D EXSY for short, was introduced in1979. [29] 2D EXSY is an especially powerful method to investigate multisite systems insituations where the exchange is faster than the longitudinal relaxation T1. However, theexchange should be slow in the NMR time scale so that the NMR method is able to resolvepeaks from the different sites. EXSY is used most commonly to demonstrate the existenceof exchange processes but it can also be used to determine quantitative values, such as rateconstants.

Fig. 2.5 shows the 2D EXSY pulse sequence. The sequence has four periods: prepa-ration, evolution (duration t1), mixing (duration τm) and detection (duration t2). Thefirst pulse flips the magnetization to the xy-plane where, during the evolution period, themacroscopic magnetization vectors precess and gain their frequency labeling. The secondpulse flips the magnetization vectors to the z-axis direction and during the mixing periodthe spins may move from one site to other. This process is seen in the resulting 2D spectraas off-diagonal signals.

In the experiment, the mixing time τm is kept constant and usually it is much longerthan the duration of the detection or evolution periods. The exchange happening duringthese two time periods can be neglected if the exchange is slow in NMR timescale.

Any leftover transverse magnetization after the second pulse is destroyed with the useof a field gradient or by using phase cycling. The third pulse flips the magnetization backto transverse plane and an FID signal is observed. The whole process is then repeated butfor each cycle the time of the evolution step is incremented by4t1.

After performing a two-dimensional Fourier transform on the recorded signals, a set ofdiagonal and off-diagonal peaks is observed if the exchange rate is within proper limits.

28

As an example an EXSY measurement for N,N-Dimethylacetamide is shown in Fig. 2.6.Diagonal peaks arise from spins that have not experienced any exchange and from spinsthat have traveled during the pulse sequence but are at the same location during bothevolution and detection. The off-diagonal peaks correspond to the spins that have changedtheir site during the evolution time and are at different locations during evolution anddetection. In addition to the exchange process, the off-diagonal cross peaks may arisefrom magnetization transfer due to cross-relaxation (so-called NOE phenomenon). Theexperimental time required for an EXSY experiment is typically rather long, even hours,because a large number of t1 increments must be performed to achieve a satisfactoryspectral resolution in the indirect dimension.

Figure 2.5. 2D EXSY pulse sequence. The sequence is repeated n times and after everycycle the evolution time t1 is incremented by4t1.

Figure 2.6. 2D 1H EXSY demonstration spectrum of N,N-Dimethylacetamide. The greydots represent the off diagonal exchange peaks, which arise from the rotation of the C-Nbond.

29

2.5 Hadamard spectroscopy

As the resolution of the indirect dimension in the multidimensional NMR experimentsis mainly restricted by time, numerous ways have been developped for the reduction ofthe measurent time while retaining benefits of a good resolution. [30, 31] Both spectrumanalysis methods and data sampling methods have been developped for these purposes. Asan example of these kind of methods sparse sampling [32] and ultra fast NMR [31, 33]can be mentioned. In this work, however, a method based on Hadamard encoding wasemployed.

Frequency domain Hadamard NMR spectroscopy [34] is based on a selective spectralmanipulation, which is executed by using soft selective excitation pulses, exciting onlyselected nuclei, instead of hard pulses affecting all nuclei of the same isotope. Theexperimental setup requires a prior knowledge of the position of the peaks of interest asonly these positions are exited with the selective pulses. The position of the signals can bedetermined by measuring a 1D NMR spectrum.

Hadamard spectroscopy involves encoding the phases of the signals according to thesigns of a R×R Hadamard matrix [35]. Hadamard matrices are square matrices whitchentries are either +1 or -1 and which rows are orthogonal (see Fig. 2.7). If the numberof peaks of interest is S, a Hadamard matrix is selected so that S ≤ R. Therefore, themeasurement comprises of R signal acquisitions. The rows of the matrix describe thephase of the measured peaks and the columns describe how to combine the measuredpeaks so that a particular signal is visible while the others will vanish. This means thatthis method can be used also to suppress unwanted signals, such as water peak, from theresulting spectrum.

As an example, let us suppose that we have now two signals, A and B, in our spectrumand we have measured a 2 × 2 data matrix where the first row has now entries +A and+B and other row has entries +A and -B. When we combine these rows the way that itis described in the first column of the 2 × 2 Hadamard matrix (in Fig. 2.7 H2) we get:(+A+B)+(+A-B) = 2A and when we combine the rows according to the second column

Figure 2.7. First three Hadamard matrixes. With the same method one can build any sizeof Hadamard matrix.

30

we obtain: (+A+B)-(+A-B) = 2B. By choosing a correct operation (column of Hadamardmatrix) either only the signal A or B will be left visible. Generally it can be concludedthat the resulting signal is amplified by factor of R , where R is the size of the Hadamardmatrix. A benefit of the method is that the noise of the spectrum, due to its irregularity,is increasing less than the signal. Therefore, the resulting signal to noise ratio (SNR) isincreased by

√R as compared to a separate selective exitation of each signal.

After the Hadamard encoding, a normal 2D pulse sequence (EXSY, COSY or other) isperformed without the usual evolution period. As a result, altogether R FIDs are collected.A total of R experiments is acquired because all the rows of the Hadamard matrix areneeded for the final resulting spectrum.

It is, however, important to choose the smallest possible matrix for the task in orderto keep the total duration of the experiment as short as possible. Usually, the numberR is, however, much smaller than the number of the 4t1 increments needed for thecorresponding traditional 2D measurement. This feature makes the Hadamard methodmuch faster than traditional 2D NMR methods. Even though each encoding step ismeasured separately, the frequency domain Hadamard spectroscopy is a way to solve theproblem of long experimental times in 2D spectroscopy without losing the sensitivity. [34]

The main drawback of the method is the finite selectivity of the used pulses. If thespectra are crowded the selectivity of soft pulses might be insufficient for separation ofoverlapping signals.

2.6 Sensitivity

NMR is an astonishingly powerful tool for scientists but the biggest drawback of themethod is its low sensitivity. Based on the Boltzmann distribution (see Section 2.1), thepopulation difference, ϕ , between the energy states is

ϕ =N↑ −N↓N↑ +N↓

= tanh(γhB0

4πkT), (2.17)

where the N↑, N↓ are the populations on the spin up or down states.The population difference in a typical NMR magnet is extremely small, about 0.001%.

This presents the sensitivity problem for NMR spectroscopy because the absolute valueof the resulting magnetization vector is proportional to this difference. As seen from Eqs.2.8 and 2.17, the net magnetization can be increased by using a higherB0 field, a lowertemperature T or a larger number of atoms. These approaches are not always feasible dueto sample properties, experimental setup or by the limitations of the equipment and financee.g. achieving high and homogeneous magnetic fields is both difficult and expensive. Alsothe equipment used introduces some restrictions e.g. the sample probes are limiting theallowed temperatures and volumes. For non-MRI magnet the sample volumes can beup to a few milliliters. This is the maximum volume that can give raise to NMR signal.Moreover in NMR the spins are encoded and the resulting response is detected with thesame coil. This causes the setup not to be optimal for either task. Therefore, compromisesare inevitable in the design of the probe. Lots of improvement can be achieved if, insteadof one coil, two separately optimized coils are used, like in the case of remote detection

31

NMR. The signal intensity can also be improved by using hyperpolarization methods.In this thesis work remote detection (RD) NMR method is used to overcome the sensi-

tivity issue and the hyperpolarization effect caused by parahydrogen induced polarization(PHIP) was used to study catalyst surfaces. Because the RD NMR method is of suchan importance in the work the basics of the method are described in a separate Chapter4 whereas the hyperpolarization using parahydrogen enriched hydrogen gas is brieflydescribed in the next section.

2.7 Parahydrogen-induced polarization

The term hyperpolarizer is used for experimental setups that result in spin polarizationwhich differs from the thermal equilibrium situation. These methods transfer magnetizationfrom a more ordered system to a less ordered system. There are many ways to transferthe polarization, for example: SEOP (spin-exchange optical pumping) [36, 37], DNP(dynamic nuclear polarization) [38], MEOP (metastability optical pumping) [39] and PHIP(parahydrogen induced polarization) [40–42]. Here the basics of the PHIP method areshortly presented as in the Paper II parahydrogen enriched hydrogen gas was used to studycatalyst surfaces and their ability to produce pairwise addition of hydrogen molecules tosubstrates. If a parahydrogen molecule were to be added in a pairwise manner to a targetmolecule, it would be observed as enhanced NMR signals. This phenomena is calledparahydrogen induced polarization.

2.7.1 Spin isomers of molecular hydrogen

Molecular hydrogen H2 is composed of two electrons and two hydrogen nuclei, both ofwhich possess a non-zero spin (I = 1

2 ). Para- and orthohydrogen are two spin isomers ofthe molecular hydrogen, differing in their nuclear spin configuration (total spin of 0 forpara- and 1 for orthohydrogen). Para- and orthohydrogen have also different rotationalstates, heat capacities, electrical conductivities and melting points. Under standard con-ditions, hydrogen gas consists of 74.9% of ortho- and 25.1% of parahydrogen. As onlyorthohydrogen has a non-zero I , only it is NMR active, giving rise to a singlet peak around4.55 ppm in the NMR proton spectrum.

The existence of these hydrogen isomers comes from the symmetrization postulate ofquantum mechanics. The existence of the isomers was experimentally verified alreadyin the beginning of 1900. Because the quantum mechanical treatment of even as simplemolecule as hydrogen is complicated, the following summary is only highlighting the mostimportant parts.

In general, under the Born-Oppenheimer approximation, the total wave function of thehydrogen molecule can be presented as the product of five functions

ψ = ψorbe ψseψvibn ψrotn ψsn, (2.18)

where ψorbe is describing the orbital motion of electrons, ψse the electron spin state, ψvibn

32

the vibrational state of the nuclei, ψrotn the rotational motion of the nuclei and ψsn the spinstate of the nuclei.

The overall wave function of H2 has to be antisymmetric in exchange of the nuclei.When looking at Eq. (2.18), it is clear that the first two terms are symmetric as they areindependent of nuclear coordinates. The third function is also symmetric as the position ofboth of the nuclei can be interchanged without affecting the vibrational state. The overallsymmetry therefore depends on the two last terms

ψrotn ψsn. (2.19)

Interchanging the two nuclei transforms the second last term to

P12(ψrotn ) = (−1)Jψrotn (2.20)

where P 12 represents the permutation operator that changes the position of the nuclei andJ is the rotational quantum number. Therefore, ψrotn is symmetric for even rotational statesand antisymmetric for odd ones.

There are four allowed spin configurations, ψsn , of the dihydrogen molecule:

ψT+1 = |αα〉 (2.21)

ψT−1 = |ββ〉 (2.22)

ψT0 =1√2

(|αβ〉+ |βα〉) (2.23)

ψS0 =1√2

(|αβ〉 − |βα〉). (2.24)

The first three αα, ββ and αβ + βα, are symmetric with respect to the exchange of nuclei.These three form the orthohydrogen isomer and are marked with symbol T (triplet state).The remaining configuration αβ − βα is antisymmetric and is known as parahydrogenmarked with S (singlet state).

According to Pauli’s principle, the symmetric rotational function must be combinedwith the singlet nuclear spin function, whereas each antisymmetric rotational function hasto be combined with a symmetric (triplet) spin function. As a result the total wave functionis antisymmetric.

2.7.2 Production of parahydrogen enriched gas

Parahydrogen enriched gas is formed by cooling hydrogen gas. The cooling processdrains energy from the rotational states, forcing the molecule to populate the symmetricrotational ground state. This also forces the nuclear spin wave function to be antisymmetric(parahydrogen state). It is important to notice that the transition between the singlet andtriplet nuclear spin states which is symmetry forbidden. Therefore, the conversion of para-to orthohydrogen is really slow and it would take weeks to reach the thermal equilibrium.However, the transition is much faster if some catalyst is introduced into the system.

33

If the parahydrogen enriched gas is heated up again without the catalyst present, thehydrogen cannot relax fast back into the thermal equilibrium in this new temperature. Theinterconversion between the states has a half-time of approx. 3 weeks but, in practice, dueto impurities in the container etc. the gas relaxes faster. The ratio between the ortho- andparahydrogen in thermal equilibrium can be written as:

NorthoNpara

=3∑odd J(2J + 1)e−θ(

J(J+1)T )∑

even J(2J + 1)e−θ(J(J+1)

T ), (2.25)

where θ is the rotational temperature, which is defined as θ = ~2

2Y kB. [43, 44] Here kB is

the Boltzmann constant and Y is the moment of inertia. θ describes the estimate of thetemperature at which thermal energy is comparable to the difference between rotationalenergy levels. For H2 θ =87.6 K. As the energy difference between the rotational states isbigger than the difference between the spin states, the manipulation of the rotational statesis much easier than manipulating the nuclear spins directly. As these states are pairedthrough symmetry, one is able to produce high population difference for the spin states atmoderately low temperatures (see Fig. 2.8).

In our experiments parahydrogen was produced by slowly flowing high purity hydrogengas through a copper spiral connected to a tube filled with a FeO(OH) catalyst. The catalystand the cooling spiral were kept at liquid nitrogen temperature (77 K). The parahydrogenenrichment setup used in the experiments is described in more detail in Ref. [45].

Figure 2.8. Proportions of para- and orthohydrogen present in hydrogen gas at thermalequilibrium with respect to temperature.

34

2.7.3 NMR signal enhancement with parahydrogen

In this section the mechanism leading to signal enhancement is explained by using apopulation-oriented approach. This approach is sufficient for the major features (shapeof the spectra and signal enhancement) of small, weakly coupled AX systems. Densityoperator formalism is needed for more complicated systems. [42]

The underlying principle of the PHIP effect is the conversion of the parahydrogen singletstate into a state with observable magnetization. Like stated before, in parahydrogen, thespins are opposed, essentially canceling each others out, making the molecule invisible forNMR unless the symmetry of the molecule is somehow broken. In the hydrogen moleculeitself it is difficult to break the symmetry. Hence, the first step of PHIP experiment is achemical manipulation. In most cases the hydrogenation reaction is performed with thehelp of a catalyst (homogeneous or heterogeneous). After the hydrogenation reaction theparahydrogen derived protons have typically different chemical environments. This changein the symmetry makes the signal observable. It is, however, important to transfer bothprotons to the same target (pairwise transfer), as otherwise the singlet symmetry of theparahydrogen will not be preserved and the hyperpolarization effect will be lost.

When hydrogenation with parahydrogen enriched gas is performed, only those nuclearspin energy levels in the product molecule become populated that have correspondingsymmetry properties with the parahydrogen. Therefore the populations in the product spinsystem differ vastly from the thermal equilibrium and an enhanced signal is observed (seeFig. 2.9). There are several ways to produce this enhancement effect. [46] In the followingexample two methods are described; PASADENA [47, 48] and ALTADENA [49].

The hydrogen molecule is now considered to be a strongly coupled A2 system beforethe hydrogenation. After the reaction is performed the hydrogens form a weakly coupledAX system (with four states; αα, αβ, βα, andββ), which is isolated from the rest of thetarget molecule. If the hydrogenation is done with thermal hydrogen at room temperaturelike seen in Fig. 2.9 a, the initial A2 system has four eigenstates that are almost equallypopulated (P = 0.25). The difference between the highest and the lowest energy state is2ε, where ε = ~γB0

kT ∼ 10−5 for protons at room temperature. The resulting spectrum hasfour identical signals with intensity ∝ ε.

If the reaction with parahydrogen is performed at high magnetic field, the experimentis called PASADENA (Parahydrogen and Synthesis Allow Dramatic Enhancement ofNuclear Alignment). At high magnetic field the chemical shift differences dominate anyJ-coupling interactions. During the hydrogenation the symmetry of parahydrogen is brokenand sudden transition from a strongly coupled A2 system into a weakly coupled AX systemoccurs. This sudden transition preserves the spin orientation and both antiparallel energylevels of the AX system are populated equally with the excess of spins (see Fig. 2.9 b). Asa result a spectra with two anti phase doublets is observed with the intensity proportionalto 3

24P ± ε, where 4P is the population excess of the singlet state in the A2 system.This means that the intensity can be even four to five orders of magnitude larger that theintensity in Fig. 2.9 a.

ALTADENA experiment starts by the hydrogenation reaction that is performed in lowmagnetic field. In this case the chemical shift differences are small compared to J-couplings.Typically the hydrogenation is performed at Earth’s magnetic field. The system is thentransferred to high field. By doing this only the antiparallel state of the AX system with

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Figure 2.9. PHIP effect illustrated with a population-oriented approach. a) NMR spectrumafter hydrogenation is performed at room temperature with normal hydrogen gas. Thefour eigenstates in the A2 system are almost equally populated as the population followsthe Boltzmann distribution (the difference is of factor 10−5). After the hydrogenation theprotons become an AX system whose NMR spectrum consists of four identical signals.b) Hydrogenation reaction with the PASADENA experimental setup. The resulting NMRspectrum has two anti phase douplets. c) Hydrogenation reaction with the ALTADENAexperimental setup. The resulting NMR spectrum has two signals with opposite phases.

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lower energy is populated (see Fig. 2.9 c). This leads to a spectrum where two anti phasepeaks separated by the chemical shift and J-couplings are present. The resulting signalscan have twice the intensity as compared to the PASADENA experiment.

Originally PHIP was discovered in a homogeneous catalytic hydrogenation. Sincethen many new homogeneous catalytic systems have been shown to produce PHIP. Ithas been recently shown that PHIP is not limited to homogeneous phase reactions [42].Heterogeneous PHIP has a benefit that no separation of catalyst from the substrate isneeded. However, unlike in homogeneous phase reactions the hydrogenation step doesnot take place at one single metal center. Instead a metal surface or immobilized metalcomplexes are present, allowing different interactions upon adsorption of parahydrogen onthe surface. This results in a smaller signal enhancement if an enhancement is observed atall.

In ALTADENA and PASADENA methods the hyperpolarization effect is achieved byadding the parahydrogen molecule into the target molecule through hydrogenation reaction.However, there is a way to transfer the spin order from the parahydrogen molecule intothe target substance also with the help of a catalyst through a short-lived complex. Thismethod is called SABRE (Signal Amplification By Reversible Exchange) [50, 51] and itsbenefit over the hydrogenative methods is that the substrate stays chemically unchanged.

3 Magnetic resonance imaging

Magnetic resonance imaging (MRI) is perhaps the best known application of NMR spec-troscopy. The method is widely used in medical diagnostics where it has proven to bean extremely useful tool. In this chapter the basic principles of MRI are explained withfew examples of some common pulse sequences. More information can be found in refs.[25, 26, 52, 53]

3.1 Basics of MRI

The basic goal of magnetic resonance imaging is to correlate measured NMR signals withspatial coordinates in order to construct an image of the studied system. Explaining theidea behind MRI can be started from the resonance equation

ν =γB0

2π, (3.1)

which states that the resonance frequency is directly proportional to the magnetic fieldexperienced by the nuclei. In the case of NMR spectroscopy the spectrum is observedfrom a sample under a homogeneousB0 field and the resulting NMR spectrum containsinformation which arises from local field differences like explained in Chapter 2. If thisapproach would be used to study a complex structure, such as a human body, whichcontains mostly water and fat, the resulting 1H spectrum would be in this simplifiedexample situation dominated by a water peak (see Fig. 3.1 a ). This kind of 1H spectrumwould not give much information about the body or its structure, even though the intensityof the signal is proportional to the amount of water in the patient. If, on the other hand, amagnetic field gradient Gx (linear variation of the magnetic field with respect to position)along the x direction is used in the experiment, the resonance frequency of the protonswould vary linearly across the body:

ν =γ(B0 + xGx)

2π= ν0 +

γxGx2π

. (3.2)

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The resulting FID now contains information about the position of the spins along thechosen axis. When this FID is Fourier transformed, a spectrum is obtained which showsthe frequency distribution of the signals. This forms the 1D image of the sample. As theresonance frequency ν, Larmor frequency ν0, gyromagnetic ratio γ and the gradientGx areknown, a spatial map of, for example the water inside the human body, can be generated(see Fig.3.1 b.) by using the following equation:

x =(ν − ν0) 2π

γGx. (3.3)

As an result a 1D MR image is obtained with spatial information. The same principle canbe expanded for multidimensional experiments with gradients applied along two or threeorthogonal directions.

Figure 3.1. Difference between a NMR spectrum and a 1D MRI image. a) If a NMRspectrum were to be measured from a human patient, the resulting spectrum would bedominated by a water signal at 4.7 ppm. This does not give any useful information aboutthe studied system. b) MR imaging is done by adding a magnetic field gradient to theexperimental setup. This will cause the signal to divide on the frequency axis. With thehelp of the Eq. (3.3) the frequency axis can be converted into a spatial axis. The amplitudeof the resulting 1D image is proportional to the number of spins contributing to the signalat each spatial point.

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3.2 Imaging equation

In a one-dimensional MRI experiment the signal, s(k), is measured as a function of k-space

s (k) =

∫ρ (r) e−i2πkrdr. (3.4)

Here ρ(r) is the effective spin density and the k-space can be written as

k =γ

2π

∫G(t)dt, (3.5)

where the G is the gradient with respect to time. The Fourier transform of the signal in Eq.(3.4) results in an image of the spin density distribution

ρ (r) =

∫s (k) ei2πkrdk. (3.6)

Therefore, position r and spatial frequency k form a Fourier transform pair. This equationpair (3.4) and (3.6) is also called the 1D imaging equation. These equations are easilyexpandable for two- and three-dimensional imaging.

In this simple example the relaxation effects are neglected. This approach would bevalid if the repetition time would be TR >> T1 and the echo time TE << T2 but this israrely the case in real experiments. In reality the effective spin density contains the effectsof relaxation, i.e, ρ(r, T1, T2). This feature can be used as a benefit in imaging as materialswith different relaxation properties can be easily resolved. In the following section twobasic pulse sequences are introduced.

3.3 Spin-echo imaging

The MRI pulse sequence for a 2D spin-echo imaging is shown in Fig. 3.2 a. The experimentstarts with a frequency selective pulse and slice selection gradient. This combination excitesthe magnetization in a desired slice. The dephasing caused by the slice selection gradientis refocused by a successive negative gradient with an area half of the first gradient. Aftera time that is a half of the echo time, TE , the signal dephasing is refocused by a 180◦

pulse and an echo is detected at time TE , as in the normal spin-echo NMR pulse sequencedescribed in Section 2.3.

The 2D spatial information of the spins is encoded to the sample by using a phaseencoding gradient, GPE , during the evolution period and a readout gradient, GFE , (per-pendicular to the GPE) during the signal acquisition. By changing the gradient valuesthe experiment maps out the so-called k-space, which can be described as a matrix (seeFig. 3.3) in which the raw data from MRI experiment steps is stored during the dataacquisition. Typically the k-space matrix has the same amount of rows and columns as thereconstructed image.

In the example shown in Fig. 3.2 a different values of GPE are used for each measure-ment step. Therefore each row of the resulting k-space contains the raw data received after

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Figure 3.2. a) Spin-echo imaging pulse sequence and b) gradient-echo FLASH imagingpulse sequence

Figure 3.3. By changing the values of phase and read gradients the k-space is mappedout in point-by-point manner.

a particular phase gradient value. The GFE is then in every measurement used first to getto the negative end of the k-space in the readout direction.

This is then followed by another readout gradient during which the signal is observedand the k-space is sampled in point-by-point manner in the read direction with desired

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resolution 4kFE . The k value described by the Eq. (3.5) can be written separately forread and phase direction:

kFE =γ

2πGFEm4t (3.7)

kPE =γ

2πn4GPEτ. (3.8)

Here m tells the column in frequency encoding direction, n the row in read direction in thek-space. The4t is the sampling time and τ is the duration of the phase encoding gradient.

Let’s look at a simple example to understand better the effect of the gradients: Assumefour magnetization vectors of spin ensembles which have exactly the same chemical shiftsbut different locations on x-axis. The vectors are flipped to the xy-plane by a selective 90◦ pulse. These four magnetization vectors would start to precess with a Larmor frequencyν0 at the fieldB0.

When a phase encoding gradient GPE along the x-axis is applied, the four vectors startto precess with the frequency given by Eq. (3.2), which is dependent on the x-coordinate.Each transverse magnetization vector has therefore an unique frequency. On the otherhand, the protons in a same row, perpendicular to the x-axis, have the same frequency andphase. When the gradient is turned off, the external magnetic field experienced by eachspin vector is once again identical. Therefore, all the vectors precess with an identicalLarmor frequency. The phase angle φ for each vector on the other hand is unique,

φ = γGPEt, (3.9)

where t is the time the phase encoding gradient was applied. The phase angle describes theangle between a reference axis (can be agreed to be the y- or x-axis) and the magnetizationvector.

The final part in the 2D imaging sequence is the read gradient GFE that is appliedin direction perpendicular to the direction of the GPE while the signal is detected. Thereadout gradient encodes the frequency difference to the signals on each columns of thek-space.

The pulse sequence is repeated until all the phase encoding steps have been recorded.2D spin-echo imaging is used in medical imaging as it results in high quality images. Anadvantage of using this kind of sequence is that it introduces T2 dependence to the signaland it refocuses the dephasing caused by the magnetic field inhomogeneities. However, theexperiment times are quite long and often some faster method is used to avoid movementrelated artifacts. The measurement time for spin-echo imaging is determined by the amountof lines in the k-matrix.

3.4 Gradient-echo imaging

Gradient-echo pulse sequence is another way to perform imaging. The pulse sequencehas only one rf-pulse located in the beginning of the sequence. This frequency selectivepulse is applied together with a slice selection gradient similarly to the spin-echo imaging.

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The dephasing caused by the slice selection gradient is refocused by a successive negativegradient with an area half of the first gradient as in the case of spin-echo imaging.

As the 180◦ refocusing pulse is not used in the sequence, an echo is produced with thehelp of the gradients. To achieve this a dephasing gradient is used in the readout directionsimultaneously with a phase encoding gradient. The dephasing gradient corresponds tohalf of the readout gradient but with an opposite sign. This causes the spins to be inphaseat the center of the read gradient, which is employed during the acquisition. Therefore,the spins will rephase during the first half of the read gradient and dephase again in thesecond half. As a result a gradient-echo signal is recorded. Imaging with a gradient-echosequence is more sensitive to magnetic field inhomogeneities because the inhomogeneitiesare not refocused by a 180◦ as in the spin-echo experiment.This feature is also known asT ∗2 weighting.

In Fig. 3.2 b a special, fast form of gradient-echo imaging sequence is shown. In thisFLASH (fast low angle magnetic resonance imaging) pulse sequence [53] the first pulsedoes not flip the magnetization by a full 90◦ but a selective pulse with small flip-angle αEis applied at the same time with slice-selecting gradient. According to the Ernst rule [26],the optimum flip angle αE to get maximum amount of signal at a certain time is

cosαE = e−t0T1 , (3.10)

where t0 is the recycle delay between scans. The introduction of this pulse sequenceshortens dramatically the time needed for MRI measurements without big losses in theimage quality. However, the contrast of the resulting image may be different compared tothe pure 90◦ excitation.

4 Remote detection NMR

Remote detection (RD) is a signal detection scheme developed for NMR and MRI exper-iments introduced by the research group of Alexander Pines at University of California,Berkeley [4, 5]. In the RD setup the encoding of NMR or MRI information about thestudied system is physically separated from the detection of the signal. Typically thesesteps are performed with two different RF coils. The sample itself is stationary and only theinformation encoded into the magnetization of a carrier fluid is moving from the encodingcoil to the detector. This approach offers means to overcome the inherent weak point ofNMR, low sensitivity. Remote detection has proven to yield up to 103 times better signalto noise ratio (SNR) than is achievable with a traditional NMR setup.

4.1 Principles of RD NMR

Remote detection NMR experiment can be divided into three stages: encoding, travel anddetection. In RD experiment a fluid is flowing continuously through a studied systemwhich is positioned in the middle of an encoding coil (see an example in Fig. 4.1 a). Thedesired information of the sample is encoded into the spin coherences of the carrier fluidby using magnetic field gradients and different kind of pulse sequences, while the fluidis inside the encoding coil (see Fig. 4.1 b). At the end of the encoding step, the acquiredinformation is stored by turning the magnetization along the external magnetic field. Thus,during the travel period only T1 relaxation affects the magnetization. Often T1 relaxationtime is significantly longer than T2 relaxation time. Additionally, the inhomogeneity ofthe magnetic field does not cause the longitudinal magnetization to fan like it would in thecase of transverse magnetization. Therefore, longitudinal orientation is preferable for theduration of the travel phase.

The experimental setup has to be designed so that the travel time to the detector is soshort that the encoded information has not decayed significantly due to T1 relaxation. Thestored information is then read with a separate detector. The separation of the encoding anddetection also allows the use of many different kinds of detection methods like SQUIDs(superconducting quantum interference devices) [54, 55], Hyper-SAGE (hyperpolarizedxenon signal amplification by gas extraction) [56, 57], optical atomic magnetometry [58],

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Figure 4.1. Schematic representation of the remote detection experiment. a) A sample isplaced inside an encoding coil and a continuous flow of carrier fluid (marked with whitearrows) is flowing through the sample. The arrows in the image indicate also the flowdirection. b) Information about the sample is encoded to the spins while the fluid is insidethe encoding coil (Encoded fluid is marked with dark grey). c) The information travelswith the flow to a separate detector, where the stored data is read with optimized sensitivityand filling factor.

microcoils [59] and micro solenoids [10]. All these methods have the same goal; to achievebetter sensitivity. In this thesis hand wrapped micro solenoids with different diameterswere used for detection. An estimate of the sensitivity gain between two coils can becalculated from the 90o pulse lengths td90 and te90 (determined with the same rf power)using the following equation

Λ =te90td90

. (4.1)

Here d and e label the detection coil and encoding pulse lengths, respectively.Remote detection setup makes the optimization of the size, sensitivity and geometry of

the coils possible. [60] This yields better signal to noise ratio. [59] In addition, differentfield strengths can be used for the encoding and detection. [4] For example encoding canbe performed at low field while the detection is performed in high field to ensure highenough SNR. This is advantageous, especially, while using hyperpolarized fluids, if thesample is heterogeneous and one wants to avoid susceptibility gradients. The references[59, 60] offer an excellent overview of the issue of sensitivity enhancement.

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4.2 Information carriers

In principle, all fluids with NMR active nuclei (I 6= 0) can be used as the carrier of theencoded information. Most commonly spin- 12 nuclei are preferred due to their simplespectrum and the lack of quadrupole interactions.

One of the qualification factors is the longitudinal relaxation time T 1. To be a potentialinformation carrier the T 1 of the fluid should be at least of the same order of magnitude asthe average travel time in the setup. This ensures that after the travel there is still someencoded longitudinal magnetization left and that the information can be read out with thedetector. For liquids the 1H relaxation times are usually around a few seconds and for gases1H relaxation times are less than a second. Noble gases, however, have relatively long T 1

relaxation times. [60] The travel path should also be designed so that there would be aslittle magnetic field changes as possible, as they can make the relaxation times shorter.

However, the long T1 can be also a problem in the continuous flow setup. As the termT1 describes the building of magnetization along the external magnetic fieldBo there maynot be enough time to build the thermal polarization. For example, when 129Xe flowsthough the sample, the fluid is inside the magnet typically less than a minute and the T1can be easily several minutes for xenon.

In some applications another important issue is chemical inertness as the fluid carryingthe information should not alter the studied sample while passing through. However, on theother hand the capability to react may be important e.g. in reactor studies. Additionally, ifthe carrier fluid is able to show chemical shift upon non-covalent contact with the sample,one is able to extract information even about surface chemistry, pore sizes etc.

In the thesis work 1H was used as it is an ideal nucleus for studying flow patternsand chemical reactions. The T1 of the 1H is short enough to achieve sufficient thermalpolarization in the experimental setup used in the projects. On the other hand the relaxationtime was long enough to enable safe travel for the encoded information to the detector.Additionally, 1H has high gyromagnetic ratio γ (267.513×106 rad

sT ), high natural abundancein and high sensitivity. Therefore, proton spectrum gives well resolved signals fromdifferent chemical environments. [61]

4.3 Application of RD method to microfluidics

Microfluidic processes and devices are often monitored by optical [62, 63], electrochemical[64] or mass spectrometry [65] methods. Most frequently, optical and electrochemicalmethods are utilized as they have relatively good sensitivity. [66, 67] Recently, also theusefullness of NMR spectroscopy in the characterization of microfluidic devices (seeSection 5.2.2) has been realized. [68, 69] NMR is a non-invasive method to obtain versatilespatial, spectral and dynamic information without the need for optical transparency oradditional tracer molecules. [58, 61, 70, 71] The weak spot of NMR is its low sensitivitycaused by the small population difference between the energy states (see Section 2.6). Theinsensitivity is being emphasized in the case of microfluidic devices as the volume with themeasured fluid inside the channels is minimal compared to the overall size of the device.The low filling factor combined with low density gaseous fluids may cause the sensitivity

46

to be inadequate for proper signal detection.Remote detection, however, may overcome the sensitivity problem. The unique ex-

perimental setup of RD allows the optimization of both encoding and detection steps,separately, resulting in high sensitivity enhancement. This has broadened the scope ofapplications of NMR and MRI. As a natural side product, of the RD experimental setup,Time-of-Flight (TOF) [5] information is obtained as the travel time from the sample to thedetector depends, among other things, on the initial location of the molecules. [72]

RD NMR is applicable from large-scale flow systems to miniaturized lab-on-a-chipreactors. As microfludic chips naturally have transportation of fluids through the chips,they are a perfect couple for the RD setup. The remote detection allows one and multidi-mensional Time-of-Flight (TOF) imaging, which can present detailed information aboutflow paths, diffusion, mixing, concentrations of molecules, chemical reactions in certaingeometries. [70] RD NMR has been used to image flow through porous materials [73]and membranes [74], microfluidic devices [70, 75, 76], rocks [5], wood [77], as well asfor chemical reaction imaging [45, 78, 79]. Two new RD based methods were presentedin Papers I and III. In paper II the RD NMR was used to characterize the performanceof different kind of microfluidic chips, which are used for hydrogenation reactions. Inthe next sections a few basic experiments, which are employed in the thesis work, areexplained.

4.4 Travel time experiment

The travel time experiment [4, 77] is commonly used to study the time it takes for thespins to travel though the encoding region or, alternatively, from the sample region to thedetector. This is achieved with the pulse sequence seen in Fig. 4.2 a. The experiment startswith a 180◦ pulse executed by the encoding coil. This will affect the spins which are at thatmoment inside the encoding coil by flipping their macroscopic magnetization vectors onthe negative z-axis. Right after the first pulse, the detection coil starts pulsing the fluid flowwith a train of 90◦ pulses and after each pulse the signal is gathered. A single detectionpulse reads the magnetization of the spins which are inside the detector at that moment. Asa result, first a positive signal is observed, which is typically normalized so that the signalamplitude equals to 1 like seen in Fig. 4.2 b at time t = 0. The detected signal amplitudeswill start getting smaller and finally negative as more spins, which experienced the initial180◦ pulse, arrive to the detector. If the amplitudes are plotted against the time that haspassed since the first 180◦ pulse, a plot like in Fig. 4.2 b is achieved. This figure revealsthe time the fluid spends inside the sample and also the time it takes to reach the detector.

The spacing of the detection pulses depends on the acquisition time of the FID signaland other delays used in the experiment. This determines the time resolution of theexperiments, because a new detection pulses cannot be applied before the previous FID hasbeen recorded. The acquisition time for the FID signal is normally matched to be equal ora little bit shorter than the residence time of the fluid inside the detection coil. The amountof repetitions for the detection pulse is chosen so that the total detection time is longer thatthe longest travel time from the sample to the detector. [70]

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Figure 4.2. a) Travel time pulse sequence and b) travel time curve for gas flowing inside atube which is passing through the encoding and detection coils.

As the signal intensities are normalized, the minimum amplitude can be -1. Howeverthere are many things, which can cause the dip in the amplitudes to be smaller. For example,the effect of dispersion can be seen from the shape of the figure. If the edges of the dipare not steep and the minimum value differs from -1, the dispersion is notable. Dispersiondescribes the variations in the velocities of the particles which is seen as variation in thetravel times through the system. Additionally an imperfect 180◦ pulse angle or relaxationcan cause the minimum to be smaller than -1. As the spins travel to the detection region,they start to relax as an effect of longitudinal relaxation processes (T1 relaxation) asexplained in Section 2.3.

4.5 Z-encoded time-of-flight imaging experiment

Z-encoded time-of-flight (TOF) imaging [77] is an experiment where, like in the previousexperiment, the travel time of the encoded spins from the sample to the detector is measured.The TOF imaging experiment, however, adds an extra dimension to the experiment asmagnetic field gradients are used to encode spatial information to the spins.

The TOF imaging experiment can be done as one dimensional or multidimensional.The pulse sequence for a one dimensional TOF imaging can be seen in Fig. 4.3 a. Thefirst encoding coil pulse flips the net magnetization to xy-plane and after that a magneticfield gradient along the z-axis is applied. This step encodes the position of the spins on thez-axis similarly as in the phase encoding step used in traditional MRI experiments (seeChapter 3). Then another 90◦ pulse is applied to store the encoded information for thetime of travel. As the molecules exit the encoding coil region the information travels alsowith the fluid flow. In the meantime, a train of 90◦ pulses is applied with the detectioncoil and after each pulse signal is recorded. In the resulting image the average locationdistribution of the spins on the z-axis is plotted against the travel time (see Fig. 4.3 c). Inthe example, shown in Fig. 4.3 b and c, gas is flowing first through a packed bed sampleand then through an empty outlet tube. The spins from the lowest point of the encodingcoil (empty tube, marked with violet triangle) arrive to the detector first with the shortest

48

travel time and the spins from the top of the encoding coil (packed bed, marked with violetdiamond) arrive to the detector last. As the plot, shown in Fig. 4.3 c, indicates the timeit has taken for spins at certain z-location (during encoding) to reach the detector, theamplitude pattern can be used to study, for example, the velocity of the flow in each regionof the system. As the slope of the pattern is directly the velocity, therefore, the steeper theslope, the faster the flow. In the case of this example, one can conclude that the flow isfaster in the empty tube than in the packed bed region.

Figure 4.3. a) Z-encoded time-of-flight pulse sequence. b) Measurement setup. Thesample is placed in the middle of the encoding coil. c) Z-encoded TOF image of thepacked bed sample. The symbols indicate corresponding position in the z-encoded TOFimage and the sample. The violet triangle dot is at the lowest point of the encoding regionin b). Therefore, the spins from that location arrive to the detector with shortest travel time,which can be seen in c) as a triangle in the left bottom corner. At the point marked withred circle is the connection between the filled and empty tube. This change in the flowsystem can be seen in c) as a change in the steepness of the slope. The violet diamondshape indicates the highest point of the encoding region in b). The spins form this regionarrive to the detector last after traveling about 700 ms as seen in c).

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4.6 Multidimensional TOF imaging

Multidimensional TOF is almost identical to the 1D one, but instead of using only onegradient, the sequence has simultaneous gradients in two or three orthogonal axes. Theencoding of the spin locations along different axes will be done in a similar manner asin the multidimensional MRI experiments. The experiment goes through the k-space inpoint-by-point manner as explained in Chapter 3. Again, a 90◦ pulse stores the informationand the flow of the fluid takes the encoded spins to the detector where the flow is pulsedwith a train of 90◦ pulses. As a result, images of the flow at different travel time values arereconstructed. 3D TOF is basically the same, but now three gradient pulses are used to gothrough a three dimensional k-space.

As an example a two dimensional TOF pulse sequence with gradients on two axes, yand z, is shown in Fig. 4.4 a. The measured sample is a microfluidic reactor consisting of36 parallel microfluidic channels. The experimental setup is shown in Fig. 4.4 b and theresulting TOF images are shown in c. The images reveal the encoded yz-location of thespins which have arrived to the detector with the travel time indicated with yellow numbers(ms) on the top of of each TOF panel. The first image shows the spins from the outletconnector and the last one spins from the inlet connector. The right most image is a sum ofall the TOF panels.

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Figure 4.4. a) Y z-encoded TOF pulse sequence. b) Experimental setup for imaging gasflow through a microfluidic chip. c) Resulting yz-encoded TOF images at different traveltimes indicated by yellow numbers (ms) on the top of the panels. The arrow like shapeseen in the panels is mainly due to the difference in the path lengths. The spins travelingthrough the outermost channel have almost 8 mm longer path as compared to the onesflowing through the middle channel. This causes spins in the outer channel appear to becloser to the outlet than the spins in the middle at the same travel time.

4.7 Indirect RD NMR spectrum

The indirect RD NMR is a way to aqcuire a spectrum from the sample area inside of theencoding coil with the separate detection coil. The resulting spectrum may differ fromthe direct spectrum measured with the detection coil from the carrier fluid with no samplepresent. The indirect approach [4] starts with a normal 90◦ pulse (see Fig. 4.5 a). Thefirst pulse flips the magnetization to the xy-plane (4.5 b). Thereafter, the magnetization isfreely evolving during the time t1(4.5 c). The information is then again stored by flippingthe magnetization to the direction of the external magnetic fieldB0. When the fluid arrivesto the detector, the amplitude values are read by the 90◦ detection pulses. This procedureis then repeated several times by changing the length of the t1 by constant intervals.

Basically this means that the NMR information is recorded in a point-by-point mannerwith different t1 values. After all points are measured, the resulting FID signals are Fouriertransformed (4.5 d). The signals should be identical in their frequency but they differin their amplitudes. These peaks are not telling anything new about the sample, but if

51

the signal amplitudes are plotted against the evolution period time, t1, it will result in anindirect FID signal (Fig. 4.5 e) for the indirect time dimension whose Fourier transformgives the indirect spectra (Fig. 4.5 f). A similar procedure is used in many 2D spectroscopymethods like, for example, in EXSY (see Chapter 2).

Figure 4.5. Measurement of an indirect spectrum. a) Pulse sequence of the indirect RDNMR experiment. b) The first rf-pulse turns the magnetization to y-axis. c) During theevolution time t1 the magnetization vectors have time to evolve. The time t1 is increasedfor each measurement resulting in a change in the amplitude of the Fourier transformeddetection coil signal like the one seen in part d). The resulting amplitudes are plottedwith respect to the time t1 and an indirect FID like seen in e) is observed. f) The Fouriertransform of the FID gives the indirect spectrum.

5 Microfluidics

5.1 Fluid dynamics

Fluid dynamics is a term used about equations and laws which describe the transport andphysical properties of fluids. According to the formal definition, a fluid is any substancethat deforms continuously if a shear stress is applied to it. In the next subchapters fewconcepts important for this thesis work are described with the initial assumption that allthe fluid molecules are spherical particles.

5.1.1 Viscosity

Viscosity is defined as the capability of a fluid to resist shear stress (drag). Therefore themore viscous the fluid is the more sticky it is. Viscosity can also be described as kind of aninternal friction as the property indicates the difficulty of the fluid particles to pass eachother or a solid surface. The effect comes from intermolecular cohesion and transfer ofmolecular momentum, latter being more dominant in the case of gases.

Newton’s law of viscosity states that "viscosity is that fluid property by virtue of whicha fluid offers resistance to shear stresses". The Newtonian viscosity µ is defined by

τ = µdu

dy, (5.1)

where τ is the shear stress and dudy is the rate of angular deformation.

There are, however, fluids that do not have linear relationship between the τ and dudy

and they are called non-Newtonian. [80] These fluids have special rules, which are notexplained in this brief overlook as the gases used in the thesis projects are all Newtonianfluids. Ref. [80] is recommended for the ones who are interested on the behaviour ofnon-Newtonian fluids in microchannels.

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Figure 5.1. Transition between laminar, transitional and turbulent flow

5.1.2 Laminar flow

There are many ways in which the flow can be classified, but one of the most importantways to describe a fluid flow is the difference between laminar and turbulent flow. Laminarflow is highly predictable as the fluid is flowing in parallel layers. At low velocities thelayers are not mixing as they are just passing each other. In other words, there is no currentperpendicular to the direction of the flow and the flow is time independent (steady flow).In steady laminar flow inside a cylindrical tube the particles move in a very orderly mannerparallel to the edges of the surface (see Fig. 5.1) with a parabolic velocity distribution sothat the slowest speed is closest to the surface. At higher speeds the streams may showsome wave patterns which are time dependent (unsteady flow) but still the lamellae arenot mixing. Between the laminar and turbulent flow a state of transitional flow exists. Inthis state both laminar and turbulent flow types are possible. If the pressure difference atthe end of the pipes is increased, the flow gets faster and faster until the parabolic velocitydistribution and the steady stream lines break and the fluid starts to move randomly. Thisis called as a laminar-turbulent transition point. In a turbulent flow the paths of the fluidmolecules are complicated and there is high degree of mixing happening, making the flowtime dependent and unpredictable (see Fig. 5.1).

5.1.3 The Reynolds number

To describe and predict the behavior of a fluid flow in different situations, a dimensionlessnumber called the Reynolds number is used. [81] The Reynolds number is the ratio ofthe inertial forces to viscous forces. The idea was introduced already in 1851 but it wasOsborne Reynolds who made the concept well known with his study of the transition fromlaminar flow to turbulent flow of fluids in pipe. [81]

The definition for the Reynolds number depends from the situation on hand, such asthe geometry of the system. Let’s first consider a flow in a pipe. In this case the Reynoldsnumber is

Re =ρvL

µ, (5.2)

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where ρ is the density of the fluid, v is the mean velocity of the flow, L is the characteristiclinear dimension (in the case of pipe it is the inner diameter) and µ is the dynamic viscosityof the fluid. In practice even small changes in the shape or surface of the flow channelcan result in big changes in the flow behavior, making the fluid flow behave locally ina chaotic manner. However, the Reynolds number is a good way to predict the generalbehavior of a fluid. Different flow regimes have been resolved for the flow in a pipe. If theReynolds number is smaller than 2300, the flow is fully laminar, and if the Re > 4000, theflow is turbulent. Therefore, the laminar flow occurs when viscous forces are dominantand turbulent flow when inertial forces dominate the flowing fluid.

In the case of a microfluidic channel the characteristic linear dimension L is the hy-draulic diameter DH . In the microfluidic reactors used in this thesis the channels arerectangular. Therefore, the hydraulic diameter is

DH =4wh

(w + 2h), (5.3)

where w is the width and h is the height of the channel. In this case the flow is laminar ifRe ≤ 2000 and turbulent if Re ≥ 4000.

Additionally, if the fluid is flowing through a packed bed, the Reynolds number is

Re =ρvSD

µ, (5.4)

where D is the diameter of the packed particles and vS is superficial velocity. Thesuperficial velocity is the volumetric flow rate of the fluid divided by the cross sectionalarea of the packed bed. In this case the laminar flow regime is when Re ≤ 10 and the flowis fully turbulent already when Re ≥ 2000.

5.1.4 The Péclet number

The Péclet number is the ratio between convection and diffusion, i.e., the ratio betweenhydrodynamic forces and Brownian diffusion (random diffusion). Therefore, it describeswhich feature is dominant in a flow system with certain dimensions. The transition pointoccurs at the Péclet number of Pe = 1. This number is defined as

Pe =3va2

Dh0, (5.5)

where a is the particle radius, h0 is the diameter of the flow system and the characteristicdiffusion coefficient D is given by Stokes-Einstein diffusivity:

D =kT

6πµa, (5.6)

where k is Boltzmann constant and T is the temperature in Kelvins. With small values ofRe and Pe the Brownian diffusion dominates the flow whereas if the Reynolds number isbig enough, the turbulent behaviour is dominating the flow. In the case of microfluidic gas

55

reactors, the Péclet number is quite small and the flow is laminar, thus making the randomdiffusion dominant.

5.1.5 Poiseuille law

In Poiseuille flow, which is anticipated in the case of microfluidic devices, if a pressuredifference ∆P is applied over a cylindrical channel, a parabolic velocity profile is expected.The flow can be imagined to contain a vast amount of infinitely thin laminas. According tono slip condition, the fluid at the edges, touching the surface of the channel, is stationary(vwall = 0) and the fluid lamina at the middle of the channel has the fastest velocity.Therefore each lamina experiences pull from the faster lamina and a drag from the slowerlamina next to it. In a steady laminar flow the forces are in balance with the pressuregradient. According to Hagen-Poiseuille’s law the velocity v(r) at certain point in acylindrical channel is

v(r) =(r2 − r20)∆P

4µL, (5.7)

where L is the characteristic length of the channel, r is the distance from the centre and r0is the distance of the wall from the centre. At the wall r = r0, eq. (5.7) yields

v(r0) =(r2o − r20)∆P

4µL= 0, (5.8)

and in the middle of the channel (r = 0)

v(0) =(−r20)∆P

4µL. (5.9)

By integrating the velocity over the pipe radius the volume flow rate, or the so calledPoisseuilles law, is obtained

V =

r0∫0

2πrv(r)dr =−r40π∆P

8µL. (5.10)

If this is then divided by the cross section of the pipe we get the mean velocity:

V =−r20∆P

8µL. (5.11)

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5.2 Microfluidics

Microfluidics [6, 80, 82] is a field of science and technology that deals with manipulationof fluids in systems with dimensions of tens to hundreds of micrometers. These smalldimensions offer many advantages and only a few disadvantages. The small dimensionsenable, for example, small sample volumes, high surface to volume ratio, efficient heatexchange, precise control of chemical reactions, short analysis times, low cost of device andreactants, mobility and ability to carry out separations and detections with high resolutionand sensitivity.

First application of microfluidics was a gas chromatograph already in the 1970’s [83, 84].It consisted of an injector, separation channel and thermal conductivity detector. Since thenthe field has widened and microfluidic devices have attracted lots of interest in many areasof science. Lab-on-a-chip reactors are kind of fluids representative of integrated circuits.These devices aim to replace a full normal size laboratory with a small chip that wouldperform for example a full chemical analysis. This unique system and process integrationbrings safety of operation, decreases the experimental time needed and allows portabilityof a fully operational laboratories.

Compared to macroscopic world, different phenomena are important at the micro scale.For example, surface tension and capillary forces are dominant, but the effect of gravitycan be almost totally neglected. Also diffusion becomes important in the transportation offluids. Microfluidic chips also offer a flexible channel design and high chemical stability.In addition, in most cases, the fluid flow inside the channels is laminar [85] making thefluid flow highly predictable as described earlier. These and many other properties are whymicrofluidics offers great promises for future technologies and applications, like cancerdiagnosis [86] and drug delivery [87].

5.2.1 Microfluidic chips

Microfluidic chips typically have either one or several inlets and outlets. Between thesethere is a set of interconnected channels (see Fig. 5.2), which have at least one dimension inthe order of tens to hundreds of micrometers. A whole range of features may be integratedinto these chips including fluidic valves, pumps, mixers, catalysts and many others. Thereare numerous solutions on how the sample is introduced to the chip and how the fluid ismade to move through the channels. The sample can may be moved by active (pumps,pressure gradients, syringes) or passive systems (hydrostatic pressure).

The chips are most often planar as the channels are etched, molded, embossed or printedinto various materials. Most commonly materials like glass, silicon, quartz, metals ordifferent polymers such as PDMS (PolyDimethylSiloxane) are used. [82] However, forexample, 3D-printing and injection molding offer new design possibilities as the channelsare not restricted to the planar surfaces. Recently, PDMS has become one of the mostpopular materials as it is highly suitable for prototyping due to its transparency, goodbiological performance, elasticity and low cost.

The most traditional materials for microfluidic chips are, however, silicon and glass.They offer high temperature durability, precise channel dimensions and even the possibility

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of integration of electronic circuits. In this thesis work the micrfluidic chip reactors wereetched in silicon wafers. In Paper I glass wafer and in Paper II a commercial foil was usedto seal the rectors from top (see Sections 6.2 and 7.2 for fabrication details). The ref. [88]offers elegant review on different fabrication processed suitable for silicon and glass.

Figure 5.2. Example of a microfluidic chip with 10 mm long reactor consisting of 36parallel channels containing reaction catalyst.

5.2.2 Using NMR to study microfluidics

To enable precise fluid handling, accurate knowledge of the flow and other propertiesinside microfluidic devices is needed. Various detection methods are already in usefor these purposes (see Section 4.3), but most microfluidic flow measurements rely onoptical detection, which require optically transparent devices and often injection of tracers.Furthermore, the fluids to be analyzed must be optically transparent as well. NMR isan ideal non-invasive tool which can give versatile information about the reaction, flowand the reactor itself without the need for tracers or transparent devices like described inChapter 4.

However, due to the low sensitivity of traditional NMR method, the study of microfluidicdevices is rather challenging and some fresh ideas are needed to make the NMR evenmore attractive choice for specialists dealing with microfluidics. The detection sensitivitymay be improved by decreasing the size of the RF coil as explained in Section 4.1. Theminimization of the coil additionally increases the filling factor which is favorable for theintensity of the obtained signal.

There are numerous ways in which the principles of NMR have been combined tomicrofluidcs. One solution has been to integrate small volume NMR probes directry to the

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microfluidic device itself [89] or to it’s vicinity. The coils have been also minimized inmultiple ways, for example, planar coils or microcoils [11, 90–96], microcoils [89, 97–99]have been used in this type of studies. Another especially useful solution for monitoringcontinous flow reactions inside a microfluidic chips is a high resolution stripline detectors.[100–105] Additionally, microslots [106] have been used with microfluidic applications.Some miniaturized coil designs have also been combined with hyperpolarzation methods.All of these designs have their own problems. For example some of the chips are made outof materials containing large amounts of hydrogen. This causes large background signalsto the resulting spectrum which might make acquisition of well resolved signals difficult.Also the magnetic susceptibility between different materials might become an issue.

In this thesis project the sensitivity problem for microfluidic gas flow is overcomeby using RD NMR. [4, 107, 108] As the signal is detected outside the microfluidc chipall the material related susceptibility and background signal problems are avoided. Theapplication of remote detection NMR to microfluidics was introduced in Section 4.3.

6 Imaging microfluidic chemical reactors withHadamard-encoded RD NMR (I)

In Paper I, a concept of remote detection exchange NMR spectroscopy (RD-EXSY) wasintroduced and a demonstration of the usability of the Hadamard encoding of the indirectspectral dimension in TOF RD-EXSY imaging was given. The usefulness of the novelmethods in acquiring unique combination of detailed chemical and spatial informationwas demonstrated by following a simple gas phase hydrogenation reaction of propeneinto propane in a microfluidic reactor. The remote detection setup was employed in theexperimental work throughout the thesis and it has proven to be a remarkably important andflexible tool for imaging microfluidic flow, chemical reactions and adsorption phenomena.

6.1 Hydrogenation

Hydrogenation is a chemical reaction, in which two hydrogens attach to a pair of atoms(usually carbons) sharing an unsaturated (double or triple) bond. Therefore, hydrogenationreduces the amount of the double bonds in hydrocarbons and the reaction is called in somecases as reduction of organic compounds. Most hydrogenation reactions use hydrogen gasas the source of hydrogen.

At temperatures close to room temperature, the hydrogenation reaction often requiresthe presence of a metal catalyst. Catalysts are divided into two categories: homogeneousand heterogeneous. Homogeneous catalysts are dissolved into the solvent containing thereactants and heterogeneous catalysts are usually solid metals which are in contact with thesubstrate. Heterogeneous hydrogenation is an important and widely used reaction in manyareas of science and industry since it can produce catalyst free reaction product. All sixplatinum elements, Ru, Rh, Pd, Os, Ir, and Pt, can be utilized as hydrogenation catalysts.In this thesis work platinum was chosen as the catalyst due to its high catalytic activity,[109–111] which has been shown to depend on the (platinum) particle size, density, shapeas well as the reacting molecules size and the choice of support. [112–114]

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6.2 Microreactor

The reactor performing the hydrogenation had 36 parallel channels (length 10 mm, width50 µm and height 50 µm) coated with platinum catalyst (thickness 100 nm). The channelswere connected to inlet and outlet channels (width 200 µm, length 10 mm) by horizontalchannels (width 200 µm) (see Fig. 6.1). The microfluidic chips used in this thesis workwere manufactured by the group of professor Sami Franssila in the Department of materialsscience and engineering at the Aalto University.

The manufacturing process involved microchannel and inlet fabrication in a siliconwafer, catalyst metal deposition and anodic bonding to a glass wafer with catalyst patternmatching the channel structure (see Fig. 6.2). The platinum catalyst was introduced to thesurface by sputtering, which is a widely used process to cover surfaces. For example, inscanning electron microscopy (SEM), the specimen are covered with conductive materialsby the sputtering process. Sputtering is a physical vapor deposition method where particlesare ejected from a target onto a silicon wafer or some other surface (see Fig. 6.3). This

Figure 6.1. Illustration of the microfluidic reactor design and dimensions.

Figure 6.2. Manufacturing steps of the microreactors. A cross-section of the reactoris presented. a) The top of a silicon wafer is covered with SiO2 and the bottom with aaluminium. SiO2 is first patterned and then microchannels were etched by DRIE (deepreactive-ion etching). Next, the system was turned around and the inlet holes were alsoDRIE etched. b) Sputtering of Cr/Pt (20/100nm). c) The SiO2 and platinum on the top aswell as the aluminium on the bottom are removed with HF. d) Aligned anodic bonding toPt-patterned glass wafer.

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Figure 6.3. Sputtering process. Energetic particles (most commonly gas ions or plasma)hit the sputtering target. This causes the target material to eject particles towards a substrateon which the thin-film of target material is formed. The sputtering gas is normally aninert gas such as argon. Sputtering process allows a precise control over the growth andmicrostructure of the deposited film.

generates a thin film of the particles on the substrate surface. More details about the makingof the chips can be found from ref. [78].

The studied chips produced reaction yields between 25 % and 50 % at the used ex-perimental conditions. With time the activity of the catalyst dropped due to catalystdeactivation. By flushing the reactors with pure hydrogen gas at elevated temperature wewere, however, able to restore the activity close to its original value.

6.3 Flow system

The hydrogenation reaction was performed under continuos flow of a mixture of propeneand hydrogen at elevated temperature (approximately 40◦C) by using a home built airheating system. The gases were premixed with a 2:3 pressure ratio (propene:hydrogen)with a total pressure of 8 bar in a 1 L cylinder (see Fig. 6.4). The surplus of hydrogen isused to ensure that there is always enough hydrogen around for the hydrogenation reactionto occur. The mixture flowed from the cylinder continuously through the microfluidic chipwhere the hydrogenation reaction occurred. After passing through the chip the gas enteredan outlet tubing and flowed out of the magnet. The inlet and outlet tubings were madefrom a fused silica gel capillary (Upchurch, OD 360 µm, ID 150µm). The capillaries wereconnected to the chip by Upchurc nanoport connectors (see Fig. 6.5). The gas flow ratewas controlled by a valve at the end of the flow system and the pressure was followed witha pressure gauge connected to the inlet tubing. The experiments were performed between8 and 6.5 bar. During the continuous flow, the pressure dropped by less than 0.1 bar perhour due to the decreasing amount of gas mixture in the 1L cylinder.

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Figure 6.4. Illustration of the flow setup used in the experiments. Smaller (1 l) gas cylinderwas filled with a mixture of propene and hydrogen. The gases were allowed to mix forsome time in the cylinder before the start of the flow to the microfluidic reactor which islocated inside the spectrometer. The flow velocity was controlled with a valve at the end ofthe flow system

6.4 NMR hardware

The experiments were carried out using a Bruker DSX 300 wide bore spectrometer oper-ating at 300 MHz proton resonance frequency. For all remote detection experiments thesame double probe system (described below) was used with case-specific modifications.For encoding of the spatial information a Bruker 2.5 imaging probe with a 25 mm RFinsert was used. The RF insert had a birdcage coil with 25 mm inner diameter and 35mm height. As the imaging probe had a 22 mm diameter empty cavity through the wholelength of the probe, the detection probe was built to fit that cavity. A home built sampleholder optimized for each sample was used to position the measured system in the middleof the encoding coil (see Fig. 6.5). Signal detection was carried out with a microsolenoid,which was hand wrapped around the outlet capillary out of 120 µm copper wire (see Fig.6.6). Length of the coil was about 3 mm and it consisted of 18 loops. The detection coilwas positioned about 10 mm below the lowest point of the encoding coil to avoid artifactsfrom the interaction of the two coils.

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Figure 6.5. Illustration of the double-probe RD setup with the home-built sample holder.

Figure 6.6. Detection coil and the coil holder

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6.5 Results

6.5.1 Two-dimensional TOF imaging

Y z-encoded TOF images were measured for all the studied chips to examine how the gasis flowing through the investigated reactors (see Fig. 6.7 a). The pulse sequence used inthis case can be seen in Fig. 6.7 b. To cancel the effects arising from the inhomogeneity ofthe magnetic field in the sample region, a spin-echo scheme was added to the encodingpulse sequence.

The TOF images were processed by selecting an area containing a signal of interestfrom the detected spectra. For example, the images seen in the top row of Fig. 6.8 wereprocessed by selecting the propane CH3 group signal (marked with red number 5 in Fig.6.7 c). As the detection coil was about 800 times more sensitive than the encoding coil,the resulting SNR was high enough to achieve nice spectra from the gas. The J-couplingswere not resolvable from the detection coil spectra due to the broadening caused by theflow. However, the resolution was high enough to separate signals from all gas components(see Fig. 6.7 c) and therefore, the TOF images corresponding to propene and propanegas could be reconstructed independently from a single experiments as seen in Fig. 6.8.The TOF image contains information of the location of selected gas molecules during theencoding and the time it has taken for those spins to reach the detector. Therefore, theimages having the shortest travel time show the gas that was nearest to the chips outletduring the encoding, and the image with longest travel time shows spins from the inlet.

The sums of the panels in Fig. 6.8 reveal that the reaction yield was larger in theoutermost channels than in the middle of the chip as most of the propane signal wasdetected in the outermost channels. Based on these TOF images, the flow velocity on theedges was calculated to be 2/3 of the velocity in the middle. Thus, the larger yield can be

Figure 6.7. a) The microfluidic reactor and its position inside the encoding coil. b) Theyz-encoded TOF imaging pulse sequence with the addition of a 180◦ spin echo pulse inthe encoding coil to avoid artifacts arising from the inhomogeneity of the magnetic fieldinside the encoding coil. c) 1D spectrum of the gas flowing through with the detection coil.The spectrum clearly shows well resolved peaks of all the gas components.

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Figure 6.8. Yz-encoded TOF images of propene hydrogenation in the microfluidic reactor.The top row is obtained by selecting the propane methyl group signal for the processing.The rightmost image is the sum of all the panels. Bottom row is constructed by selectingthe propene methyl group signal. The travel time is indicated by the yellow numbers (ms)on the top of each panel.

hypothesized to be a consequence of the longer flow path coupled with slower flow, whichtogether give the gas much more time to react. These combined together with relaxationare causing also the signal amplitude in the sum images to be weaker in the upper cornersthan in the lower parts of the chip.

These TOF images do not, however, portray precisely the active regions of the chipas the spatial encoding of the spins is preserved in the hydrogenation reaction. WhenTOF images are processed with the propane signal, also the propene molecules that wereconverted into propane after the encoding will contribute to the image. Because of this,the propane signal can be seen even in the inlet although there is no catalyst present andhence no opportunity for hydrogenation reaction exists. Additionally these images tellnothing about the reversibility of the reaction studied. RD-EXSY offers a solution to thesechallenges.

6.5.2 RD-EXSY

The pulse diagram for RD-EXSY can be seen in Fig. 6.9 a. First, the chemical shifts areencoded to the spins inside the encoding coil region like in the evolution period of 2D

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EXSY experiment. As always in RD scheme, the information is saved by rotating themagnetization along the external magnetic field and then it is read out with the detectioncoil. This sequence is basically identical to the indirect RD NMR explained in Section 4.7.

The resulting spectra can be seen in Fig. 6.9 c. Both diagonal and off-diagonal peakscan be observed in the spectra. The signals on the diagonal arise from spins that did notchange during the experiment. In other words they belonged to either propene or propaneduring both encoding and detection. The off-diagonal cross peaks indicate the spin thatbelonged to different molecules during the encoding and the detection. This means that the

Figure 6.9. a) RD-EXSY pulse sequence. b) Numbering of the protons in propene (blue),hydrogen (green) and propane (red) used in the RD-EXSY and TOF figures shown in c). c)2D RD-EXSY spectra with the corresponding TOF images. As the RD-EXSY does notproduce direct spatial information, the results can be compared to yz-encoded TOF imagesto get indirect information about the position of molecules during the signal encoding. Thetravel time is indicated in the EXSY images in red (ms) and in TOF images in yellow (ms).

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hydrogenation reaction took place between encoding and detection for these molecules.The presence of the cross peaks proves that when propene is hydrogenated into propanebetween the encoding and the detection, the encoding of spin coherence is preserved.There is, however, no direct spatial information in the EXSY figures. By comparing theyz-encoded TOF images and RD-EXSY figures with same time value one is able to getindirect spatial information as seen in Fig. 6.9 c.

Contrary to standard RD imaging, RD-EXSY method has a potential to reveal thereversibility of reactions. In the example reaction no peaks indicating reversibility ofthe reaction were observed as the reaction is irreversible in the used conditions. Thereversibility would be seen as off-diagonal peaks on the other side of the diagonal. Inaddition, the reaction intermediates should be visible in the spectra if the intermediates hadsufficiently long lifetime compared to NMR-timescale. In this example the lifetime of theintermediates was not long enough for them to be observable.

6.5.3 Spatially resolved Hadamard-encoded RD-EXSY

Imaging chemical reactions in microfluidic chip would be hugely improved if the activeregions of the chip could be accurately assigned. The RD-EXSY approach does not directlyproduce this kind of information, but the spatial information is obtained from the TOFimages indirectly as was seen in Fig 6.9 c. A more accurate way of achieving spatialinformation would be to combine indirect spectral encoding with indirect spatial phaseencoding. This, however, would lead to unbearably long experiment times due to the hugenumber of encoding steps. One possible solution to this was presented in Paper I. Wedemonstrated that, if the idea of Hadamard spectroscopy is implemented in the encoding ofthe signals, it is possible to obtain spatially resolved RD-EXSY images within a reasonablemeasurement time.

In Paper I, propene hydrogenation was followed. Therefore, only a 2 × 2 Hadamardmatrix, H2, was used, as it is enough to follow one signal from both the reactant and theproduct:

H2 =

[1 11 −1

]. (6.1)

In this case the signals arising from the CH3 groups of both propene and propane werechosen. The signals were selectively encoded by using the pulse sequences seen in Fig.6.10. By summing two successive experiments (Enc1 + Enc2 and Enc3 +Enc 4) together,it was ensured that all the signals experienced similarly the imperfect inversion by thefrequency selective pulses as well as the relaxation occurring during the encoding. Supposethat x is a number between 0 and 2, which describes the size of the effect. Therefore,x = 0 only when the inversion is perfect and there is no relaxation occurring during theselective pulses. Encoding number 1 (Enc 1) has no selective excitation. Therefore, bothsignals have positive phases before the direct spatial encoding step, which is similar tothe one used in yz-encoded TOF. Therefore, the resulting intensities of the signals canbe written as IPropane and IPropene (see Fig. 6.11 a). In the second encoding (Enc 2),the phases of both methyl group peaks are inverted with selective pulses. The resultingintensities due to imperfections are −(1− x)IPropane and −(1− x)IPropene for propane

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Figure 6.10. Pulse sequence of spatially resolved Hadamard-encoded RD-EXSY.

and propene, respectively. The negative phases of the signals are converted into positive bychanging the sign of the phase of the following π

2 pulse. In the third encoding (Enc 3) onlythe phase of propene is inverted whereas, in the fourth encoding (Enc 4), only the propanesignal is inverted. Resulting signal intensities for each encoding can be seen in Fig. 6.11 a.

The sum of the intensities of the signals from the first two experiments (F = Enc 1+ Enc2) corresponds to the first row of the Hadamard matrix and the sum of the experiments 3and 4 (G = Enc 3 +Enc 4) is used to form the second row as seen in Fig.6.11 b and eq.(6.2).

HRD−EXSY =

[IPropane IPropeneIPropane −IPropene

](2− x). (6.2)

When the spectra corresponding to the Hadamard matrix rows seen in the Fig. 6.11bare summed together, the resulting propane signal strength is 2Ipropane(2− x) whereasthe intensity of the propene signal is zero (see 6.11 c). If the rows are subtracted, thepropane signal is zero and propene has an intesity of 2Ipropene(2 − x). Therefore, itis possible to form either propane or propene encoded TOF images as can be seen inFig. 6.12. Additionally, the encoding frequencies can be correlated with the observedfrequencies, providing EXSY information. Due to the properties of the Hadamard encodingthe resulting spectrum has

√R times bigger SNR (R is the size of the Hadamard matrix)

than could be achieved in a spectrum which would be selectively excited without the useof Hadamard scheme.

The spatially resolved remote detection Hadamard TOF EXSY images can be seen inFig. 6.12. The first row of Fig. 6.12 is reconstructed by using the sum of the Hadamardmatrix rows of Eq. (6.2) (F + G). As can be seen form Fig. 6.11c it includes only signalfrom spins that belonged to propane during the encoding step. The data was processedusing the detection coils propane signal and therefore these images correspond to thediagonal peak arising from propane in the RD-EXSY spectra.

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Figure 6.11. Visualization of the Hadamard encoding of the signals arising from themethyl groups of propene and propane performed with the pulse sequence shown in Fig.6.10. a) Shows the intensities of the signals after each pulse sequence (Enc 1, 2, 3 and4). b) Intensities of the summed experiments. All the signals have experienced the sameimperfections caused by the experimental setup (marked with x). Spectrum F correspondsto the first row and G corresponds to the second row of the H2 matrix. c) The resultingsignal intensities after performing the Hadamard transform according to the columns ofthe H2 matrix. See text for further information.

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Figure 6.12. Hadamard encoded TOF images. The right most image is a sum of all theother panels on the same row. The top row shows images which were processed by usingpropane signal for both encoding and detection. The amplitude of the signal in the sum ofthe resulting TOF images could be directly proportional to reaction yield, but as relaxationrate in the case of propane is quite fast compared to the experiment time the relaxation hasto be taken into account. The images in the middle row represent results obtained by usingpropene signal for both encoding and detection and the bottom row spins bottom row spinsthat have converted between encoding and detection into propane are seen.

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The second row in Fig. 6.12 is reconstructed by subtracting the Hadamard matrix rowsof Eq. (6.2) (F-G). Therefore, the images contain only signal from methyl groups whichbelonged to propene during encoding. The processing was done using the detected propenesignal and thus the result corresponds to the RD- EXSY diagonal signal arising frompropene.

In the last row, the propene signal was encoded but propane signal was detected. Thiscorresponds to the off-diagonal gross peak in the RD-EXSY spectra, which indicates thosemolecules that converted between encoding and detection.

As the Hadamard encoding requires only that the number of encoding steps is greaterthan or equal to the number of signals of interest, the experiment time can be shortenedradically as compared to indirect spectral phase encoding. The experiment time in this casewas at least 18 times shorter than a theoretical indirect spectral encoding, which woulddemand the number of the phase encoding steps to be defined by the ratio between thespectral width and the smallest frequency difference of neighboring signals (1800 Hz and100 Hz in our case, respectively).

6.6 Summary

Paper I concerned with high resolution imaging of lab-on-a-chip microfluidic reactors.We have succesfully demonstrated the usefulness of the RD-EXSY method in providingchemical information and revealing reaction pathways. Additionally, the TOF informationwas shown to be useful, for example, in providing indirect spatial information for RD-EXSY, therefore revealing the active regions of the studied reactor. A Hadamard encodingscheme was also employed in the study to efficiently implement indirect encoding of thespectral dimension, greatly shortening the experimental time otherwise required in spatiallyencoded RD-EXSY (more than an order of magnitude). The novel experimental setupallowed to characterize quickly and accurately the active reaction regions while presentinginformation also about the chemical exchange. Hadamard spectroscopy has been appliedto fast protein resonance assignment [115–117], single-scan 2D NMR [118, 119] andhyperpolarization applications [120] but, our experiments represented the first applicationin chemical reaction imaging.

7 Characterization of the catalytic performance of ALDdeposited platinum nanoparticles in microfluidic reactors

(II)

Catalysts are employed in many industrial processes. Due to strong demand for sustainabil-ity and due to the high costs for catalytic materials, the aim is to use noble metal catalystsin the most efficient way while producing as minimal amount of waste as possible. Eventhe most basic reactions, such as hydrogenation, can still be improved.

In Paper II, a novel microfluidic hydrogenation reactor was designed. Atomic layerdeposition (ALD) was applied to generate a catalyst layer out of platinum (Pt) nanoparticles(NP) with size of ca. 1-5 nm inside the microfluidic reactor. Continous flow propenehydrogenation was investigated as a model reaction by means of NMR and remote detectionNMR, while the amount of deposited platinum by the ALD method was varied. The activityof the novel Pt nanoparticle chips was compared to chips coated with Pt using sputteringmethod (see Chapter 6).

7.1 Microfluidic hydrogenation reactor

The main purpose of hydrogenation reactors is to bring hydrogen, catalyst and reactantinto contact in ideal conditions to achieve highest possible hydrogenation reaction yield.Recently, increased interest towards microfluidic solutions has generated a rising need forhigh reaction yield microfluidic hydrogenation reactors as the small dimensions offer manyintriguing benefits (see Chapter 5) for reactor design.

There are several papers about performing hydrogenation reaction inside microfluidicreactors [45, 121–124] but, so far, only a few studies have been conducted for microfluidicreactors which operate at moderate temperatures and pressures [121] or use ALD depositedplatinum nanoparticles as catalysts [112, 125]. Our work represents, for the first time,microfluidic chips in which ALD has been used to introduce the nanoparticles and thesupport directly into the channels of the microreactors.

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7.1.1 Atomic layer deposition

Atomic layer deposition (ALD) is a vapor phase method capable of depositing a variety ofmaterials as a thin films from the vapor phase. [126] Benefits of ALD are precise layerthickness control and tunable film composition. Therefore, the amount of wasted materialis minimal. The ALD process consists of alternating pulses of gaseous sustances. Asillustrated in Fig. 7.1 the precursors (A) are introduced to the surface placed in evacuatedchamber. [127] The substance is given some time to react with the surface. The chamber isthen flushed with an inert gas that removes the extra precursor and reaction side products.Next, the desired material (B) (in this case Pt-based precursor) is introduced to the chamberand let to react. The reaction chamber is once again evacuated from extra material. Thisprocedure may be repeated to achieve desired property, such as layer thickness.

ALD has been used to produce catalysts and supports for heterogeneous catalysis [128],but prior to our publication, it had not been applied directly to deposit metal catalystnanoparticles to a microfluidic reactor. In the wall-coated microreactors used in thestudy both TiO2 catalyst support and Pt catalyst were deposited with the ALD method.Additionally Pt nanoparticles were deposited by ALD on Piranha treated silicon (Si) wafer.(see Section 7.1.2 for description of Piranha treatment)

Figure 7.1. Atomic layer deposition basic sheme. a) Precursor (A) is introduced to thereaction chamber containing the surface to be coated. b) After the precursor has hadenough time to cover the whole surface the chamber is flushed to get rid of extra materialand reaction side-products. c) The desired material (B) is added to the chamber and let toreact with the precursor (A). After the layer is complete the volume is cleared from extramaterial and the process a)-d) is repated until the desired layer thickness (or other criteria)is achieved.

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7.1.2 Piranha treatment

Piranha is a mixture of sulfuric acid (H2SO4) and hydrogen peroxide (H2O2) [82] (mostcommonly with 3:1 or 7:1 ratio, in this paper 4:1 ratio was used). The mixture is used toremove organic residues off from surfaces. Piranha is strongly oxidizing and therefore itremoves most organic matter and hydroxylates most surfaces. It is also highly corrosive.Piranha is widely used in microelectronics to clean silicon wafers and to etch circuit boards.In this study Piranha treatment was used to oxidize the silicon surface of the wafer.Thetreatment was done by dipping the reactors into the solution at room temperature for 60seconds before the Pt deposition by ALD.

7.2 Microreactor fabrication

The chips were produced in a similar manner as explained in section 6.2 but in this casethe platinum was positioned on the surface by the ALD method. Pt nanoparticles weredeposited on two different supports, ALD deposited TiO2 or Piranha treated Si. Thesupport options were treated with different amounts of ALD cycles (5, 10, 20, 40, 50) toproduce different sizes of the Pt nanoparticles. Instead of using glass to seal the chips a125 µm thick commercial laminating foil (Fellowes Laminating Pouches), was used for theALD treated chips. The foil has three layers: 75 m polyethylene terephthalate (PET), 25 methylenevinyl acetate (EVA), and 25 m low density polyethylene (LDPE). The LDPE wasused as the bonding surface. The foil allows proper seal even though the Pt nanoparticleswere also on the bonding surface and therefore prevented the use of glass. The foil is agood choice in low temperature and pressure reactions. Further details of manufacturingcan be found in Paper II.

In the following text the chips are marked as chip Xc, Ymm, which means that the chiphad X cycles of ALD deposited Pt and the reactor channels were Y mm long. If the chiphad Piranha treatment, it is indicated with the capital letter P in front of the number of ALDcycles (for example, P50c, 20mm). The studied chips consisted of 36 parallel channelswith 50 µm wide and 100 µm deep channels (only 60 µm for P50c, 20 mm chip) (see Fig.7.2). The length of the channels was either 5, 10 or 20 mm. The channels were connectedto inlet and outlet by a perpendicular 200 µm wide channel.

7.3 Nanoparticle characterization

Transmission Electron Microscope (TEM) and Scanning Electron Microscope (SEM) wereused for imaging of the surfaces. TEM images of TiO2 with 10, 40 and 80 cycles of Ptand SEM images of Piranha treated Si (PirSi) with 40 and 50 cycles of Pt are shown inFig. 7.3. The particle sizes and surface coverage were estimated by using Fiji-imageanalysis software. The analysis shows that the particle size distribution widens withincreasing number of ALD cycles (see Fig. 7.4 and Table 7.1). This indicates that newparticles kept forming on the surface with increasing number of the ALD cycles. Narrow

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distribution of the size would be preferable as the catalyst properties depend on the size ofthe nanoparticles. Additionally it can be seen from the images that some particles havestarted to grow together especially in the cases of 80 cycles of Pt on TiO2 and 50 cyclesof Pt on PirSi. As seen in Fig. 7.3 d and e as well as in the Table 7.1 there is a hugedifference in the surface coverage between the piranha treated chips. This is presumablydue to difference in the Piranha treatment. In the case of the 40 cycles of Pt no fresh H2O2

was added to the solution in the treatment tank making the solution weaker than in the caseof the chips with 50 cycles of ALD. More details of the particle size analysis can be foundform Paper II.

Figure 7.2. Chip design and the experimental setup for RD NMR. The chip was positionedin the center of the encoding coil by the home-built sample holder and the detection coilwas hand wrapped around the outlet capillary.

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Figure 7.3. On the top row the TEM images from a) 10 b) 40 and c) 80 ALD cyclesof Pt depostied on top of TiO2 are shown. The lower row shows the SEM images of Ptnanoparticles on PirSi surface with d) 40 and e) 50 cycles of ALD.

Figure 7.4. Platinum particle size distribution calculated from the TEM images.

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7.4 Characterization of the reactor performance

The yield of the hydrogenation reaction of propene into propane and the activity ofthe catalytic surface was monitored by measuring 1H NMR spectra with the detectionmicrosolenoid wrapped around the outlet capillary (see Fig. 7.2). The microsolenoidprovides an 800-fold sensitivity boost compared to the large imaging coil surroundingthe sample. Remote detection was utilized to visualize the gas flow inside the reactors bymeasuring yz-encoded TOF images. The surface properties of the chips were also studiedby using parahydrogen-enriched hydrogen gas in the hydrogenation.

The measurements were performed with two spectrometers (Bruker Avance III 300and Bruker DSX 300). The same double-probe setup was used in the study as explainedin section 6.4. The flow system was also the same as described already in the section6.3. However, in this time, the reaction was performed with a 1:3 mixture of propeneand hydrogen (pressure was 5.7 bar) for the ALD chips and with 2:3 mixture at 7.5 barfor P50c, 20 mm. The experiments were performed first at room temperature and thenrepeated at elevated temperature of approximately 50◦C. The TOF images of pure propene(seen in Fig. 7.5) were measured at 4.3 bar.

7.4.1 Two-dimensional TOF imaging

Two-dimensional yz-encoded TOF experiments [5] of pure propene were conducted toinvestigate mass transport through the reactors. As an example, a chip with 20 mm longreactor channels is shown in Fig. 7.5. The signal forms an arrow shape because the flowpath via the outermost channels is slightly longer than the path through the channels in themiddle. The arrow is getting elongated with longer TOF times (time indicated in red on

Table 7.1. Mean particle size and surface coverage of the Pt nanoparticles calculated usingTEM images for TiO2 and SEM images for Piranha treated Si.

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top of the images) because the flow velocity is slightly lower in the outer channels. We candeduce that the gas is flowing similarly in all the channels as the dispersion is small andthe shape of the arrow is regular. This also indicates that there were no big differences inthe channel dimensions. For all the chips, similar arrow shapes were observed.

Additionally, the TOF images were used to estimate the contact time (time it takesfor the mixture to flow through the chips). The flow rate of the gas mixture throughthe detection coil was kept same for all the measurements (1.8 cm/s) if not mentionedotherwise. For the 20 mm long reactors the contact time was 1100 ms whereas for the 10mm long reactors it was 550 ms. For P50c, 20mm chip the contact time was estimated tobe 620 ms. The shorter time is a consequence of the smaller channel depth.

The T1 relaxation time was also determined from the TOF images (as explained inref. [78]). The resulting T1 was estimated to be 600±90 ms for propene. Because therelaxation time is shorter than the time it takes for the gas to flow through the whole chipand reach the detector, the sum of the panels in Fig. 7.5 (the right most figure) has highersignal intensity in the low parts of the chip (close to the detector). As can be seen, thetravel time indicated in the last panel is about two times the T1 relaxation time.

7.4.2 Reaction yield

The reaction yield was studied by measuring a 1H NMR spectrum of the gas mixture at theoutlet tubing by the detection coil right after the flow was started and 65 minutes later atboth temperatures (room temperature and 50◦C). Additional time steps were measured forchip 40c, 20mm at elevated temperature to follow the performance of the reactor with time.

Figure 7.5. The yz-encoded TOF images of pure propane flowing through a chip with 20mm long reactor channels. The outlines of the channels are marked with white lines. Thetime-of-flight (ms) is written with red numbers on top of each panel. A sum of the panelsis seen on the right hand side.

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The 1H NMR spectra of the gas mixture at room temperature at the beginning of theflow for the chips with TiO2 can be seen in Fig. 7.6. Despite of the small detection volume(53 nl), small sample volume, short residence time within the coil (14 ms) and the effect ofthe magnetic susceptibility caused by the proximity of the encoding RF coil, the resolutionand SNR is sufficient for the separation of the different spectral components arising fromthe different gases. A stopped flow experiment resulted in a line-width of ca. 40 Hzwhereas the continuous flow caused the width to be about 100 Hz.

The reaction yield was estimated from the integrals of the signals in the 1H spectra byfitting Gaussian lineshapes with Origin 2016 program. The comparison was done for themost intense peaks arising from the CH3 groups of both substances. The resulting peakareas were then scaled so that the area was divided by the number of protons contributingto the signal. Therefore, the area for the propene CH3 group signal was divided by threeand the area of signal arising from the two propane CH3 groups was divided by six. Thereaction yield was then calculated by dividing the scaled area of propane with the sum ofthe scaled areas of propene and propane. The yields at both temperatures at the beginningof the flow are shown in Table 7.2. An error of less than 10% was estimated for the yields.

It can be clearly observed from the results seen in Table 7.2 that the reaction yieldincreases with the increasing number of ALD cycles and channel lenght. The dependenceon the number of cycles is almost linear until the 100% yield was reached in the TiO2

case. At room temperature 5c, 10mm chip did not give any yield whereas the yield of 40c,

Figure 7.6. 1H NMR spectra measured at room temperature for a gas mixture flowing outfrom the TiO2 supported reactors right after the start of the flow. The origin of each signalis indicated with numbers and colours (green = propene, blue = hydrogen, red = propane).

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20 mm chip was about 90%. The resulting yield at the elevated temperature was roughlydouble compared to the room temperature experiments. Both 20c, 20mm and 40c, 20mmresulted 100% yield at 50◦C.

The effect of flow rate was tested at room teperature with 5c, 10mm chip. With theflow rate used in rest of the experiments (contact time 550 ms) the reaction yield was zero.When the flow rate was slowed (contact time 1100 ms) a small reaction yield (6.5 %) wasobserved. It can be concluded that for the TiO2 case the yield is dependent on the reactorlength (although the nanoparticles are also in the inlet and outlet channels), contact time,temperature and flow rate.

For 40c, 20mm chip, additional time steps were measured to follow the decay of theyield with time. The flow was kept on for four hours at elevated temperature. During thistime the reaction yield dropped from 100% to 50% (see Fig. 7.7). After waiting a longertime the reactor was completely deactivated. The deactivation is probably caused by thepoisoning of the catalyst surface. The catalyst activity did not recover for the TiO2 chipsafter being treated with a flow of pure hydrogen gas at 50◦C . This treatment was, however,able to recover the catalyst activity of the Piranha treated chips and on chips with sputteredPt. The foil capping of the TiO2 chips prevented the use of higher temperatures whichcould possibly enable the catalyst reactivation.

The Piranha treated P40c, 20mm chip did not result in any observable reaction evenat elevated temperatures. On the other hand the P50c, 20mm showed a yield of 46% atroom temperature and 100% at 50◦C. This might be a result of a much higher surfacecoverage (46% vs. 5%) as seen in the Table 7.1. It also has to be taken into account that theexperimental conditions were not the same for these two types of chips. The P50c, 20mm

Figure 7.7. Reaction yield as a function of time for a 40c, 20mm chip at 50◦C.

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had lower channel depth (60 µm instead of 100 µm) and the propene to hydrogen ratio ofthe mixture used was 2:3 with the total pressure of 7.5 bar. Additionally, the contact timein the case of P50c, 20mm was shorter (650 ms instead of 1100 ms).

The reaction yields measured in our previous study [78] for microfluidic reactors (reactorlengths of 5, 10 and 20 mm) with sputtered Pt surface are also shown in the Table 7.2. Thevalues are much lower for these chips than the ones obtained for the ALD chips. Onceagain, the experimental conditions were not exactly comparable. The channel depth wasonly 50 µm and the sputtered chips had the Pt catalyst on all the four surfaces whereas thechips coated with the ALD method did not have any catalyst particles on the capping foil.The contact time was also shorter as can be seen from the Table 7.2.

Table 7.2. Active Pt surface area for samples with different reactors. Values for thereaction yield, reaction rate k and activity A are reported at the beginning of the flow bothfor room temperature and heated situation. * Overestimate (Particle coalescence makes theestimation used to calculate the area invalid). ** Reaction conditions differ from the othersin the paper II. *** Taken from Ref. [78].

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7.4.3 Chips activity based on the first order kinetics

In addition to the reaction yield, it is beneficial to look at the activity of the reactor. Thereaction yield does not take into account the fact that the change in the reactor lengthchanges the residence time of the gas inside the reactor as the flow rate is kept as constant.A better number to clarify the efficiency of the reactors is activity which tells the amountof produced propane per unit surface and time (see Table 7.2). This number takes also intoaccount the minor differences in total pressure of the flow system differing between eachmeasurement set. The activity can be obtained as follows based on first order kinetics.

The chemical process of propene hydrogenation is described by reaction:

C3H6 + H2 = C3H8. (7.1)

If the order of the reaction between propene and hydrogen over TiO2-supported platinumis assumed to be first and zero with respect to hydrogen and propylene, respectively, whichhas been shown to be approximately true for pumice-supported rhodium [129], the rate ofthe reaction, r, is

r =d [C3H8]

dt= k [H2]

1[C3H8]

0= k [H2] , (7.2)

where [B] is the concentration of substance B and k is the rate constant of the reaction(valid for small volume dV ). When this equation is solved (see Supporting information ofPaper II), the rate constant k is

k =u0lR

(χ

4+

3

4ln[1− χ

3

]+ ln

[3

3− χ

]), (7.3)

where u0 is the linear flow velocity, lR is the reactor length and the χ is the reaction yield.The rate constants calculated can be seen in Table 7.2.

Eq. (7.2) can also be used for determination of the specific catalytic activity. By usingthe standard definition for continuous flow reactors we get activity

A =3PVRk

4RTAPt, (7.4)

where P is the total pressure of the gas mixture, and the factor 34 takes into account the

partial pressure of H2 in the gas mixture, k is the rate constant calculated with Eq. (7.3), Ris the universal gas constant, T is the temperature, V R is the volume of the microfluidicchip, which is 2.3 � 10−9m3 for the 10 mm reactor and 3.8 � 10−9m3 for the 20 mm reactor.APt is the Pt surface area which is determined from

APt = 2ScAS , (7.5)

where the Pt particles on the channel surfaces were assumed to be half-spherical, AS isthe total surface area of the channels and Sc is the surface coverage. The activity valuescan be also seen in Table 7.2. It can be concluded that the surfaces with 20 cycles of ALDdeposited Pt were the most active (11-17 mmol s−1m−2 at room temperature and 31 mmols−1m−2 at elevated temperature). The particle size distribution analysis (Fig. 7.4 andTable 7.1) shows that after 20 cycles of ALD the surface has quite narrow distribution of

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nanoparticles between 0.5 and 2.5 nm. Because the activity in the case of 5 and 10 ALDcycles was lower and they had the mean particle size below 1 nm, it can be concluded thatthe particles between 1 and 2 nm are the most efficient. The activity drop in the case ofthe 40 cycles of ALD can be explained by the wide particle size distribution (1-5 nm). Ascan be seen in Fig. 7.4 the percentual amount of the particles at the correct size range hasdramatically dropped.

7.4.4 Pairwise addition

NMR studies using PHIP have demonstrated that pairwise H2 addition can occur in homo-geneous and heterogeneous [130–132] hydrogenation over supported Pt catalysts. Pairwiseand random addition processes in hydrogenation reactions are normally indistinguishable.However, if a parahydrogen enriched hydrogen gas was used and PHIP [40, 47, 124, 133]effect were to be observed in the NMR measurement, it would mean that the surfaceproduces a pairwise hydrogenation reaction and therefore preserves the parahydrogenpairs in the addition process. The pairwise addition of the both hydrogens to magneticallyinequivalent position in the same target molecule would cause a significant, up to 105

signal enhancement in the resulting spectrum if the correlation of the spins is preserved.In this work we tested if the ALD deposited platinum nanoparticles can be used to

produce pairwise hydrogen addition inside the microfluidic reactor. It is stated in literaturethat the process is dependent on support used as well as on the size and the shape of theused nanoparticles. [112–114] In previous studies the best PHIP effects were observed fornanoparticles with size below 1 nm [131] and for TiO2 support [130]. Our microreactorsare close to these conditions as can be seen in Fig. 7.4. In these studies, however, powder-like catalysts were used and the preparation method was completely different. While ourchips produced high activity values, there was no observable PHIP effect. This impliesthat the pairwise addition is not dominantly occurring during the hydrogenation, whichmight be caused by the differences in the preparation of the Pt surface.

7.5 Summary

A novel way to produce efficient microfluidic hydrogenation reactors was presented in thePaper II. ALD deposited nanoparticles demonstrated a remarkable catalytic activity andthe manufacturing method enables easy implementation of various channel and reactordesigns. ALD of metals is more challenging than that of oxides, but they display the fullbenefits of ALD.

At elevated temperatures, reaction yields up to 100% were produced. Reaction yieldindicated a strong correlation between the amount of ALD cycles, contact time and reactiontemperature. The activity study revealed that the surfaces with 20 cycles of ALD depositedPt were the most active. This knowledge combined with the particle size distributioncan be used to state that Pt particles between 1 and 2 nm are the most efficient. Thereaction mechanism was also studied with the use of parahydrogen. As no PHIP effect was

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observed, it can be hypothesized that the surface does not produce a pairwise addition ofthe hydrogens to the target molecule.

We also observed differences in poisoning and reactivation of Pt nanoparticles on TiO2

and Piranha treated silicon surface versus continuous sputtered Pt films. We were not ableto revive the ALD chips after the reaction yield had dropped to zero, while the referencechip could be recovered. This needs to be studied further to understand the differences inthese systems. The ALD chips also suffered from lack of durability as the chips did notstand the temperatures close to 70◦C and pressures over 5 bar.

8 Quantifying the adsorption of flowing gas mixtures inporous materials (III)

In Paper III, a novel RD NMR based method for in situ analysis of adsorption of flowinggases in mesoporous materials is introduced. Porous materials are widely employed, e.g.,as catalysts, desiccants, for the purification and separation of gases, pollution control andrespiratory protection [134]. The main need for the new method arises from the fact that, inmost of the applications depending on adsorption, gas mixtures are flowing through porousmaterial. Traditionally adsorption isotherms are, however, measured in static equilibriaconditions. Additionally, the measurements are mainly done for a single gas componentas the measurement of multicomponent adsorption isotherms is very challenging andtime-consuming. Because in most of the applications flow of gas is essential part of theprocess, a static measurement may give inaccurate view for the adsorption phenomena ofthe flowing systems.

Controlled pore glass and silica gel mesoporous materials were studied to demonstratethe potential of the novel RD NMR method for both single and multi-component flowinggases. The results were compared with the data measured using conventional adsorptionexperiment in static equilibrium pressure situation.

8.1 Adsorption on porous materials

Adsorption is a phenomenon which occurs when a fluid is allowed to reach its equilibriumstate while in contact with a solid or liquid surface. The fluid tends to create a film ofadsorbate on the surface and thus the concentration of the fluid molecules tends to be higherat the vicinity of the surface than in the free phase. Adsorption differs from absorption,which involves the fluid penetrating the surface. Adsorption of fluid on a solid surface is aspontaneous process which is always exothermic as the loss of freedom also causes thedecrease of the entropy.

Adsorption can be divided into two categories: 1. chemical adsorption, which is theprocess of chemical bonding and, 2. physisorption, in which no chemical bonds are formed.Physisorption will occur on any solid-gas interface and chemisorption happens only if the

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gas is able to form chemical bond with the surface atoms. In this study physisorption isstudied.

The amount of adsorbed fluid can be investigated in many ways. Traditionally adsorptionisotherms are measured in static equilibrium conditions. The acquired isotherm measuresthe number of adsorbed molecules at equilibrium as a function of pressure. The shape ofthe isotherm can give precious information about the adsorption process, filling of particlelayers and the surface of the absorbent. There are six types of adsorption isotherms forphysisorption (Fig. 8.1). [134]

According to Ref. [134] the main characteristic feature in the type I isotherm is thealmost horizontal and long plateau. This type of isotherm forms if the adsorption is limitedto a formation of a monolayer. The plateau in type II also indicates the formation of themonolayer but there is no saturation limit like in the case of type I. Type III is observedin situations where the adsorbent-adsorbate interactions are weaker than the interactionbetween adsorbates. Type IV is a variation of the type II with hysteresis loop and italso tends to level off with higher pressures. This kind of isotherm is obtained in finitemulti-layer formations corresponding to filling of capillaries. The type IV adsorption isusual for mesoporous materials. Type V is similarly a variation of the type III. Type VIforms a stair like figure due to layer-by-layer adsorption process.

Traditional techniques for the measurement of adsorption isotherms are relatively time-consuming even when a single-component gas isotherm data is collected. Furthermore, themeasurement of adsorption of gas mixtures requires a separate analysis of the compositionof the non-adsorbed gas.

Figure 8.1. The six main types of adsorption isotherms.

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8.2 NMR adsorption measurements

Both NMR and MRI have been utilized for the determination of adsorption. MRI canbe used to acquire spatially resolved concentration profiles and adsorption isothermsof gases in porous materials [135, 136]. NMR has been exploited in the determinationof the amount of adsorbed gas in static conditions by measuring the amplitude of thegas signal in the region outside the porous material, and converting it into the amountof substance [137, 138]. Therefore, this method can be considered analogous to thestandard static adsorption measurements, with an additional benefit that signals of differentgas components of a gas mixture are resolvable from the spectrum, making the multi-component gas adsorption analysis possible. However the setup can not be used for flowinggas.

If the spectrum would be measured directly from the sample region, the separation ofthe signals might be difficult. In Fig. 8.2 the susceptibility issues arising from the porousmaterial cause the spectral components of the two different gases (propane and propene)to be unresolvable (red dashed line) when the gas is measured in static condition fromthe sample region. The signal widening caused by the porous material is seen also inthe spectrum measured from the sample region from single gas (propane) (blue dottedline). RD NMR offers a solution to this problem. As the signal is detected outside of thesample, there are no susceptibility problems caused by the material, and signals can beseparated clearly (black solid line). The flow causes some signal broadening and thereforeJ-couplings can not be seen.

Figure 8.2. Comparison of the 1H spectra measured with RD detection coil (black solidline) outside the packed bed sample with continuos flow and the spectra measued directlyfrom the sample region in static situation (pure propane blue dotted line, mixture ofpropene and propane (with 1:1 ratio) red dashed line). The peaks are assigned withnumbers corresponding to chemically inequivalent sites. The sites are not resolved in thespectrum measured from the packed bed region in the case of mixture.

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The weakness of NMR and MRI is their insensitivity. This problem is aggravated whengases and their flow are under investigation. Furthermore, in the case of microreactors andmicrofluidics, the size of an overall device is much larger than the volume that containsthe porous material, leading to a very low filling factor of the NMR/MRI coil, which isaround the microfluidic device. RD NMR offers a remedy for the issue. As the detectionis performed at the outlet tubing, with a coil wrapped around it, the filling factor is muchbetter. Additionally, the detection coils used in this work were 300 to 700 fold moresensitive than the commercial encoding coil.

8.3 Remote detection NMR of gas adsorption

We investigated adsorption of continuously flowing single gases (propane and propene)as well as their mixture in packed beds of controlled pore glass (CPG) and silica gel (SG)materials. As the detection was performed outside the packed bed region, the spectra werenot influenced by the susceptibility issues or background signals caused by the porousmaterials. Because resonances of each gas component were well resolved in the spectra(see Fig. 8.2, black solid line), the amount of adsorption of each gas component as well asthe gas component analysis could be determined from the same data, measured only in afew minutes.

In the RD NMR adsorption experiments, the gas or a mixture of gases flows througha porous material packed bed (see Fig. 8.3). The capillary holding the material is thenconnected to another empty capillary called outlet capillary. If the average concentrationof the gas in the sample region was approximately equal to the one in the outlet tubing(without the effect of adsorption), the flow velocity in the sample region would be higherthan in the outlet as the solid porous material makes the free volume smaller in the packedbed region. In this assumption the diameters of both the sample and outlet tubing are thesame. However, in a previous study Zhivonitko et al. [45] found out that the flow velocity

Figure 8.3. Packed bed sample. Length of the sample column varied between 15 to 26mm. The inner diameter of the capillary was 0.5 mm in the case of controled pore glassand 0.41 mm in the case of silica gel material.

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of gas was lower in the packed bed region than in the empty capillary region. This is causedby the significant gas adsorption on the surface of the porous material. The adsorption alsomakes the average gas concentration in the packed bed region higher than in the emptyregion. Therefore, the observed average flow velocity through the sample region is lowerthan in the case of the empty tube.

A theoretical model describing the phenomena was derived (see Supporting Informationof Ref. [45]). The theory is based on four assumptions; Firstly, mass balance is presumed.This requires that the amount of gas that in a certain time period 4t travels trough across-section of an empty tube has to be equal to the value on in the packed-bed region.Secondly, the gas behaves like an ideal gas. Thirdly, the pressure drop is insignificantin the sample region. Lastly, the flow and adsorption are independent of each other. Inother words, during the flow through the sample region one molecule undergoes severaladsorption-desorption happenings. Under these conditions an equation for the amount ofadsorbed gas per unit area, nua, is

nua =P

sRT

[(d2ouod2pup

− φ)

1 + νporeρsolid(1− φ) ρsolid

− νpore]. (8.1)

Here, parameters dp and do are the inner diameters of the packed bed and outlet capillaries,respectively, P is the gas pressure, T is the temperature, R is the universal gas constant, sis the specific surface area of the porous material, φ is the porosity produced by the voidsbetween the particles, νpore is the specific pore volume and ρsolid is the density of thesolid skeleton of the particles (2.23g/cm3 [139]). Values of these parameters used in Eq.(8.1) are shown in Table 8.1 for the materials studied in this work.

On top of these parameters, the amount of adsorbed gas depends on the ratio of theflow velocities in the packed bed region, up, and outlet tubing, uo. These values can bedetermined from the z-encoded TOF RD NMR experiment. In the TOF image the averagelocation distribution of the spins on the z-axis is plotted against the travel time. Therefore,the slope of the amplitude pattern provides a straightforward way to determine the flowvelocity at different regions of the system from a single, fast experiment.

8.4 Samples

Adsorption of propene and propane gas (purity >99.5%) was studied in controlled poreglass (CPG, Millipore) and silica gel (SG, Merck) materials. Three CPG materials withpore diameters of 81, 115 and 237 Å (referred as CPR81, CPG115 and CPG237) and onesilica gel material with 100 Å pore diameter (marked as SG100) were studied. The sampleswere tested with various gases and gas mixtures. The experiments were also performedwith propyne, but they were not successful, because propyne was partially converted intoanother substance in the porous material, presumably due to a reaction with some residualmoisture. The sample packing and other relevant experimental setup information canbe read from Paper III. The properties of the materials and continuous flow packed bedsamples (mass and length of the sample column) used in the experiments are shown inTable 8.1.

The porous material was packed inside a capillary for the RD flow experiments. Random

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Table 8.1. Properties of the studied samples. * values specified by the manufacturer.

packing of identical spheres would theoretically result in inter particle porosity, φ, rangingfrom 0.36 to 0.44. The bulk porosity values for each sample, were calculated using thefollowing equation (Table 8.1)

φ =Vsample − Vsolidskeleton − Vpores

Vsample. (8.2)

Here Vsample is the volume of the packed bed calculated from the diameter and the lengthof the sample column. Vsolidskeleton is the volume of the porous materials solid skeletoncalculated using the mass and the density ρsolid of the sample. Vpores is the volume of thepores in the porous material (announced in cc/g by the manufacturers, see Table 8.1). Theresults range from 0.36 to 0.49 and the φ values were highest for CPG materials.

The CPG samples were packed in a 1/32” capillary with 0.5 mm inner diameter whilethe SG100 sample was packed in a 1/32” capillary with 0.41 mm inner diameter. Thelarger particle size distribution may be the cause why the SG100 sample has smaller interparticle porosity.

In order to get reference values for the RD NMR adsorption analysis, traditionaladsorption isotherm measurements were carried out for CPG115 and CPG237 materials.The samples were inserted in a 10 mm NMR sample tube (inner diameter 8 mm, volumeof an empty tube 9.38 ml), with the height of the sample pillar about 5 cm in both cases.

The porous materials were kept under vacuum at 50◦C overnight, before both the RDNMR and the reference adsorption measurements. This was done in order to remove themoisture and to keep the measurement conditions as similar as possible for both experimenttypes. The experiments were performed at room temperature, after cooling the samplesunder vacuum. The reference measurements for both propene and propane gases wereperformed separately.

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8.5 Measurements

8.5.1 Experimental setup for the RD NMR measurements

The measurements were performed with two Bruker spectrometers: Avance II 300 andDSX 300. Both of them are equipped with imaging system and operate at 300 MHz protonresonance frequency. The same double-probe system, as used in the previous Papers I andII (see Section 6.4), was modified to fit the needs of the adsorption experiment (see Fig.8.4). To keep the detection coil ca. 10 mm below the bottom of the encoding coil, new coilholders were 3D printed by using the stereolithography method (Formlabs Form II).

The flow system was also similar as described in Section 6.3. The remote detectionmeasurements for each sample were performed with propene, propane and mixture ofthese two gases. The pressure range for propene was 5-1.25 bar and for propane 8-1.25bar. The mixture was prepared with either 1:1 or 1:2 ratio of propane:propene with thepressure range of 8-1.25 bar. The measurements were performed from high to low pressurevalues by evacuating certain amount of gas from the gas container to achieve desired lowerpressure for the next measurement point. The flow rate was kept as constant as possibleby adjusting the valve at the end of the outlet tube to keep the refreshment time of thedetection coil stable thorough all the measurements.

Figure 8.4. Image of the double probe RD NMR setup with the packed bed sample.

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8.5.2 Adsortion measurements with RD NMR

As explained in the theory part (Section 8.3), to resolve the amount of adsorbed gasin continuous flow situation, one needs to measure the flow velocities of the gas in thesample region as well as in the empty tube. To do this, z-encoded TOF RD NMR imageswere measured for each pressure point. The details about the pulse sequences, pulselenghts and delays are reported in Paper III. Example of a measurement of propane flowingthrough CPG237 mesoporous material measured at room temperature is shown in Fig. 8.5.The slopes of the pattern, denoted by black dashed lines in the image, indicate the flowvelocities in the packed bed and empty outlet capillary regions. The slope is smaller in thepacked bed region (resulting a velocity of 5.1 cm/s) than in the outlet capillary (10.7 cm/s),although the inner diameters of the packed bed and outlet capillaries were equal.

The dispersion of gas is relatively small as the width of the signal pattern is narrow.This is a consequence of fast diffusional mixing of flow lamellas in the narrow capillaries.It also indicates that the exchange between gas inside the porous material and free gas isfast as compared to the travel time through the packed bed; otherwise significant dispersionwould be expected.

The flow velocities in the packed bed and outlet capillaries were determined from thez-encoded TOF images for all the samples at different pressure points, and they wereconverted into the amount of adsorbed gas per unit of the surface area of the porousmaterial, nua, by using Eq. (8.1). The results for single and competitive gas adsorption,along with the reference values given by standard, static adsorption measurements, areshown in Figs. 8.6 and 8.7.

Figure 8.5. Result of a z-encoded TOF experiment of a pure propane gas flowing throughCPG237 material. The two slopes (indicated with black dashed lines) can be used todetermine the flow velocity in the outlet (uo) and packed bed (up) capillary.

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8.5.3 Reference adsorption experiments

The physical principles of the volumetric gas adsorption experiment are quite simple. Aknown amount of gas in a volume is expanded into a volume which contains the adsorbent,in this case the porous material. The amount of free gas in the container can be calculatedbased on the equilibrium pressure. If the equilibrium pressure is lower than the calculatedpressure of the two combined volumes, the rest is assumed to be adsorbed on the absorbent.[134]

In our experiments the gas (propene or propane) was added to the sample tube from acontainer with the volume of 46 ml. The volume of the connection between the containerand sample tube was 0.84 ml.

At the beginning, 0.05 bar of gas was added to the container under vacuum. Then the gaswas allowed access also the sample volume and the pressure change was recorded after anequilibrium delay of 10-20 min. This process was repeated with a steps of approximately0.2 bar until the final pressure of 2.95 bar. The adsorption isotherm was calculated in astandard way based on the results [134]. The resulting values are shown in Fig. 8.6.

8.6 Results

8.6.1 Single gas adsorption results

The results from RD and standard measurement are seen in Fig. 8.6. In addition, referencevalues for propene and propane adsorption in silica gel (surface area of 751 m2/g) takenfrom Ref. [140] are shown. The values given by the novel RD NMR method are on thesame order of magnitude as the reference values. However, the values are systematicallylower. Based on the RD NMR, it can be deduced that the smaller the pore size and thesurface area of the adsorbent, the larger the difference is between the continuous flow andstatic equilibrium measurements. We, therefore, interpret that the difference is due to theeffect of the flow as with the flow no equilibrium surface will have time to form.

It is worth to note, that the increased concentration of gas molecules in the sampleregion might cause a significant flow resistance, which could lead to wrong results. Theresistance would be, however, observed in the measured z-encoded TOF as it would leadto a pressure gradient. This would cause increasing gas concentration with increasingspatial coordinate z. This, together with mass balance, would lead in decreasing velocityin the images, which would be seen as curved amplitude patterns. However, in all themeasurement conducted for different porous materials the pattern seen in the z-encodedTOF is very linear (see Fig. 8.5). Hence the flow resistance can be neglected.

The T1relaxation could also cause the results to be faulty. If the travel time of somemolecules (because the molecule got stuck for relative long time in a small pore, forexample) would be much longer than the longitudinal relaxation time, the contribution ofthose molecules would not be observed properly in the detected signal. This would lead tosignificant dispersion and would be observed as broad amplitude patterns in the z-encodedTOF images. As the observed patterns are narrow, the effect of dispersion can be said to benegligible. Thus it can be deduced that the observed lower amount of adsorbed gas in the

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Figure 8.6. Single gas adsorption. The standard static equilibrium measurements areindicated with open symbols (REF) whereas the RD NMR measurements are markedwith filled symbols (RD). a) Result for propane are shown. b) and c) Results for propeneadsortion. SG_REF values are taken from Ref. [140].

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RD NMR analysis as compared to the static measurements is not an artifact of the method,but it is a true phenomenon arising from the effect of the flow.

8.6.2 Competitive gas adsorption results

Multicomponent gas adsorption was also studied with RD NMR by measuring a mixtureof propene and propane. As the spectrum measured with the detection coil gives wellresolved signals for both gas components (see Fig. 8.2), the same z-encoded TOF datameasured at single pressure point can be used to solve adsorption values for both gases byusing the same Eq. (8.1). In this case the pressure P is the partial gas pressure of each gascomponent instead of the total pressure. The resulting values are shown in Fig. 8.7. In allthe figures the amount of adsorbed propene is higher than the amount of propane. Thisis in agreement with the values measured for single component gases, where the resultsindicated that the propene has higher adsorption values than propane. There is, however,one pressure point which is not following this trend: In Fig. 8.7 a, the adsorption valuemeasured at the total pressure of 8 bar has higher value for propane than propene. Thismight be due to a partial condensation of propane gas in small pores (the vapor pressure ofpropane is 8.5 bar). At room temperature, the amount of adsorbed molecules for each gascomponent is lower in the case of competitive adsorption than in the case of pure gases, asexpected. This due to the fact that many adsorption sites are already occupied by the othergas component of the mixture.

8.7 Summary

The results stress the importance of the RD NMR adsorption measurement method pre-sented in Paper III. Because the flow has a notable effect on the amount of adsorbed gasper unit area, it is important to be able to quantify adsorption in dynamic conditions. Thisis especially important as many everyday technological applications depend on gas flowingthrough porous materials. The RD NMR approach developed in this work provides aquick and sensitive way to measure adsorption under conditions relevant to these kindof applications. With single fast measurement, one can quantify the adsorption of eachgas component in a case of gas mixture adsorption. Results indicate a clear differencein the behavior of different gases, gas mixtures and adsorbents. The values given by theRD NMR analysis are on the same order of magnitude with the reference values, showingthat the method works. As expected, the flow causes the amount of gas adsorbed on thesurface to be smaller than in the traditional system because no equilibrium adsorption stateis reached while the gas is flowing. The results also imply that the smaller pore size andthe surface area yield a larger difference between the RD NMR and reference experiments.

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Figure 8.7. Results for RD NMR adsorption measurements in the case of competitiveadsorption of propene and propane. a) CGP81 is used as the porous material. Thepropane:propene ratio was 1:1. In b) the adsorbent is CPG115 and the gas ratio 1:1. c)CPG237 with the gas mixture with 2:1 ratio. In the figures the total gas pressure of themixture is used as the horizontal axis.

9 Summary and conclusions

The projects presented in this thesis are all based on the utilization of the remote detectionNMR method, in which the spectral, spatial or dynamic information about a studied systemis encoded in the spin coherence of fluid molecules by magnetic field gradients and a largecoil around the system, while the fluid is passing the sample. The information is readby a microsolenoid wound around the outlet tubing when the fluid flows out. Significantsensitivity enhancement is obtained due to the optimized filling-factor and smaller size ofthe detection coil. The technique is ideal for applications in microfluidic devices, whoselow fluid volumes make conventional NMR analysis difficult. The thesis consists of threejournal articles, Papers I-III, which can be found from the end of this thesis. Papers I andIII concentrate on development on novel remote detection NMR based methods whereas inPaper II RD NMR was used to characterize the performance of novel microfluidic reactors.

In Paper I we developed new methods for more accurate reaction imaging in microfluidicflow systems. As a result we introduced the concept of remote detection exchange (RD-EXSY) NMR spectroscopy. We demonstrated that the RD-EXSY method provides uniquechemical information, revealing reaction pathways and intermediate products. Furthermoretime-of-flight information, which is a natural side product of the experimental setup used,was converted into indirect spatial information, revealing the positions of the active reactionregions in a microfluidic device accurately.

In Paper I we also attacked the problem of the spatially resolved RD-EXSY. We illus-trated that direct spatial resolution can be added to RD-EXSY efficiently while applyingthe principles of Hadamard spectroscopy in the encoding of the indirect spectral dimension.The resulting spatially resolved Hadamard TOF EXSY allowed even more accurate char-acterization of the active regions, while keeping the advantages of RD-EXSY. Hadamardspectroscopy has been applied to protein assignment, single-scan 2D NMR and hyperpo-larization applications but never before in chemical reaction imaging.

Paper II presents novel microfluidic reactors in which the catalyzing nanoparticles weredeposited by ALD. We demonstrated that the novel reactors can produce high and quitelong lasting hydrogenation reaction yields at mild temperatures. In the study platinumwas chosen to be the test catalyst. ALD can be, however, used to deposit also other noblemetals and even bimetallic particles. This option allows more freedom in the catalystdesign as wall-coated microreactors enable easy implementation of many types of designschemes. In the study we showed that Pt nanoparticles between the size of 1 and 2 nm

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were the most active. Additionally, we observed differences in poisoning and reactivationof Pt nanoparticles on TiO2 versus Pt nanoparticles on Piranha treated silicon surface orcontinuous 100 nm thick sputtered Pt film. This needs to be studied further to understandthe differences in these systems.

Gas adsorption analysis is extremely important in many fields of industry, chemicalengineering and scientific research. In Paper III we presented a novel method for gasadsorption measurements in porous materials using remote detection time-of-flight NMRimaging. We developed an optimal experimental framework required for the investigationsof single and multicomponent gases and compared the obtained results with standardmeasurements of gas adsorption isotherms measured for the same materials. The resultsstress the importance of the RD NMR adsorption measurement method presented ,becausethe flow has a notable effect on the amount of adsorbed gas in unit area. Thus it isimportant to be able to quantify adsorption in dynamic conditions and the presented RDNMR approach provides a quick and sensitive way to measure adsorption under conditionsrelevant to many application dealing with gases flowing through porous materials. Witha single fast measurement, one can quantify the adsorption of each gas component in acase of multicomponent gas adsorption. RD NMR provides a significant, 300–700 -foldsensitivity gain and because the signal is detected outside the sample, the spectra arenot affected by the susceptibility issues and background signals arising from the porousmaterial. In the case of multicomponent gas mixture this means that the signals of eachcomponent are resolvable in the spectrum (contrary to the spectrum measured directly fromthe porous material region), and therefore adsorption of each component can be quantifiedfrom a single measurement data acquired in a few minutes.

The methods demonstrated in Papers I and III hold a great promise to be useful additionsto the already wide toolbox offered by NMR and MRI for the scientists and industry.This work has provided several new tools for the study of porous materials, adsorptionphenomena, chemical reactions and characterization of microfluidic reactors. Thesemeasurement setups can be combined with hyperpolarization methods to further increasethe signal strength or remote detection may be combined to relaxation or diffusion studies.Use of the RD NMR flow isotherms will hopefully be in the close future an actual way toacquire adsorption information. Faster experiments and more accurate characterization onactive reaction areas in microfluidic reactors may play important role in the forthcomingdevelopment of lab-on-a-chip devices.

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Original papers

I Reproduced with permission from the Angewandte Chemie International Edi-tion.V.-V. Telkki, V. V. Zhivonitko, A. Selent, G. Scotti, J. Leppäniemi, S. Franssilaand I. V. Koptyug,Lab-on-a-chip Reactor Imaging with Unprecedented Chemical Resolution byHadamard-Encoded Remote Detection NMR.Angewandte Chemie International Edition 53,11289-11293 (2014).Copyright (2014) Wiley-VCH Verlag GmbH Co. KGaA, Weinheim.

II Reproduced with permission from the Chemistry- A European Journal.V. Rontu, A. Selent, V. V. Zhivonitko, G. Scotti, I. V. Koptyug, V.-V. Telkki andS. Franssila,Efficient Catalytic Microreactors with Atomic Layer Deposited Platinum nanopar-ticles on Oxide Support.Chemistry- A European JournalAccepted version published in electronic form with theDOI:10.1002/chem.20170339 (2017).Copyright (2017) Wiley-VCH Verlag GmbH Co. KGaA.

III Reproduced with permission from the Microporous and Mesoporous Materials.A. Selent, V. V. Zhivonitko, I. V. Koptyug and V.-V. TelkkiQuantifying the adsorption of flowing gas mixtures in porous materials byremote detection NMR.Microporous and Mesoporous MaterialsAccepted version published in electronic form with theDOI:10.1016/j.micromeso.2017.05.040 (2017).Copyright (2017) Elsevier Inc.