"Cellulose nanocrystals, one of the most abundant materials in nature, have attracted great attention in the biomedical community due to qualities such as supreme mechanical properties, biodegradability, biocompatibility and low density. In this research, we are interested in developing a bio-inspired material-by-design approach for cellulose-based composites with tailored interfaces and programmed microstructures that could provide an outstanding strength-to-weight ratio. After a preliminary study on some of the existing biomaterials, we have focused our research on studying the nanostructure and nanomechanics of the bamboo fiber, a cellulose-based biocomposite, designed by nature with remarkable strength-to-weight ratio (higher than steel and concrete). We have utilized atomistic simulations to investigate the mechanical properties and mechanisms of interactions between cellulose nanofibrils and the bamboo fiber matrix which is an intertwined hemicellulose and lignin called lignin-carbohydrate complex (LCC). Our results suggest that the molecular origin of the rigidity of bamboo fibers comes from the carbon-carbon or carbon-oxygen covalent bonds in the main chain of cellulose. In the matrix of bamboo fiber, hemicellulose exhibits larger elastic modulus and glass transition temperature than lignin whereas lignin shows greater tendency to adhere to cellulose nanofibrils. Consequently, the role of hemicellulose is found to enhance the thermodynamic properties and transverse rigidity of the matrix by forming dense hydrogen bond networks, and lignin is found to provide the strength of bamboo fibers by creating strong van der Waals forces between nanofibrils and the matrix. Our results show that the amorphous region of cellulose nanofibrils is the weakest interface in bamboo microfibrils. We also found out that water molecules enhance the mechanical properties of lignin (up to 10%) by filling voids in the system and creating hydrogen bond bridges between polymer chains. For hemicellulose, however, the effect is always regressive due to the destructive effect of water molecules on the hydrogen bond in hemicellulose dense structure. Therefore, the porous structure of lignin supports the matrix to have higher rigidity in the presence of water molecules. "

"Recently, there has been some good interest in the field of Dynamic Materials, also referred to as Spatio-Temporal Composites. These materials have been theoretically attributed to show ability to switch their electromagnetic properties in time, as contrast to the spatial variations shown by regular materials of non-dynamic nature, existing naturally. Though there is no exhibition of dynamic material in nature yet, there are suggestions for its synthesis. This paper follows the idea of using standard lossless transmission line model approximating a material substance. Such a material though not truly homogeneous, could be made to vary its properties in time. The aim of this work is to test this idea for its functional efficiency in comparison to analytical results obtained from earlier works on the subject. We make use of Spice simulation for this. An important aspect of this work is to facilitate the dynamic operations in a static environment. Almost all the simulators available today like Spice, ADS, etc intrinsically provide no ability for parameter variations in time. Nonetheless, we make use of certain popular tricks to implement circuits imitating the dynamic circuit components we need. Such implementations are separately tested to demonstrate their success in providing us with the dynamic environment we desire. Finally, within the limitations of the computing capabilities, we could successfully show an agreement between the results obtained and the existing theory. "

A Multivalent entity, which could represent a protein, nanoparticle, polymer, virus or a lipid bilayer, has the ability to form multiple bonds to a substrate. Hence, a multivalent interaction can be strong, even if the individual bonds are weak. However, much more interestingly, multivalency enables the design of highly specific interactions using non-specific individual bonds. We attempt to rationalise multivalent effects using simple physical models complemented with numerical simulations. Based on physiochemical characteristics of multivalent binders, we aim to predict the overall strength of interaction and its sensitivity to variation in parameters. We start with a simple model of homo-multivalency, where all bonds are equivalent. Such systems can exhibit a super-selective response, which denotes the high sensitivity of the strength of multivalent binding to the number of accessible binding sites on the target surface. We present a theoretical analysis of systems of multivalent particles and show that a certain degree of disorder is necessary for super-selective behaviour. Moreover, we formulate a set of simple design rules for multivalent interactions that yield optimal selectivity. In the second stage, we expand the model to hetero-multivalency, accounting for multiple distinct types of binding partners. We consider targeting of cells based on a density profile of different membrane receptors types and demonstrate, that speci city towards a desired receptor density profile can be obtained. Hence, cells can be reliably targeted in the absence of specific markers. Crucially, we show that for optimal selectivity, individual bonds must be weak. Finally, we add information about specific geometry and positions of binding sites on the multivalent entity. We focus on molecular imprinting; the process whereby a polymer matrix is cross-linked in the presence of template molecules. The cross-linking process endows the polymer matrix with a chemical ‘memory’, such that the target molecules can subsequently be recognised by the matrix. We show how the binding multivalency and the polymer material properties affect the efficiency and selectivity of molecular imprinting.

<p>Protein conformational transitions are fundamental to the functions of many proteins, and computational methods are valuable for elucidating the transitions that are not readily accessible by experimental techniques. Here we developed accelerated sampling methods to calculate optimized all-atom protein conformational transition paths. Adaptively biased path optimization (ABPO) is a computational simulation method to optimize the conformational transition path between two states. We first examined the transition paths of three systems with relatively simple transitions. The ways to define reduced variables were explored and transition paths were built at convergence of the optimizations. We constructed the all-atom conformational transition path between the active and the inactive states of the Src kinase domain. The C helix rotation was identified as the main free energy barrier in the all‑atom system, and the intermediate conformations and key interactions along the transition path were analyzed. This is the first demonstration of the robustness of a computational method for calculating protein conformational transitions without restraints to a specified path. We also evaluated protein‑peptide interactions using both molecular dynamics simulations and peptide docking. Long unbiased simulations were used to evaluate Src‑SSP interactions and complex stability in both implicit and explicit solvent. Molecular docking was used to build possible protein‑peptide interaction models, using both Src regulatory domain SH2 and the kinase domain. Possible Src‑SSP complexes were built as the first Src‑substrate complex structure models.</p>

Galaxy clusters are the most massive collapsed structures in the Universe and their properties offer a crucial insight into the formation of structure. High quality observational data is forthcoming with ongoing and upcoming surveys, but simulations are needed to provide robust theoretical predictions for comparison, as well mock data for testing observational techniques. Numerical simulations are now able to accurately model a range of astrophysical processes. This is highlighted in the BAHAMAS and MACSIS simulations, which have successfully reproduced the observed scaling relations of galaxy clusters. We use these simulations to quantify the impact baryons have on the mass distribution within galaxy clusters, as well as the bias in X-ray and weak lensing mass estimates. It is shown that baryons have only a minor affect on the spins, shape and density profiles of galaxy clusters and they have no significant impact on the bias in weak lensing mass estimates. When using spectroscopic temperatures and densities, the X-ray hydrostatic mass bias decreases as a function of mass, leading to a bias of ~40% for clusters with M_500 > 10^15 solar masses. In the penultimate chapter, we use the EAGLE and C-EAGLE simulations to construct more realistic mock cluster observations. The EAGLE simulations have been shown to successfully reproduce the properties of field galaxies and they are complemented by the C-EAGLE project, which extends this work to the cluster scale. We use these simulations to construct a cluster lightcone that accounts for the impact of uncorrelated large scale structure on cluster observables, including weak lensing mass estimates, the Sunyaev-Zel'dovich parameter and X-ray luminosity.

Thermal performance of an insulation material is influenced by the in-service temperature condition. Unlike most other insulation materials, thermal resistance (R-value) of polyisocyanurate (polyiso) foam insulation with ‘captive blowing agent’ varies non-linearly with temperature. Building designers consider constant R-value of different insulating materials for building design and energy calculations, and hygrothermal simulation software packages, such as WUFI, consider linear temperature dependent R-value profiles, even for polyiso. However, neither the linear temperature dependent thermal resistance nor the constant thermal resistance value of polyiso represents the actual thermal performance of the building envelope. This thesis aims to quantify the impact of in-service boundary temperature conditions in Canadian climates on the thermal resistance of polyiso foam insulation board used in EPDM and PVC roof constructions. Hygrothermal simulations were performed using WUFI® Pro, which considers real climate data and hygrothermal properties of constituent roof components for evaluating moisture and temperature conditions in roof constructions. Based on heating degree days (HDD), ten different cities were selected between climate Zone 4 (HDD<3000) to Zone 8 (HDD≥7000). The thermal resistance measurements were conducted using heat flow meter apparatus on four polyiso insulation boards (two new and two aged) of different sizes [thickness - new: 1inch (25mm) and 2 inch (51mm); aged: 2 inch (51mm) and 3 inch (76mm)] at five mean temperatures -4°C (25°F), 4.5°C (40°F), 10°C (50°F), 24°C (75°F), 43°C (110°F) and at a temperature differential of 28°C (50°F). The measured thermal resistance data of the four samples at different mean temperatures were normalized with calculated thermal resistance of each sample at 22°C (72°F). The normalized R-value variation was calculated using in-service boundary temperature conditions determined from hygrothermal simulations and considering linearly varied thermal resistance with temperature, for the selected ten Canadian cities. / Graduate

No presente trabalho estudamos a difusão de compostos dispersos atmosfericamente como, por exemplo, fertilizantes e pesticidas particulares, em ambientes agrícolas de larga escala. Tal estudo foca-se na aplicabilidade de modelos numéricos e teórico-fenomenológicos de fenômenos turbulentos em estimativas de vantagens econômica e ambiental desses sistemas. A atmosfera terrestre, em escalas de tamanho e velocidade típicas do objeto de estudo deste trabalho, é um sistema turbulento. A turbulência é um fenômeno complexo, que envolve a interação dinâmica de distintas escalas resultando em um efeito coletivo de larga escala, decorrente de uma interação não linear entre modos perturbativos em um fluido. A modelagem da turbulência, portanto, é em geral possível através de Simulação Numérica Direta - DNS (Direct Numeric Simulation). Uma das consequências típicas da turbulência é a difusão, ou seja, o aumento em sistemas abertos da separação entre corpos particulados, em taxas muito superiores àquelas da difusão molecular térmica padrão. Neste trabalho, apresentamos um estudo focado na quantificação da difusão turbulenta de partículas através de simulações numéricas de turbulência, com o objetivo de identificar impactos de fertilização e dispersão de poluentes atmosféricos com implicações na saúde e ambiente / In the present study, we study the diffusion dispersed atmospherically compounds, such as fertilizers and particular pesticides in large scale agricultural environments. This study focuses on the applicability of numerical and theoretical and phenomenological models of turbulent phenomena in estimates of economic and environmental advantages of these systems. The Earth\'s atmosphere, in typical size and speed ranges of the study object of this work is a turbulent system. Turbulence is a complex phenomenon which involves the dynamic interaction of different ranges resulting in a large-scale collective effect due to a nonlinear interaction between perturbation modes in a fluid. The modeling of turbulence, so it is generally possible through Direct Numerical Simulation - DNS. A typical consequence of turbulence is the diffusion, i.e., increased separation in unbound systems of particulate bodies, much higher than those of the standard thermal molecular diffusion rates. In this work we present a study focused on quantifying the turbulent diffusion of particles through numerical simulations of turbulent media, in order to identify the impact of fertilization and dispersion of air pollutants on human health and environment

This thesis investigates how breaking apart selection interference (‘Hill-Robertson’ effects) that arises between linked loci can select for higher levels of recombination. Specifically, it mainly studies how the presence of both advantageous and deleterious mutation affects selection for recombination. These evolutionary advantages are subsequently investigated with regards to sex resisting asexual invasion in a subdivided population. i) KEIGHTLEY and OTTO (2006) showed a strong advantage to recombination in breaking apart selection interference, if it acts across multiple, linked loci subject to recurrent deleterious mutation. Their model is modified to consider selection acting on recombination if a small proportion of mutations are advantageous. This leads to a greater increase in selection acting on a recombination modifier, compared to cases where only deleterious mutations are present. ii) Branching-process methods are developed to quantify how likely it is that a deleterious mutant hitchhikes with a selective sweep, and how recombination between the two loci affects this process. This is compared to the neutral hitchhiking model, to determine how levels of linked neutral diversity would differ between the two scenarios. A simple application with regards to human genetic data is provided. iii) Population subdivision can maintain costly sex, as a consequence of restricted gene flow slowing the spread of invading asexuals, which leads to an excessive accumulation of deleterious alleles. However, previous work did not quantify whether costly sex can be maintained with realistic levels of population subdivision. Simulations in this thesis show that the level of population subdivision (as measured by Fst) needed to maintain costly sex decreases with larger population size; however critical Fst values found are generally high, compared to surveys of geographicallyclose populations. The lowest levels of population subdivision that maintained sex were found if mutation is both advantageous and deleterious, and demes were arranged in a one-dimensional stepping-stone formation. iv) An analytical method is developed to calculate how long it takes an advantageous mutation (such as an invading asexual) to spread through a subdivided population. The flexibility of the methods created means that they can be applied to different types of stepping-stone populations. It is shown how to formulate the fixation time for one-dimensional and two-dimensional structures, with analytical methods showing a good fit to simulation data.

DNA scaffolds self-assembled by short-stranded synthetic DNA can be tailored to build thermally reversible hydrogels with target binding sites. These hydrogels exhibit highly selective binding properties due to the specificity of DNA and also provide an aqueous environment for various reactions to happen within the network constraints. Hence, a careful study on the assembly mechanism and other physical aspects of DNA hydrogels is required to facilitate the future design and construction of such materials at the precise control. In this thesis, I present the work on well-designed DNA nano-stars as scaffolds for functional bulk materials with potential applications in bio-sensing. Chapter 1 starts with introducing the fundamental properties of DNA molecules, focusing on the advantages of utilising short-stranded DNA to programme and engineer micro- and macro- materials. Then it briefly reviews the field of rheology and micro-rheology, with the diffusing wave spectroscopy (DWS) technique illustrated explicitly as an example passive micro-rheology tool. Afterwards, a critical literature review on computational modelling of DNA systems is present, followed by the thesis outline at the end. Chapter 2 describes a simple DNA dendrimer system self-assembled from three-armed DNA nano-stars. The characterisation tools such as UV-vis spectroscopy, gel electrophoresis and dynamic light scattering (DLS) are introduced to verify the final production of the complex DNA structures. From this practice, we develop a routine for designing DNA scaffolds that yield optimal productivity. Chapter 3 investigates the mechanical properties of DNA hydrogels made of three-armed DNA nano-stars and how they change upon cooling and heating empolying DWS micro-rheology. The resulting viscoelastic moduli over a broad range of frequencies reveal a clear, temperature-reversible percolation transition coinciding with the melting temperature of the system's sticky ends. This indicates that we can achieve precise control in mechanical properties of DNA hydrogels, which is beneficial for designing more sensitive molecular sensing tools and controlled release systems. Chapter 4 develops a coarse-graining computational model of DNA hydrogels that resembles the system in Chapter 3 using LAMMPS, a classical molecular dynamics code. Thermodynamics, structural analysis and rheology tests were taken, qualitatively reproducing the physical phenomena of DNA assembly of the hydrogel network. Chapter 5 studies the internal behaviours of three-armed DNA complexes using oxDNA model also implemented in LAMMPS, with particular focus on the effect of the inert bases in the core and between double-stranded branches and single-stranded sticky ends. A deep insight into sequence-dependent behaviour of such complex structures can guide the parameter optimisation of the individual building blocks for the model described in Chapter 4. Chapter 6 concludes the thesis and presents an outlook for the future work that emerged out of my experimental and numerical studies.

It is well known that nucleotide diversity varies across the genomes of eukaryotic species in ways consistent with the effects of natural selection. However, the contribution of selection on advantageous and deleterious mutations to the observed variation is not well understood. In this thesis, I aim to disentangle the contribution of background selection and selective sweeps to patterns of genetic diversity in the mouse genome, thus furthering our understanding of natural selection in mammals. In chapter 1, I introduce core concepts in evolutionary genetics and describe how recombination and selection interact to shape patterns of genetic diversity. I will then describe three projects in which I examine aspects of molecular evolution in house mice. In the first of these, I estimate the landscape of recombination rate variation in wild mice using population genomic data. In the second, I estimate the distribution of fitness effects for new mutations, based on the site frequency spectrum, then analyse population genomic simulations parametrized using my estimates. In the third, I use a model of selective sweeps to estimate and compare the strength of selection in protein-coding and regulatory regions of the mouse genome. This thesis demonstrates that selective sweeps are responsible for a large amount of the variation in genetic diversity across the mouse genome.