Rozprawy doktorskie na temat „Crystal Engineering Approach”

Doctor of Philosophy
Department of Chemistry
Christer B. Aakeroy
The work presented in this thesis has demonstrated that supramolecular synthons can be used to make multicomponent crystals, and various synthons can be combined to make supermolecules. The synthons can also be used to construct nanoscale assemblies. Molecules containing single and multiple hydrogen-bond (HB) and halogen-bond (XB) acceptor sites have been synthesized in an effort to carry out supramolecular synthesis in order to establish a reliable hierarchy for intermolecular interactions. Pyrazole-based molecules have been made, combined with various carboxylic acids, and characterized using infrared (IR) spectroscopy to give a success rate of 55-70%. Reactions that gave a positive result were converted to solution experiments, and crystals were grown and characterized using single-crystal X-ray diffraction (XRD). The co-crystals display infinite 1-D chains with the intended stoichiometry and structural landscape on 6/6 occasions. The salts, on the other hand, display unpredictable stoichiometry and structural landscape on 5/5 occasions. Furthermore, the electrostatic charge on the primary hydrogen-bond acceptor, N(pyz), can be altered by adding a nitro, R-NO2, covalent handle to the backbone of the pyrazole molecule. Addition of a strongly electron withdrawing group significantly lowered the charge on the pyrazole nitrogen atom and, in turn, lowered the supramolecular yield to 10%. Ditopic molecules containing pyrazole and pyridine on the same molecular backbone were synthesized and characterized using 1H NMR. The molecules were co-crystallized with carboxylic acids, and the resulting solids were characterized using IR spectroscopy. The solids could then be classified as co-crystal or salt using specific markers in the IR spectrum. Single-crystal XRD was used to observe the intermolecular interactions in the co-crystals and salts, and the co-crystals were assigned to two groups: Group 1 (2) and Group 2 (2). The salts (4) show more unpredictability with stoichiometry and structural landscape. A library of ditopic molecules containing triazole and pyridine acceptor sites were synthesized and characterized using 1H and 13C NMR. The molecules were co-crystallized with carboxylic acids and the resulting solids were characterized using IR spectroscopy which demonstrated a 100% supramolecular yield whenever a pyridine moiety was present, consistent with results from Chapter 3. Single-crystal XRD was used to identify the intermolecular interactions in the co-crystals (2) and salt (1), and the results show that triazole can compete with pyridine for hydrogen bond donors. A library of ditopic molecules was also used for halogen-bonding (XB) studies with a series of activated iodine and bromine-based donors. The results show that iodine donors have a higher success rate range (12.5-75%) compared to bromine donors (16.7-50%) based on results obtained from IR spectra. Furthermore, the results from the XRD show that pyrazole nitrogen atoms can compete with pyridine for forming XB, and two groups of supramolecular synthons were observed. Finally, relatively weak non-covalent interactions, HB and XB, can influence the assembly of nanoparticles based on IR spectroscopy and TEM images. The assembly of the particles is influenced by specific capping ligands, which were synthesized and characterized using 1H, 13C and 19F NMR. The results demonstrate that relatively weak non-covalent interactions based on HB and XB interactions can influence nanoparticle assembly.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Materials Science and Engineering, 2007.
Includes bibliographical references (p. 137-147).
This thesis develops a machine learning framework for predicting crystal structure and applies it to binary metallic alloys. As computational materials science turns a promising eye towards design, routine encounters with chemistries and compositions lacking experimental information will demand a practical solution to structure prediction. We review the ingredients needed to solve this problem and focus on structure search. This thesis develops and argues for a search strategy utilizing a combination of machine learning and modern quantum mechanical methods. Structure correlations in a binary alloy database are extracted using probabilistic graphical models. Specific correlations are shown to reflect well-known structure stabilizing mechanisms. Two probabilistic models are investigated to represent correlation: an undirected graphical model known as a cumulant expansion, and a mixture model. The cumulant expansion is used to efficiently guide Density Functional Theory predictions of compounds in the Ag-Mg, Au-Zr, and Li-Pt alloy systems. Cross-validated predictions of compounds present in 1335 binary alloys are used to demonstrate predictive ability over a wide range of chemistries - providing both efficiency and confidence to the search problem. Inconsistencies present in the cumulant expansion are analyzed, and a formal correction is developed. Finally, a probabilistic mixture model is investigated as a means to represent correlation in a compact way. The mixture model leads to a significant reduction in model complexity while maintaining a level of prediction performance comparable to the cumulant expansion. Further analysis of the mixture model is performed in the context of classification. Unsupervised learning of alloy classes or groups is shown to reflect clear chemical trends.
by Christopher Carl Fischer.
Ph.D.

The purpose of this research is to develop a new tool for mechanical design and analysis of single crystal (SC) nickel base superalloys used in gas turbine engine components. The principle of this tool is based on the extension of the predictive models for isotropic material behavior to anisotropic materials such as SC nickel, base superalloys. This objective is achieved by combining the two main approaches used in the literature for SC materials development: the macroscopic approach and the microscopic approach. For that reason, this theory is designated as the "combined approach " (CA).
The structure of the CA theory requires two main elements: a viscoplastic model (that admits a yield function) and a slip factor. The viscoplastic model describes the behavior of the material in the macroscopic level. Conversely, the slip factor based on the crystallographic theory, accounts for the micro-slip state that dominates SC materials during deformation.
In order to determine the slip factor, a preliminary slip trace study of the crystal is established. Also to determine material constants from experimental data, a procedure has been developed to reduce the 3D basic equations into a one-dimensional form. The model has been evaluated for its predictive capability on SC material behavior including orientation dependence of the initial yielding, tension/compression asymmetry, stress-strain response, fully reversed cyclic response, creep response and relaxation response. In almost all the cases, good correlation has been observed between the predicted responses and experimental data, when available. Furthermore, it is believable that the CA can be successfully used for many other SC materials such as the body-centered-cubic (b.c.c) or the hexagonal-closed-packet (h.c.p). In view of all these results, the CA theory seems to offer the greatest promise in this regard. Limitations and future development needs are discussed.

Thesis (S.M. in Technology and Policy)--Massachusetts Institute of Technology, Engineering Systems Division, 2011.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 64-69).
Quantitative environmental performance evaluation methods are desired given the growing certification and labeling landscape for consumer goods. Challenges associated with existing methods, such as life cycle assessment (LCA), may be prohibitive for complex goods such as information technology (IT). Conventional LCA is resource-intensive and lacks harmonized guidance for incorporating uncertainty. Current methods to streamline LCA may amplify uncertainty, undermining robustness. Despite high uncertainty, effective and efficient streamlining approaches may be possible. A methodology is proposed to identify high-impact activities within the life cycle of a specific product class for a streamlined assessment with a high degree of inherent uncertainty. First, a screening assessment is performed using Monte Carlo simulations, applying existing activity (materials and processes), impact, and uncertainty data, to identify elements with the most leverage to reduce overall environmental impact uncertainty. This data triage is informed by sensitivity analysis parameters produced by the simulations. Targeted data collection is carried out for key activities until overall uncertainty is reduced to the point where a product classes' impact probability distribution is distinct from others within a specified error rate. In this thesis, we find that triage and prioritization are possible despite high uncertainty. The methodology was applied to the case study of liquid crystal display (LCD) classes, producing a clear hierarchy of data importance to reduce uncertainty of the overall impact result. Specific data collection was only required for a subset of processes and activities (22 out of about 50) to enable discrimination of LCDs with a low error rate (9%). Most of these priority activities relate to manufacturing and use phases. The number of priority activities targeted may be balanced with the level to which they are able to be specified. It was found that ostensible product attributes alone are insufficient to discriminate with low error, even at high levels of specificity. This quantitative streamlining method is ideal for complex products for which there is great uncertainty in data collection and modeling. This application of this method may inform early product design decisions and enable harmonization of standardization efforts.
by Melissa Lee Zgola.
S.M.in Technology and Policy

In this licentiate thesis the work done in the project KME410 will be presented. The overall objective of this project is to evaluate and develop tools for designing against fatigue in single-crystal nickel-base superalloys in gas turbines. Experiments have been done on single-crystal nickel-base superalloy specimens in order to investigate the mechanical behaviour of the material. The constitutive behaviour has been modelled and verified by simulations of the experiments. Furthermore, the  microstructural degradation during long-time ageing has been investigated with  respect to the component’s yield limit. The effect has been included in the  constitutive model by lowering the resulting yield limit. Finally, the fatigue crack  initiation of a component has been analysed and modelled by using a critical plane approach.

This thesis is divided into three parts. In the first part the theoretical framework, based upon continuum mechanics, crystal plasticity and the critical plane approach, is derived. This framework is then used in the second part, which consists of three included papers. Finally, in the third part, details are presented of the used  numerical procedures.

Control of a solid drug's physical form is an important stage of drug development, in order to best optimise the physicochemical properties of the drug. It is also important for intellectual property and regulatory considerations. Commonly, optimisation of a solid drug form moves beyond controlling the solid-state and actively manipulating it, via salt formation, co-crystal synthesis or inclusion complexation, for example. Presented in this work are three distinct approaches to the control and development of solid-state form of organic molecules and pharmaceuticals. The first of these approaches reports a novel, relatively simple technique for polymorph screening of compounds that are thermally stable, wherein homopolymer surface interactions direct the polymorph of a drug recrystallising from the supercooled melt. The study carried out demonstrates the ability to selectively crystallise the a polymorph of indomethacin using specific polymer substrates. The second theme details a crystal engineering strategy for a drug molecule to obtain a novel solid form. It is shown how knowledge of intermolecular hydrogen bonded supramolecular synthons can be exploited to rationally select potential co-crystal formers based on the likely growth unit formed. The structure of the co-crystal, solved using single-crystal X-ray diffraction, is reported and verifies the design strategy. The potential to enhance a drug's properties is demonstrated by an increased melting point compared to the native drug form, such that the liquid drug becomes a stable solid at room temperature. There is also an improved intrinsic dissolution rate as a direct result of the application of the methodology. In the last chapter, a systematic structural investigation of cyclodextrin inclusion complexes with an isomeric series of guest molecules has generated a large number of single-crystal structures and X-ray powder diffraction patterns. These provide structural understanding of these systems and highlight isostructural trends that can be used to make some general structural predictions. A heavy emphasis is placed on the method used to synthesise the crystalline inclusion complex and the structural role of cosolvents. A complementary solution-state investigation was also performed to detail the solution-state chemistry of these systems and enable the relationship between solution-state and solid-state complexation to be investigated.

Statistical approaches to chemistry, under the umbrella of cheminformatics, are now widespread - in particular as a part of quantitative activity structure relationship and quantitative property structure relationship studies on candidate pharmaceutical studies. Using such approaches on legacy data has widely been termed “taking a big data approach”, and finds ready application in cohort medicinal studies and psychological studies. Crystallography is a field ripe for these approaches, owing in no small part to its history as a field which, by necessity, adopted digital technologies relatively early on as a part of X-ray crystallographic techniques. A discussion of the historical background of crystallography, crystallographic engineering and of the pertinent areas of cheminformatics, which includes programming, databases, file formats, and statistics is given as background to the presented research. Presented here are a series of applications of Big Data techniques within the field of crystallography. Firstly, a naıve attempt at descriptor selection was attempted using a family of sulphonamide crystal structures and glycine crystal structures. This proved to be unsuccessful owing to the very large number of available descriptors and the very small number of true glycine polymorphs used in the experiment. Secondly, an attempt to combine machine learning model building with feature selection was made using co-crystal structures obtained from the Cambridge Structural Database, using partition modelling. This method established sensible sets of descriptors which would act as strong predictors for the formation of co-crystals, however, validation of the models by using them to make predictions demonstrated the poor predictive power of the models, and let to the uncovering of a number of weaknesses therein. Thirdly, a homologous series of fluorobenzeneanilides were used as a test bed for a novel, invariant topological descriptor. The descriptor itself is based from graph theoretical techniques, and is derived from the patterns of close-contacts within the crystal structure. Fluorobenzeneanilides present an interesting case in this context, because of the historical understanding that fluorine is rarely known to be a component in a hydrogen bonding system. Regardless, the descriptor correlates with the melting point of the fluorobenzeneanilides, with one exception. The reasons for this exception are explored. In addition, a comparison of categorisations of the crystal structure using more traditional “by-eye” techniques, and groupings of compounds by shared values of the invariant descriptor were undertaken. It is demonstrated that the novel descriptor does not simply act a proxy for the arrangement of the molecules in the crystal lattice- intuitively similar structures have different values for the descriptor while very different structures can have similar values. This is evidence that the general trend of exploring intermolecular contacts in isolation from other influences over lattice formation. The correlation of the descriptor with melting point in this context suggests that the properties of crystalline material are not only products of their lattice structure. Also presented as part of all of the case studies is an illustration of some weaknesses of the methodology, and a discussion of how these difficulties can be overcome, both by individual scientists and by necessary alterations to the collective approach to recording crystallographic experiments.

This work aimed to investigate and exploit the hydrogen bonds generated between heterocyclic aromatic compounds, namely benzimidazole and imidazole, and the carboxylic acid group. The flexible but robust hydrogen bonds generated have been used to create molecular complexes, using practical and relevant co-molecules. A systematic approach has been used in the selection of co-molecules on the basis of crystal engineering principles. A library of robust hydrogen bonds and primary structural motifs has been generated, which has been used to explain the solid-state assembly of the collection of molecular complexes produced in this work and in related published structures. The similarities in hydrogen bond strength, bonding motifs and proton transfer behaviour between very dissimilar molecular complexes have been remarkable. The opposite is also true in other examples, with very similar molecular complexes showing remarkable differences, but overall, a picture is built up of predictable use of crystal engineering principles in designing molecular complexes with anticipated structural and packing features. The phenomenon of polymorphism, widely known but poorly understood, is essential to many industrial processes. A primary aim of this work was to promote and control the formation of molecular complex polymorphs through varying crystallisation conditions. Co-crystallisations involving benzimidazole with the whole series of halo-benzoic acid molecules were scrutinised and polymorphism found to be prominent throughout. Selective growth for individual forms has been achieved, offering the potential for polymorph selection, but not fully understood. The behaviour of the protons was investigated in the molecular complexes generated; proton transfer was prevalent. This was achieved through three methods; firstly with the use of variable temperature X-ray and neutron diffraction experiments on the product, by altering the levels of pH during the crystallisation process and lastly by introducing competing acceptor sites through co-molecule selection. A feasibility study into the use of the relatively new solvent-free crystallisation processes was undertaken. It was shown to be a successful technique in screening for polymorphs and molecular complexes.

As a functionalized pentacene, 6,13-bis(triisopropylsilylethynyl) pentacene (TIPS pentacene) is a p-type organic semiconductor with remarkable intrinsic charge carrier transport and stability in ambient conditions. TIPS pentacene is soluble in most organic solvents, making it solution processable. TIPS pentacene, nonetheless, inherently forms acutely anisotropic crystals with large gaps in between the crystals, limiting charge transport and leading to vast variations in organic thin film transistor (OTFT) performance. Described in this dissertation are crystal growth techniques implemented to overcome these challenges. The presented temperature gradient technique, achieves highly aligned crystal arrays with excellent areal coverage which essentially results in an enhanced OTFT performance. The technique is firstly utilized to guide the TIPS pentacene crystal growth. An application of a temperature gradient to a TIPS pentacene solution controls the crystallization process to alleviate the intrinsic crystal misorientation and considerably improve film morphology. Employing this method resulted in TIPS pentacene films with uniform crystal orientations and extensive areal coverage. The favorable crystal morphology gave rise to a significant enhancement in OTFT average mobility compared to OTFTs without the temperature gradient. Employing the temperature gradient technique, however, simultaneously introduced thermal cracks in the films due to the occurrence of thermally induced stress during crystallization, which reduced the device performance of the TIPS pentacene OTFTs. To further improve the performance of TIPS pentacene based OTFTs, TIPS pentacene was blended with polymers to relieve the thermal stress and effectively prevent the generation of thermal cracks. Structural examination of, specifically, TIPS pentacene/Poly(?-methyl styrene) (P?MS) blend films at an optimal weight ratio, revealed a vertical phase segregation with elevated concentrations of TIPS pentacene molecules at the active layer/gate dielectric interface, facilitating charge transport. Thus, OTFTs based on TIPS pentacene/P?MS blends exhibited a dramatic increase in average hole mobility compared to those of pristine TIPS pentacene. In addition, an improved thin film uniformity directly enhanced the device performance consistency. Following the success of employing the temperature gradient technique concurrently with the insulating polymer, P?MS, studies were extended to build OTFTs on flexible substrates, indium tin oxide (ITO) coated polyethylene terephthalate (PET), to dramatically improve TIPS pentacene/P?MS system. Ultimately, TIPS pentacene/P?MS OTFTs on ITO/PET substrates demonstrated the highest achieved mobility from utilizing the temperature gradient system.

Il est communément admis aujourd'hui que le contact entre deux surfaces se compose en réalité d'une multitude de contact ponctuels entre des aspérités. Cette considération amène à une surface de contact réelle significativement différente de l'aire de contact parfaite supposée dans la théorie de Hertz.De même, elle implique également la présence d'un espace libre entre les deux surfaces en contact. Dans cette situation, l'objectif principal de ces travaux de thèse est de développer des approches numériques permettant l'analyse du contact mécanique entre surfaces rugueuses dans le but de qualifier/quantifier l'étanchéité de ce contact rugueux.Deux approches différentes sont étudiées. La première consiste à analyser le contact mécanique entre une surface rugueuse et un plan rigide au moyen de la méthode des éléments finis et d'un nouveau modèle numérique. La seconde concerne l'estimation de la transmissivité d'un contact rugueux en considérant des simulations de l'écoulement d'un fluide au sein du champ des ouvertures présent entre les deux surfaces en contact.La comparaison de ces estimations numériques avec les résultats expérimentaux révèlent des écarts importants. Dans le but de comprendre ces écarts, l'influence du modèle de comportement matériau dans de telles simulations est étudiée. La plasticité cristalline, mais également l'élévation de la température dégagée par déformation plastique seront considérés. La question de la représentativité de notre problème vis-à-vis de l'approche fluide sera également discutée.

abstract: Commercially pure (CP) and extra low interstitial (ELI) grade Ti-alloys present excellent corrosion resistance, lightweight, and formability making them attractive materials for expanded use in transportation and medical applications. However, the strength and toughness of CP titanium are affected by relatively small variations in their impurity/solute content (IC), e.g., O, Al, and V. This increase in strength is due to the fact that the solute either increases the critical stress required for the prismatic slip systems ({10-10}<1-210>) or activates another slip system ((0001)<11-20>, {10-11}<11-20>). In particular, solute additions such as O can effectively strengthen the alloy but with an attendant loss in ductility by changing the behavior from wavy (cross slip) to planar nature. In order to understand the underlying behavior of strengthening by solutes, it is important to understand the atomic scale mechanism. This dissertation aims to address this knowledge gap through a synergistic combination of density functional theory (DFT) and molecular dynamics. Further, due to the long-range strain fields of the dislocations and the periodicity of the DFT simulation cells, it is difficult to apply ab initio simulations to study the dislocation core structure. To alleviate this issue we developed a multiscale quantum mechanics/molecular mechanics approach (QM/MM) to study the dislocation core. We use the developed QM/MM method to study the pipe diffusion along a prismatic edge dislocation core. Complementary to the atomistic simulations, the Semi-discrete Variational Peierls-Nabarro model (SVPN) was also used to analyze the dislocation core structure and mobility. The chemical interaction between the solute/impurity and the dislocation core is captured by the so-called generalized stacking fault energy (GSFE) surface which was determined from DFT-VASP calculations. By taking the chemical interaction into consideration the SVPN model can predict the dislocation core structure and mobility in the presence and absence of the solute/impurity and thus reveal the effect of impurity/solute on the softening/hardening behavior in alpha-Ti. Finally, to study the interaction of the dislocation core with other planar defects such as grain boundaries (GB), we develop an automated method to theoretically generate GBs in HCP type materials.
Dissertation/Thesis
Doctoral Dissertation Mechanical Engineering 2014