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abstract: The properties of materials depend heavily on the spatial distribution and connectivity of their constituent parts. This applies equally to materials such as diamond and glasses as it does to biomolecules that are the product of billions of years of evolution. In science, insight is often gained through simple models with characteristics that are the result of the few features that have purposely been retained. Common to all research within in this thesis is the use of network-based models to describe the properties of materials. This work begins with the description of a technique for decoupling boundary effects from intrinsic properties of nanomaterials that maps the atomic distribution of nanomaterials of diverse shape and size but common atomic geometry onto a universal curve. This is followed by an investigation of correlated density fluctuations in the large length scale limit in amorphous materials through the analysis of large continuous random network models. The difficulty of estimating this limit from finite models is overcome by the development of a technique that uses the variance in the number of atoms in finite subregions to perform the extrapolation to large length scales. The technique is applied to models of amorphous silicon and vitreous silica and compared with results from recent experiments. The latter part this work applies network-based models to biological systems. The first application models force-induced protein unfolding as crack propagation on a constraint network consisting of interactions such as hydrogen bonds that cross-link and stabilize a folded polypeptide chain. Unfolding pathways generated by the model are compared with molecular dynamics simulation and experiment for a diverse set of proteins, demonstrating that the model is able to capture not only native state behavior but also partially unfolded intermediates far from the native state. This study concludes with the extension of the latter model in the development of an efficient algorithm for predicting protein structure through the flexible fitting of atomic models to low-resolution cryo-electron microscopy data. By optimizing the fit to synthetic data through directed sampling and context-dependent constraint removal, predictions are made with accuracies within the expected variability of the native state. / Dissertation/Thesis / Ph.D. Physics 2011

This Thesis investigates computationally the behaviour of two novel microporous materials,organic molecules of intrinsic microporosity (OMIMs) and polymers of intrinsic microporosity(PIMs). OMIMs and PIMs are organic amorphous materials, which achieve microporosityby packing inefficiently. The design of amorphous materials is challenging because their self-assembly process is not known. Predictive molecular simulations can help in recognising thefeatures that affect the properties of these materials, and guiding in the design of new structures with desired performances. OMIMs are highly concave shaped molecules, consisting of a core and a series of termini, which provide the geometry and the general chemical environment of these structures, respectively. PIMs are polymers consisting of fundamental units such as stiff segments and contortionsites, which form either linear or network like porous structures. While chronologically olderthan OMIMs, they share with them a common design philosophy. This Thesis is presented in alternative format, and the results, consisting of five journal articles,can be divided into three main parts. The first part focuses on recognising a reliable method to generate representative models ofOMIMs. Different computational protocols and molecular mechanics descriptions were investigated; the development of the utilised simulation protocol was based on comparison of several simulation methods and force fields to experimental wide angle X-ray scattering (WAXS) patterns. Our work suggests that OMIMs can be described successfully by both PCFF and UFF; the final packed material can be generated using a 21-step compression-decompression molecular dynamics protocol, previously developed to generate virtual model of PIMs. The examination of the simulated structures has provided a deeper understanding of the features that affect the packing behaviour of this class of materials, suggesting that OMIMs have a greater microporosity when the molecules are the most shape-persistent, which required rigid structures and bulky end groups. The adsorption behaviour described by different generic force fields (Dreiding, OPLS and UFF) was also investigated to guide on the selection of the solid-fluid interactions when modelling OMIMs, for future comparison with experimental data. Our results suggest that very strong interactions between argon adsorbate and OMIM-based framework are described by UFF, while the weakest adsorbent is obtained using OPLS force field. The second part of the research focuses on assessing the effect that different termini’s chemistry and bulkiness have over the packing behaviour, adsorption properties and solubility of the OMIMs. The microporous frameworks generated by two selected families of cruciform OMIMs (benzene and naphthalene- based) were investigated with respect to their packing behaviour, porosity and adsorption properties. Our analysis suggests that the final density of the material, as well as the surface area and pore volume, depend on the ending group’s bulkiness. Bulkier molecules lead to materials with lower densities, but it was found that the adsorption behaviour is not just related to the material’s density, but also to the pore size and shape, which are determined by the way the molecules pack. The relationship between adsorption capacity and physical properties was analysed and the role of surface area, free volume and enthalpic interaction was used to identify different adsorption regimes. It was found that the uptake of argon at low pressure is proportional to the strength of the adsorbent-adsorbate interaction while at moderate pressure it is dependent on the free volume and surface area. The dissolution of three cruciform OMIMs was investigated in dichloromethane, ethyl acetateand toluene. Direct interface molecular dynamics simulations showed that the solubility process consists of two steps; the diffusion of the solvent in the OMIM-rich phase, and the departure of the OMIMs in the solvent bulk. We proposed a simple model to represent this mechanism. Furthermore, results from infinite dilution simulations show that the solvent-OMIMs interactions can be related to the chemistry of the OMIMs and to the solvent’s properties. We found that, in general, increasing the length of the OMIM’s arm affects negatively the solubility of the material, while adding bulky alkyl groups favours the interaction with the solvent molecules. The third part concentrates on the characterisation of PIMs and their application as CO2 adsorbent. Properties of four polymers of intrinsic microporosity containing Tröger’s base units were assessed for CO2 capture experimentally and computationally. Structural properties included average pore size, pore size distribution, surface area, and accessible pore volume, whereas thermodynamic properties focused on density, CO2 sorption isotherms, and enthalpies of adsorption. It was found that the shape of the contortion site plays a more important role than the polymer density when assessing the capacity of the material, and that the presence of a Tröger base unit only slightly affects the amount adsorbed at low pressures, but it does not have any significant influence on the enthalpy of adsorption fingerprint. A comparison of the materials studied with those reported in the literature allowed us to propose a set of guidelines for the design of polymers for CO2 capture applications.

No description available.

No description available.

Em um exame mamográfico, quando os fótons de raios-X incidem sobre a mama, uma parte destes fótons é transmitida sem ser desviada da trajetória inicial (radiação transmitida primária), permitindo a formação da imagem mamográfica, e outra é dispersa de sua trajetória inicial pelo tecido (radiação espalhada), atuando de forma deletéria na imagem mamográfica. Entretanto, recentes investigações têm demonstrado que a radiação espalhada pode ser útil na caracterização de tecidos. O objetivo deste trabalho é desenvolver um modelo de diagnóstico de alterações no tecido mamário utilizando as informações presentes na distribuição angular da radiação espalhada (perfil de espalhamento). Os perfis de espalhamento de 40 amostras de tecidos mamários foram obtidos utilizando um difractômetro comercial SIEMENS D5005, operando em modo reflexão na energia de 8,04 keV e variando o detector da posição angular de 5º a 150º, correspondendo a um intervalo de x de 0,03Å-1 a 0,62 Å-1. As amostras de tecido foram previamente classificadas histopatologicamente como tecidos normais, fibroadenomas (neoplasias benignas) e diferentes tipos de carcinomas (neoplasias malignas). Neste trabalho, três modelos de diagnóstico baseados na análise estatística dos perfis de espalhamento foram desenvolvidos. O primeiro, analisa seis parâmetros extraídos dos perfis de espalhamento, já o segundo e o terceiro utilizam análise multivariada (análise de componentes principais e análise de discriminante, respectivamente) para reconhecimento de padrões. Para cada modelo, valores de sensibilidade, especificidade e índice de concordância entre o diagnóstico baseado no modelo utilizado e o diagnóstico histopatológico foram obtidos. Dentre os modelos desenvolvidos, aquele que utiliza análise de discriminante proporciona o melhor diagnóstico das alterações encontradas no tecido, permitindo diferenciar tecidos normais e neoplasias benignas e malignas. Com base nos resultados obtidos conclui-se que modelos baseados na análise estatística dos perfis de espalhamento permitem classificar histologicamente tecidos mamários. / In mammography, when x-ray photons reach the breast, a fraction of these photons is transmitted without interaction with any tissues (primary transmitted radiation), allowing the formation of the mammographic image, and another fraction of them is deviated by the tissue from its initial trajectories (scattered radiation), reducing the image contrast. However, recent investigations have demonstrated that scattered radiation can be a useful diagnostic tool. The purpose of this work is to develop a diagnostic model for breast tissue characterization using the angular distribution of the scattered radiation (scattering profile). The scattering profiles of 40 breast tissue samples were obtained in a SIEMENS D5005 diffractometer, operating in reflection mode at 8,04keV, and varying the angular position of the detector from 5º to 150º, corresponding to an x interval from 0,03 Å-1 to 0,62 Å-1. All tissue samples were previously classified histopathologically as normal tissues, fibroadenomas (benign alteration) and several types of carcinomas (malignant alteration). Three models of diagnostic based on the statistical analysis of the scattering profiles were developed. The first one was constructed using six parameters extracted from the scattering profiles and the second and third models used the whole information from the scattering profiles. The latter two used multivariate analysis (principal component analysis and discriminant analysis, respectively) for pattern recognition. For each model, values of sensitivity, specificity and rate of agreement between the model diagnostic and histopathological results were obtained. Among the developed models, the discriminant analysis provides the best diagnostic of the lesions present in the tissues (normal tissues, benign and malignant alterations). From the results, it is possible to conclude that models based on the statistical analysis of the scattering profiles allow the histological classification of breast tissues.

Em um exame mamográfico, quando os fótons de raios-X incidem sobre a mama, uma parte destes fótons é transmitida sem ser desviada da trajetória inicial (radiação transmitida primária), permitindo a formação da imagem mamográfica, e outra é dispersa de sua trajetória inicial pelo tecido (radiação espalhada), atuando de forma deletéria na imagem mamográfica. Entretanto, recentes investigações têm demonstrado que a radiação espalhada pode ser útil na caracterização de tecidos. O objetivo deste trabalho é desenvolver um modelo de diagnóstico de alterações no tecido mamário utilizando as informações presentes na distribuição angular da radiação espalhada (perfil de espalhamento). Os perfis de espalhamento de 40 amostras de tecidos mamários foram obtidos utilizando um difractômetro comercial SIEMENS D5005, operando em modo reflexão na energia de 8,04 keV e variando o detector da posição angular de 5º a 150º, correspondendo a um intervalo de x de 0,03Å-1 a 0,62 Å-1. As amostras de tecido foram previamente classificadas histopatologicamente como tecidos normais, fibroadenomas (neoplasias benignas) e diferentes tipos de carcinomas (neoplasias malignas). Neste trabalho, três modelos de diagnóstico baseados na análise estatística dos perfis de espalhamento foram desenvolvidos. O primeiro, analisa seis parâmetros extraídos dos perfis de espalhamento, já o segundo e o terceiro utilizam análise multivariada (análise de componentes principais e análise de discriminante, respectivamente) para reconhecimento de padrões. Para cada modelo, valores de sensibilidade, especificidade e índice de concordância entre o diagnóstico baseado no modelo utilizado e o diagnóstico histopatológico foram obtidos. Dentre os modelos desenvolvidos, aquele que utiliza análise de discriminante proporciona o melhor diagnóstico das alterações encontradas no tecido, permitindo diferenciar tecidos normais e neoplasias benignas e malignas. Com base nos resultados obtidos conclui-se que modelos baseados na análise estatística dos perfis de espalhamento permitem classificar histologicamente tecidos mamários. / In mammography, when x-ray photons reach the breast, a fraction of these photons is transmitted without interaction with any tissues (primary transmitted radiation), allowing the formation of the mammographic image, and another fraction of them is deviated by the tissue from its initial trajectories (scattered radiation), reducing the image contrast. However, recent investigations have demonstrated that scattered radiation can be a useful diagnostic tool. The purpose of this work is to develop a diagnostic model for breast tissue characterization using the angular distribution of the scattered radiation (scattering profile). The scattering profiles of 40 breast tissue samples were obtained in a SIEMENS D5005 diffractometer, operating in reflection mode at 8,04keV, and varying the angular position of the detector from 5º to 150º, corresponding to an x interval from 0,03 Å-1 to 0,62 Å-1. All tissue samples were previously classified histopathologically as normal tissues, fibroadenomas (benign alteration) and several types of carcinomas (malignant alteration). Three models of diagnostic based on the statistical analysis of the scattering profiles were developed. The first one was constructed using six parameters extracted from the scattering profiles and the second and third models used the whole information from the scattering profiles. The latter two used multivariate analysis (principal component analysis and discriminant analysis, respectively) for pattern recognition. For each model, values of sensitivity, specificity and rate of agreement between the model diagnostic and histopathological results were obtained. Among the developed models, the discriminant analysis provides the best diagnostic of the lesions present in the tissues (normal tissues, benign and malignant alterations). From the results, it is possible to conclude that models based on the statistical analysis of the scattering profiles allow the histological classification of breast tissues.

Many physical properties, for example structural or magnetic, of a material are directly dependent on elemental composition. Tailoring of properties through highly accurate composition control is possible in thin films. This work exemplifies such tailoring. A short review is given of the current status for research in the area of permanent magnets, focusing on rare earth element free alternatives, where FeNi in the L10 phase is a possible candidate. Epitaxial FeNi L10 thin films were successfully synthesized by magnetron sputtering deposition of monoatomic layers of Fe and Ni on HF-etched Si(001) substrates with Cu or Cu100-xNix/Cu buffers. The in-plane lattice parameter aCuNi of the Cu100-xNix buffer layer was tuned by the Ni content. Through matching of aFeNi to aCuNi, the strain state (c/a)FeNi was controlled, where c is the out-of-plane lattice parameter. The 001 reflection indicative of chemical order, as measured by resonant x-ray diffraction, was in most cases split in two peaks due to a composition modulation of Fe and Ni. This chemical disorder contributed to that the uniaxial magnetocrystalline anisotropy energy, KU≈0.35 MJ/m3, was smaller than predicted. In later experiments the composition modulation could partly be compensated for. Remaining discrepancies with respect to predicted KU values were attributed to additional disorder induced by surface roughness of the buffer layer. The interface sharpness between Fe and Ni was explored by producing epitaxial symmetric multilayers with individual layer thicknesses n = 4-48 monolayers (ML). For n ≤ 8 ML the films had pure fcc structure, with antiferromagnetic Fe layers. For n ≥ 8 ML the Fe layers relaxed to bcc structure. A combinatorial sputter chamber, which has the capability to deposit samples with composition and thickness gradients, was assembled. A model for simulation of composition and thickness across large substrates, for the conditions in this chamber, is presented. The model is verified by comparison to experimental data. Some challenges inherent in combinatorial sputtering are discussed, and two experimental studies employing the technique are presented as examples. These investigated magnetic and structural properties of Tb-Co films, with 7-95 at.% Tb, and of amorphous and crystalline ternary gradient Co-Fe-Zr films, respectively.