M.Sc. (Chemistry) / Please refer to full text to view abstract

Ce travail a concerné la synthèse hydro-solvothermale et la caractérisation de nouveaux fluorures hybrides à porosité variable, dans l’objectif à terme de tester ces matériaux poreux en stockage ou purification de gaz. En première partie, l’aminotétrazole a été utilisé comme ligand organique et a permis de mettre en évidence douze nouveaux fluorures hybrides, dont six sont de type MOF. Plusieurs paramètres de synthèse ont été identifiés comme cruciaux dans la condensation d'édifices ouverts. C’est, en particulier, la température, la composition du milieu ainsi que la nature des cations métalliques (Zn2+/Fe3+, Fe2+/Fe3+ et Zn2+ seul) et du solvant. Les porosités estimées de ces MOF atteignent 25% en volume bien que la taille de l’aminotétrazole soit réduite. En seconde partie, des ligands plus étendus à noyaux tétrazoliques multiples ont été choisis afin de parvenir à augmenter la dimension des cavités des MOFs. Ces molécules, non commercialisées, ont été synthétisées dans un premier temps puis impliquées dans l’élaboration de nouveaux hybrides. Alors que la molécule H3btt à 3 noyaux tétrazole n’a pas abouti à des résultats, H2bdt a conduit à de nouvelles architectures fluorées en présence de Zn et/ou Fe. Deux d’entre elles, [Hdma]∙(FeIIF(bdt)) et FeIIF(Hbdt), présentent des porosités remarquables de 40 et 60% qui s’approchent de celles des matériaux de référence. / This work focuses on the hydro-solvothermal synthesis and the characterization of new hybrid fluorides with tunable porosity, with the aim of testing new porous materials for gas storage and purification. In the first part, the aminotetrazole was used as organic linker and twelve new hybrid fluorides were evidenced, six phases belong to MOFs class. Several parameters were identified as crucial for the condensation of open frameworks, in particular, the temperature, the medium composition as well as the nature of metallic cations (Zn2+/Fe3+, Fe2+/Fe3+ or only Zn2+) and of the solvent. The porosity of these MOFs reaches 25% of volume, in spite of the small size of the aminotetrazole molecule. In the second part, polytetrazoles linkers with extended size were chosen, in order to increase the size of MOFs cavities. Non-commercial molecules were prepared and applied to the elaboration of new hybrids. While H3btt with 3 tetrazole cycles did not provide any expected result, H2bdt led to new fluorinated architectures in the presence of Zn and/or Fe. Two phases, [Hdma]∙(FeIIF(bdt)) and FeIIF(Hbdt), exhibit remarkable porosities of 40 and 60%, values.

In this dissertation, investigations regarding magnetism within metal-organic frameworks (MOFs) based on calculations in the framework of density functional theory (DFT) were carried out. On the one hand, the intrinsic magnetic properties within the MOF DUT-8(Ni) were studied (DUT -- Dresden University of Technology). This MOF is flexible, thus it can exist in two crystal structures named DUT-8(Ni)ppen and DUT-8(Ni)closed. A transition from one structure to the other can be achieved via e.g. gas adsorption, leading to a volume increase of approximately 260 %. The magnetic properties originate from spin-spin interactions between the unpaired electrons at the Ni centers. The magnetic coupling between the Ni ions was found to be low-spin (antiferromagnetic). Considering that MOFs tend to have rather large unit cells (> 100 atoms), model systems (< 30 atoms) were generated. Such models can qualitatively as well as quantitatively describe the coupling inside the crystal structure while drastically reducing computational time. Furthermore, the model systems can be easily altered e.g. to introduce defects. The influence of these alterations on the magnetic coupling was studied. In addition, the metal centers have been exchanged by other 3d-metals to analyze the coupling constant with respect to different magnetic centers. On the other hand, the magnetic shielding of Xe adsorbed into the MOFs UiO-66 and UiO-67 was investigated (UiO -- University of Oslo). Based on high-pressure nuclear magnetic resonance (NMR) measurements, which showed a decrease of the total chemical shift when going from the smaller MOF (UiO-66) to the larger one (UiO-67), a thorough theoretical analysis was carried out. For this purpose the ansatz of Ito and Fraissard, i.e. the chemical shift of Xe being a sum of different contributions, was employed. Accordingly, model systems which describe the influences of the MOFs and adjacent Xe atoms on the magnetic shielding were contructed. After equilibrating the Xe positions using molecular dynamics simulations, these model systems were taken to study the chemical shift of all Xe atoms individually. Thus, an analysis of the chemical shift inside each pore of the MOFs was carried out. This allows a description of different influences (Xe-surface, Xe-Xe) on the chemical shift, explaining the experimental behavior at an atomistic level.

<div> <p>Metal-organic frameworks (MOFs) are a class of compounds consisting of metal ions or clusters coordinated to organic ligands in porous structure forms. MOFs have been proposed in use for gas adsorption, purification, and separation applications. This work combines MOFs with 3D printing technologies, in which 3D printed plastics serve as a mechanical structural support for MOFs powder, in order to realize a component design for gas adsorption. The objective of the thesis is to understand the gas adsorption behavior of MIL-101 (Cr) MOF coated on 3D printed PETG, a glycol modified version of polyethylene terephthalate, through a combined experimental and modeling study. The specific goals are: (1) synthesis of MIL-101 (Cr) MOFs; (2) nitrogen gas adsorption measurements and microstructure and phase characterization of the MOFs; (3) design and 3D printing of porous PETG substrate structures; (4) deposition of MOFs coating on the PETG substrates; and (5) Monte Carlo (MC) modeling of sorption isotherms of nitrogen and carbon dioxide in the MOFs.</p><p>The results show that pure MIL-101 (Cr) MOFs were successfully synthesized, as confirmed by the scanning electron microscopy (SEM) images and X-ray diffrac- tion (XRD), which are consistent with literature data. The Brunauer-Emmett-Teller (BET) surface area measurement shows that the MOFs samples have a high cover- age of nitrogen. The specific surface area of a typical MIL-101 (Cr) MOFs sample is 2716.83 m2/g. MIL-101 (Cr) also shows good uptake at low pressures in experimental tests for nitrogen adsorption. For the PETG substrate, disk-shape plastic samples with a controlled pore morphology were designed and fabricated using the fused de-</p><p> </p><p>position modeling (FDM) process. MOFs were coated on the PETG substrates using a layer-by-layer (LbL) assembly approach, up to 30 layers. The MOFs coating layer thicknesses increase with the number of deposition layers. The computational model illustrates that the MOFs show increased outputs in adsorption of nitrogen as pres- sure increases, similar to the trend observed in the adsorption experiment. The model also shows promising results for carbon dioxide uptake at low pressures, and hence the developed MOFs based components would serve as a viable candidate in gas adsorption applications.</p><div><br></div></div>

The emerging field of nanomaterials has raised a number of fascinating scientific questions that remain unanswered. Molecular theory and computer simulation are key tools to unlocking future discoveries in materials science, and various computational techniques and results toward this goal are elucidated here. High-performance computing methods (utilizing the latest supercomputers and codes) have been developed to explore and predict the chemistry and physical properties of systems as diverse as Metal-Organic Frameworks, discrete nanocubes, photoswitch molecules, porphyrins and several interesting enzymes. In addition, highlights of fundamental statistical physics, such as the Feynman-Hibbs effective partition function and generalized ensemble theory, are expounded and upon from the perspective of both research and pedagogy.

Ce projet concerne la synthèse et caractérisation de nouveaux matériaux composites à base de nanoclusteurs de thiolates d’or Au25(SR)18 (tGNCs), supportés sur divers polymères de coordination (MOFs), ainsi que sur ZrO2. L’activité catalytique de ces matériaux a été évaluée sur la transformation de différents substrats. Les tGNCs sont des matériaux atomiquement bien définis et connus pour être actifs dans des réactions d’oxydation. Les nanoparticules de MOFs sont des matériaux pouvant servir de support pour des tGNCs avec de bonnes dispersions. Certains MOFs sont connus pour avoir des propriétés acides et peuvent être actifs en catalyse. Parmi eux, MIL-101 (Cr), UiO-66 (Zr) et ZIF-8 (Zn) on été choisis en raison de leur propriétés acides et/ou de stabilité thermique. La synergie entre les tGNCs et les MOFs a été évaluée à travers la conversion catalytique de différents substrats tels le glucose, le fructose, l’alcool benzylique et le furfural, impliquant des étapes nécessitant un caractère acide et/ou oxydant. Globalement, il n’a pas été observé d’impact de la présence d’or sur la réactivité de ces substrats, et les tendences catalytiques sont celles obtenues avec les MOFs seuls. Cela est certainement dû à la stabilité thermique non suffisante des MOFs qui prévient une calcination efficace des tNGCs. Lorsque ces clusters sont déposés sur ZrO2, il a été possible de les calciner à différentes températures pour étudier l’effet du ligand et de la taille de particules, pour des réactions d’oxydation en phase liquide. Ainsi, il a été montré par exemple que la température de calcination a un impact significatif sur le comportement catalytique de ces composites, qui ont donné de bonnes activités pour l’oxydation de l’alcool benzylique en benzaldéhyde dans le toluène et en conditions douces, et pour l’esterification oxydante du furfural en furoate de méthyle / This research project reports the synthesis and characterization of new composite materials based on Au25(SR)18 thiolate gold nanoclusters (tGNCs), supported over a range of metal organic frameworks (MOFs), and ZrO2. The synthesized composite materials were tested for catalytic transformations of various substrates. tGNCs are atomically well defined materials known to be active in oxidation reactions. MOFs nanoparticles are materials suitable for high dispersion of tGNCs. Some MOFs are known to have acidity and can be active as catalysts. Among them, MIL-101 (Cr), UiO-66 (Zr) and ZIF-8 (Zn) were chosen due to their acidic and/or thermal stability properties. The synergy between tGNCs and MOFs has been tested through catalytic conversions of different substrates like glucose, fructose, benzylalcohol and furfural, involving steps requiring acidic and oxidative features. Globally, no impact of the presence of Au clusters was observed, and the composite materials showed the same catalytic trends as those obtained with the MOFs alone. This is mainly due to the not sufficient thermal stability of the MOFs that prevents efficient calcination of the tGNCs. In contrast, when deposited on ZrO2 it was possible to calcine Au25(SG)18 nanoclusters at different temperatures to study the ligand and particle size effects in liquid phase oxidation reactions. For example, the calcination temperature had a significant impact on the catalytic behaviour of this composite materials, which showed good activity for the oxidation of benzyl alcohol into benzaldehyde in toluene under mild conditions, and of furfural oxidative esterification into methyl-2-furoate

A straightforward means to include explicit hydrogen bonds within the Universal Force Field (UFF) is presented. Instead of treating hydrogen bonds as non-bonded interaction subjected to electrostatic and Lennard-Jones potentials, we introduce an explicit bond with a negligible bond order, thus maintaining the structural integrity of the H-bonded complexes and avoiding the necessity to assign arbitrary charges to the system. The explicit hydrogen bond changes the coordination number of the acceptor site and the approach is thus most suitable for systems with under-coordinated atoms, such as many metalorganic frameworks; however, it also shows an excellent performance for other systems involving a hydrogen-bonded framework. In particular, it is an excellent means for creating starting structures for molecular dynamics and for investigations employing more sophisticated methods. The approach is validated for the hydrogen bonded complexes in the S22 dataset and then employed for a set of metal-organic frameworks from the Computation-Ready Experimental database and several hydrogen bonded crystals including water ice and clathrates. We show that the direct inclusion of hydrogen bonds reduces the maximum error in predicted cell parameters from 66% to only 14%, and the mean unsigned error is similarly reduced from 14% to only 4%. We posit that with the inclusion of hydrogen bonding, the solvent-mediated breathing of frameworks such as MIL-53 is nowaccessible to rapid UFF calculations, which will further the aim of rapid computational scanning of metal-organic frameworks while providing better starting points for electronic structure calculations.

This thesis explores the use of computational chemistry and machine learning techniques to aid in the design of Metal-Organic Frameworks (MOFs) for use in postcombustion carbon capture and storage (PoC-CCS). PoC-CCS is an ongoing field of research which aims to selectively remove carbon dioxide, an important greenhouse gas, from the exhaust of fossil-fuel burning powerplants. By using a suite of advanced simulation techniques, high-throughput screenings were performed on thousands of MOFs to study their behaviour in a pressure swing adsorption (PSA) system. To develop a comprehensive picture of a material’s performance, the behaviour of individual gas molecules within the pores of the crystal structures to the material’s performance in industrial scale PSA columns was evaluated. To study the behaviour of individual gas molecules within the pores of a MOF, a new algorithm which can accurately determine the locations of gas binding sites was developed. This algorithm, which relies on probability distributions generated through grand canonical Monte Carlo simulations (GCMC), was optimized for CO2 with the goal of use in high-throughput screening. By tuning the user-controlled parameters for a desired gas, this algorithm, which was named the Guest Atom Localization Algorithm (GALA), was shown to accurately reproduce experimentally determined binding sites while being run in a high-throughput manner with no user intervention. Studying MOFs at the pore or crystal scale in this manner provides valuable insights into the behaviour of gases within the materials. A major shortcoming, however, is the lack of direct insight into the material’s behaviour in industrial systems. Materials scientists and MOF chemists have historically focused on a set of performance metrics measured at this scale; however, no clear connection can be made between such metrics and the performance of that sorbent material in a PSA column. To bridge this gap between MOF chemists and the process engineers studying the PSA systems, a large-scale screening of MOFs was performed using a sophisticated PSA simulator designed to reproduce the performance of an 80 kg PSA column. By supplying isotherms obtained using GCMC simulations to be used as inputs into the PSA simulator, a multi-scale high-throughput screening of MOFs for PoC-CCS was performed for the first time under coal-fired powerplant conditions. This multi-scale screening provided the ideal conditions to study the materials science performance metrics and their relationships to industrial PSA performance. To study this relationship, a series of machine learning and artificial intelligence techniques were employed. The primary goal was to extract important relationships between the materials science and industrial PSA performance metrics, with a secondary goal of developing a predictive model which could be used to accelerate the pace of materials discovery. Through the use of machine learning, several metrics were identified which could be used to predict whether a material could meet the minimum target of 95 % purity of captured CO2, and 90 % removal (or recovery) of CO2 from the flue gas stream. Among them was the isotherm parameters for N2, the most abundant species in the flue gas. This finding was significant as to date the focus among MOF chemists studying the PoC-CCS system was placed primarily on the CO2 metrics, with N2 only implicitly considered when calculating the CO2/N2 selectivity. Although several metrics were identified which could predict the purity and recovery targets, none of the conventional metrics tested could be used to estimate the energetic cost of capture or the size of the capture plant, both important considerations in evaluating the cost of capture. The relationship between N2 binding within the pores of the MOF and its ability to meet the purity-recovery targets was explored using GALA. Using a Tanimoto similarity metric and the ratio of single component and competitive loadings, the CO2 and N2 binding environments were studied. It was determined that when the N2 binding environment was significantly altered by the presence of CO2, the material was more likely to meet the purity-recovery targets. Further analysis found that this change in binding environments was correlated to a reduced N2 uptake in the presence of CO2, implying that the competition for binding sites within the pores of the MOF is an important indicator for the material’s ability to meet the purity-recovery target. For the first time, a direct relationship between the behaviour of individual gas molecules to industrial PSA performance can be reported. Although the PSA simulator used throughout this work has proven to be a powerful tool for materials discovery, several shortcomings still exist. The first is the method used by the simulator to predict the loadings at various points within the column. This method relies on single component isotherm data despite the ability of GCMC to simulate multi-component isotherms. An alternative method to using single component isotherms was proposed which relies on multi-component isotherm data and a linear interpolation model. The existing method was compared to the new proposed interpolation method, and it was found that the loadings predicted using the interpolation method were more accurate. The second shortcoming of the PSA simulator is the computational expense associated with the optimizations. Using the PSA simulator, a single material may take up to a week to be fully optimized on a high-performance computing cluster. To increase the pace of materials discovery, a surrogate model was developed using the data accumulated over the course of the work presented in this thesis. Using artificial neural networks, a suite of models was developed which reproduces the outputs of the PSA simulator and is able to optimize a single MOF in a matter of minutes. This suite of models, known as the Fossil Fuel Combustion for Carbon Capture and Storage (FoCAS) was used to perform a screening of over 4,000 materials.

Indiana University-Purdue University Indianapolis (IUPUI) / Metal-organic frameworks (MOFs) are a class of compounds consisting of metal ions or clusters coordinated to organic ligands in porous structure forms. MOFs have been proposed in use for gas adsorption, purification, and separation applications. This work combines MOFs with 3D printing technologies, in which 3D printed plastics serve as a mechanical structural support for MOFs powder, in order to realize a component design for gas adsorption. The objective of the thesis is to understand the gas adsorption behavior of MIL-101 (Cr) MOF coated on 3D printed PETG, a glycol modified version of polyethylene terephthalate, through a combined experimental and modeling study. The specific goals are: (1) synthesis of MIL-101 (Cr) MOFs; (2) nitrogen gas adsorption measurements and microstructure and phase characterization of the MOFs; (3) design and 3D printing of porous PETG substrate structures; (4) deposition of MOFs coating on the PETG substrates; and (5) Monte Carlo (MC) modeling of sorption isotherms of nitrogen and carbon dioxide in the MOFs. The results show that pure MIL-101 (Cr) MOFs were successfully synthesized, as confirmed by the scanning electron microscopy (SEM) images and X-ray diffraction (XRD), which are consistent with literature data. The Brunauer-Emmett-Teller (BET) surface area measurement shows that the MOFs samples have a high cover- age of nitrogen. The specific surface area of a typical MIL-101 (Cr) MOFs sample is 2716.83 m2/g. MIL-101 (Cr) also shows good uptake at low pressures in experimental tests for nitrogen adsorption. For the PETG substrate, disk-shape plastic samples with a controlled pore morphology were designed and fabricated using the fused deposition modeling (FDM) process. MOFs were coated on the PETG substrates using a layer-by-layer (LbL) assembly approach, up to 30 layers. The MOFs coating layer thicknesses increase with the number of deposition layers. The computational model illustrates that the MOFs show increased outputs in adsorption of nitrogen as pressure increases, similar to the trend observed in the adsorption experiment. The model also shows promising results for carbon dioxide uptake at low pressures, and hence the developed MOFs based components would serve as a viable candidate in gas adsorption applications.

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