Energetic polyatomic cluster beams are increasingly used in materials processing and surface analysis applications. In secondary ion mass spectrometry (SIMS) such beams have previously been utilised to investigate the chemical distribution of organic molecules (polymers, biological molecules and pharmaceuticals etc). One important application is in organic electronics, where the depth-distribution of organic components is important in the device performance. Massive gas cluster ion beams (GCIBs) have produced more successful depth-profiles for organic electronic devices that smaller projectiles including SF5+ and C60+. However, further work is needed to investigate and optimise experimental parameters to deliver the necessary SIMS performance. This study focused on molecular depth profiling of organic insulator (PMMA) and semiconductor (PTAA and TIPS-pentacene) materials, in single and bi-layered combinations, utilising cluster SIMS, using C60+ and Arn+, at different temperatures and energies. In general, at room temperature, the best depth resolution was obtained, using large Ar-GCIBs of low energy per atom (E/n ~10 eV), in comparison with the smaller Ar-GCIBs or with C60+ beams at the same total impact energy. On materials which sputtering under C60+ bombardment, ion and neutral yields were greatest due to the higher E/n, compared with GCIBs. Data from PMMA show that the sputter yield under C60 and Arn projectiles conform to the published 'universal' dependence of Y/n to E/n. Depth profiling of the semiconductor compounds were unsuccessful, using C60+ projectiles. For depth profiles using large GCIB projectiles, an increase in the secondary ion yield was observed at the interface with the silicon substrate - a phenomenon which was not observed for the smaller projectiles. In general, the most successful depth profiles (i.e. more constant molecular and fragment secondary ion yields, observed at pseudo-steady-state regions) and best depth resolutions were obtained at cryogenic temperatures - conditions under which corresponding sputtering yields and secondary ion yields were suppressed.

O uso de programas de computador para simular a formação de complexos entre proteínas é uma abordagem importante para melhor compreensão de como estas moléculas interagem. A representação paramétrica e a representação em polinômios tridimensionais de Zernike são ambas descrições compactas de superfícies moleculares baseadas em harmônicos esféricos utilizadas para visualização e comparação de superfícies moleculares e para atracamento de proteínas. Entretanto, apresentam limitações como restrição à topologia da superfície e dificuldade de representação de funções arbitrárias. Neste estudo, procurou-se refinar a capacidade de representação destes métodos para obtenção de elevada qualidade de reprodução e aplicabilidade a superfícies de topologia arbitrária. Através da análise de diversos algoritmos de suas etapas, foi possível identificar os estágios de cálculo de malha triangular de superfície molecular e de mapeamento esférico como os mais influentes na qualidade da representação paramétrica em harmônicos esféricos, e a alta sensibilidade a mudança de valores nas funções projetadas na qualidade da representação em Zernike 3D. A incorporação de um método de cálculo de superfícies que gera uma malha com elevada regularidade, aliado a um moderno algoritmo de mapeamento esférico garantiu baixo nível de distorções e obtenção de superfícies reconstruídas de alta qualidade. Uma técnica de detecção de similaridade entre superfícies de diferentes conformações de um ensemble permitiu compartilhamento de partes da descrição entre várias superfícies, com correspondente redução de volume de dados e de demanda por processamento, e com influência controlável nas distorções introduzidas. Um modo diferente de organização dos dados de entrada causou melhoria na qualidade de reconstrução de funções gerais em Zernike 3D, embora com a introdução de um mapa para restauração da função. Os resultados obtidos indicam aplicação promissora dos métodos em docking de proteínas com alto nível de detalhes. / Using computer programs to simulate protein complex formation is an important approach for better comprehension of the interaction mechanisms of such molecules. The parametric representation and the Zernike polynomial method are both compact representations of molecular surfaces based on spherical harmonics, used for visualization and comparison of molecules and for protein-protein docking. They pose, however, limitations regarding surface topology and difficulty in representing arbitrary functions. In this study, the representation capacity of such methods were refined to attain high quality reproductions and applicability to arbitrary topologies. Throughout the analysis of several algorithms, the stages of surface mesh calculation and spherical mapping were identified as highly influential on the quality of the spherical harmonics parametric representation, while high sensibility to changes in the function values were identified as an influential factor for projections in 3D Zernike. A surface calculation method that generates a highly regular mesh was adopted and paired with a modern spherical mapping algorithm to yield reconstructions with low level of distortions and high quality surfaces. Similarity among surfaces from different structures in a conformational ensemble were detected to allow sharing of portions of the description among several surfaces, with corresponding reduction in data volume and processing demand and controllable influence of distortions. A new input data organization method improved the reconstruction quality of general functions in 3D Zernike, although introducing a map to restore the function. Results indicate promising application of the methods in highly detailed protein-protein docking.

The dye-sensitized solar cell is a promising solar cell technology. In these systems the key process for light to electricity conversion is molecular in nature and is initiated in dye molecules adsorbed at a semiconducting surface. This thesis focuses on the electronic and molecular surface structure of the dye/TiO2 interface, and the experimental results were obtained from surface sensitive X-ray based electron spectroscopic methods. Two families of dyes, triarylamine based organic dyes and ruthenium based inorganic dyes, were investigated. The effect of dye structural modications on the interfacial properties was studied, such as the surface concentrations, dye molecular surface orientation, molecular interactions, and energy level matching. Also, the impact of additional parameters such as the incorporation of coadsorbents and the solvents used for dye sensitization were studied and complementary photoelectrochemical characterization was used to demonstrate functional properties corresponding to changes in the molecular layers. The experiments provided information on how specic structural modications change the frontier electronic structure. The results also showed that the adsorption of the organic dye leads to submolecular electronic changes, and that the dye surface orientations in general favor effcient energy conversion. Moreover, effects of solvents and coadsorbents, on both energy level matching between the dye and the TiO2 substrate and the surfacemolecular structure were quantied.

This thesis addresses the multi-body assembly (MBA) problem in the context of protein assemblies. [...] In this thesis, we chose the protein assembly domain because accurate and reliable computational modeling, simulation and prediction of such assemblies would clearly accelerate discoveries in understanding of the complexities of metabolic pathways, identifying the molecular basis for normal health and diseases, and in the designing of new drugs and other therapeutics. [...] [We developed] F²Dock (Fast Fourier Docking) which includes a multi-term function which includes both a statistical thermodynamic approximation of molecular free energy as well as several of knowledge-based terms. Parameters of the scoring model were learned based on a large set of positive/negative examples, and when tested on 176 protein complexes of various types, showed excellent accuracy in ranking correct configurations higher (F² Dock ranks the correcti solution as the top ranked one in 22/176 cases, which is better than other unsupervised prediction software on the same benchmark). Most of the protein-protein interaction scoring terms can be expressed as integrals over the occupied volume, boundary, or a set of discrete points (atom locations), of distance dependent decaying kernels. We developed a dynamic adaptive grid (DAG) data structure which computes smooth surface and volumetric representations of a protein complex in O(m log m) time, where m is the number of atoms assuming that the smallest feature size h is [theta](r[subscript max]) where r[subscript max] is the radius of the largest atom; updates in O(log m) time; and uses O(m)memory. We also developed the dynamic packing grids (DPG) data structure which supports quasi-constant time updates (O(log w)) and spherical neighborhood queries (O(log log w)), where w is the word-size in the RAM. DPG and DAG together results in O(k) time approximation of scoring terms where k << m is the size of the contact region between proteins. [...] [W]e consider the symmetric spherical shell assembly case, where multiple copies of identical proteins tile the surface of a sphere. Though this is a restricted subclass of MBA, it is an important one since it would accelerate development of drugs and antibodies to prevent viruses from forming capsids, which have such spherical symmetry in nature. We proved that it is possible to characterize the space of possible symmetric spherical layouts using a small number of representative local arrangements (called tiles), and their global configurations (tiling). We further show that the tilings, and the mapping of proteins to tilings on arbitrary sized shells is parameterized by 3 discrete parameters and 6 continuous degrees of freedom; and the 3 discrete DOF can be restricted to a constant number of cases if the size of the shell is known (in terms of the number of protein n). We also consider the case where a coarse model of the whole complex of proteins are available. We show that even when such coarse models do not show atomic positions, they can be sufficient to identify a general location for each protein and its neighbors, and thereby restricts the configurational space. We developed an iterative refinement search protocol that leverages such multi-resolution structural data to predict accurate high resolution model of protein complexes, and successfully applied the protocol to model gp120, a protein on the spike of HIV and currently the most feasible target for anti-HIV drug design. / text

<p>New effective experimental techniques in medicinal chemistry and pharmacology have resulted in a vast increase in the number of pharmacologically interesting compounds. However, the number of new drugs undergoing clinical trial has not augmented at the same pace, which in part has been attributed to poor absorption of the compounds.</p><p>The main objective of this thesis was to investigate whether computer-based models devised from calculated molecular descriptors can be used to predict aqueous drug solubility, an important property influencing the absorption process. For this purpose, both experimental and computational studies were performed. A new small-scale shake flask method for experimental solubility determination of crystalline compounds was devised. This method was used to experimentally determine solubility values used for the computational model development and to investigate the pH-dependent solubility of drugs. In the computer-based studies, rapidly calculated molecular descriptors were used to predict aqueous solubility and the melting point, a solid state characteristic of importance for the solubility. To predict the absorption process, drug permeability across the intestinal epithelium was also modeled.</p><p>The results show that high quality solubility data of crystalline compounds can be obtained by the small-scale shake flask method in a microtiter plate format. The experimentally determined pH-dependent solubility profiles deviated largely from the profiles predicted by a traditionally used relationship, highlighting the risk of data extrapolation. The <i>in silico</i> solubility models identified the non-polar surface area and partitioned total surface areas as potential new molecular descriptors for solubility. General solubility models of high accuracy were obtained when combining the surface area descriptors with descriptors for electron distribution, connectivity, flexibility and polarity. The used descriptors proved to be related to the solvation of the molecule rather than to solid state properties. The surface area descriptors were also valid for permeability predictions, and the use of the solubility and permeability models in concert resulted in an excellent theoretical absorption classification. To summarize, the experimental and computational models devised in this thesis are improved absorption screening tools applicable to the lead optimization in the drug discovery process. </p>

New effective experimental techniques in medicinal chemistry and pharmacology have resulted in a vast increase in the number of pharmacologically interesting compounds. However, the number of new drugs undergoing clinical trial has not augmented at the same pace, which in part has been attributed to poor absorption of the compounds. The main objective of this thesis was to investigate whether computer-based models devised from calculated molecular descriptors can be used to predict aqueous drug solubility, an important property influencing the absorption process. For this purpose, both experimental and computational studies were performed. A new small-scale shake flask method for experimental solubility determination of crystalline compounds was devised. This method was used to experimentally determine solubility values used for the computational model development and to investigate the pH-dependent solubility of drugs. In the computer-based studies, rapidly calculated molecular descriptors were used to predict aqueous solubility and the melting point, a solid state characteristic of importance for the solubility. To predict the absorption process, drug permeability across the intestinal epithelium was also modeled. The results show that high quality solubility data of crystalline compounds can be obtained by the small-scale shake flask method in a microtiter plate format. The experimentally determined pH-dependent solubility profiles deviated largely from the profiles predicted by a traditionally used relationship, highlighting the risk of data extrapolation. The in silico solubility models identified the non-polar surface area and partitioned total surface areas as potential new molecular descriptors for solubility. General solubility models of high accuracy were obtained when combining the surface area descriptors with descriptors for electron distribution, connectivity, flexibility and polarity. The used descriptors proved to be related to the solvation of the molecule rather than to solid state properties. The surface area descriptors were also valid for permeability predictions, and the use of the solubility and permeability models in concert resulted in an excellent theoretical absorption classification. To summarize, the experimental and computational models devised in this thesis are improved absorption screening tools applicable to the lead optimization in the drug discovery process.

In recent decades, scientific data has become available in increasing sizes and precision. Therefore techniques to analyze and summarize the ever increasing datasets are of vital importance. A common form of scientific data, resulting from simulations as well as observational sciences, is in the form of scalar-valued function on domains of interest. The Morse-Smale complex is a topological data-structure used to analyze and summarize the gradient behavior of such scalar functions. This thesis deals with efficient parallel algorithms to compute the Morse-Smale complex as well as its application to datasets arising from cosmological sciences as well as structural biology. The first part of the thesis discusses the contributions towards efficient computation of the Morse-Smale complex of scalar functions de ned on two and three dimensional datasets. In two dimensions, parallel computation is made possible via a paralleizable discrete gradient computation algorithm. This algorithm is extended to work e ciently in three dimensions also. We also describe e cient algorithms that synergistically leverage modern GPUs and multi-core CPUs to traverse the gradient field needed for determining the structure and geometry of the Morse-Smale complex. We conclude this part with theoretical contributions pertaining to Morse-Smale complex simplification. The second part of the thesis explores two applications of the Morse-Smale complex. The first is an application of the 3-dimensional hierarchical Morse-Smale complex to interactively explore the filamentary structure of the cosmic web. The second is an application of the Morse-Smale complex for analysis of shapes of molecular surfaces. Here, we employ the Morse-Smale complex to determine alignments between the surfaces of molecules having similar surface architecture.

Dans le cadre du développement durable, les procédés rapides, propres et peu énergivores sont très recherchés particulièrement en chimie pour les réactions d’oxydation. A part les solutions de génie des procédés, la catalyse est l’un des meilleurs atouts pour améliorer le processus. Le vanadium étant l’un des meilleurs métaux catalytiques pour de tels réactions, nous avions à nous attaquer son problème de relargage dans le milieu réactionnel en vue d’applications acceptables pour l’environnement. Nous proposons donc dans cette thèse des catalyseurs au vanadium fixé à l’intérieur des nano pores de silices mésoporeuses hexagonales de type MCM-41. La grande dispersion et la rétention du vanadium sont promues grâce à la présence d’ion d’ancrage : Al(III), Ti(IV), Zr(IV) and Ce(IV). Une grande variété de catalyseurs de type V-(Al/Ti/Zr/Ce)-MCM-41 ont été préparés à partir de trois méthodes de synthèse: l’une, ultra-rapide en une étape assistée par micro-onde, la seconde à étapes séquentielles multiples mettant en œuvre une technique de pochoir moléculaire et la troisième à nombre d’étapes réduites utilisant un traitement thermique partiel d’une surface préalablement organosilylée avant le greffage des métaux. Un large panel de techniques physicochimiques fut appliqué à la caractérisation de ces solides avec une attention particulière portée à l’analyse de la bande de transfert de charge ligand-métal du vanadium au degré d’oxydation +5 dont le décalage vers le bleu est corrélé à la taille des clusters d’oxyde de ces ions. La rétention du vanadium dans le méthanol a été corrélée à la dispersion du vanadium comme la dégradation à l’air du 1,2-diphényle-2-méthoxyéthanol. Ce substrat fut choisi comme modèle pour étudier la dégradation de la lignine par clivage C-C ou C-O. Notons que ce bio-polymère produit du phénoxypropanol methylé bio-sourcé utilisé dans les bio-carburants et comme précurseur en chimie fine. Dans le cas présent, un balayage à haut débit de la dégradation de cette molécule mettant en œuvre 96 mini-réacteurs en parallèle a permis de sélectionner le solvant, le métal d’ancrage et la teneure des deux métaux donnant la plus haute conversion. Contrairement aux catalyseurs homogènes, nos catalyseurs présentent une très haute sélectivité en clivage C-C. / The search for practical large-scale, fast, clean and energy saving chemical processes are highly regarded in the frame of a sustainable development, particularly for the most problematic oxidation reactions. Apart from chemical engineering solutions, improving the process using heterogeneous catalysis is one of the most adapted solution. Vanadium being considered the best metal for such kind of reactions, one had to tackle the problem of its high dispersion on a support to minimize its high propensity for leaching and to optimize its stability for practicable, safe and clean uses. In the present thesis, vanadium is supported inside the nanopores of a mesoporous silica of MCM-41 type where the high dispersion is assisted by the presence of anchoring ions such as Al(III), Ti(IV), Zr(IV) and Ce(IV) ions. A large set of V-(Al/Ti/Zr/Ce)-MCM-41 catalysts was prepared according to three different methods of preparation: i) ultra-fast one-pot synthesis protocol using the assistance of microwave, ii) post-synthesis modification using molecular stencil patterning (MSP) technique and iii) partial thermal treatment (PTT) of the organo-silylated support. The catalysts were characterized thoroughly using a panel of physical techniques and, particularly, the blue shift of the optical gap measured from the vanadium charge transfer band known to correlated with the dispersion of the metal. In complement, the stability was tested from metal leaching using methanol as a corrosive solvent while their catalytic reactivity was estimated in the aerobic oxidation of 1,2-diphenyl-2-methoxyethanol. This is a model reaction that simulates the oxidative C-C bond cleavage in lignin, the most difficult and crucial step in the degradation of this biopolymer, then producing in a clean way valuable methoxylated phenoxy propanol units useful for biomass fuels or bio-sourced precursors for fine chemistry. A high throughput screening approach was applied to test this aerobic oxidation reaction running over 96 reactors in parallel at the same temperature and sorting out the best catalysts with the most suitable anchoring ions and metal loading for the highest catalytic efficiency. / 在可持续发展的背景下，对于清洁高效节能可行的大规模化工过程尤其是存在诸多问题的氧化反应过程的探索倍受瞩目。除化学工程解决方案之外，通过多相催化来改进反应过程也是最可行的途径之一。钒被认为是最适合于催化此类反应的金属之一，其亟待解决的问题是实现钒在载体上的高度分散，并最大限度地降低其浸出倾向，改善其稳定性，从而实现对其安全清洁有效的利用。本文提出将钒负载于MCM-41型六方介孔二氧化硅的纳米孔道中，通过锚定离子如Al(III)、 Ti(IV)、Zr(IV)、Ce(IV)离子的存在促进钒的高度分散和固载。采用三种不同的方法制备了一系列V-(Al/Ti/Zr/Ce)-MCM-41催化剂：1、超快微波一步合成法，2、使用分子复刻版技术改性的后嫁接法，3、对有机硅烷化载体进行部分热处理改性的后嫁接法。通过一系列物理化学技术对合成的催化剂进行了充分表征，特别是对与金属分散度相关的钒的电荷跃迁带的测量和与其对应的光谱带隙蓝移进行了分析。随后，以甲醇作为腐蚀溶剂对合成的钒催化剂进行了金属析出的稳定性测试。通过一种木质素模型化合物1,2-diphenyl-2-methoxyethanol的需氧氧化反应测试了所合成负载型钒催化剂的催化活性。在相同温度及反应条件下，用96通道高通量微反应器技术评价了所制催化剂对该反应的催化性能，筛选出具有最高催化效率的负载型钒催化剂及其最适合的锚定离子。该反应中的碳-碳键裂解反应是木质素降解的最关键也是最困难的步骤之一，可通过这类生物聚合物的降解以清洁的方式生产有用的生物质燃料或生物来源高附加值精细化学品前驱体。