Designing materials for fusion applications is a very challenging problem, requiring detailed understanding of the behaviour of materials under the kinds of extreme conditions expected in a fusion environment. During the lifetime of fusion-reactor components, materials will be subjected to high levels of neutron irradiation, but must still perform effectively at high operating temperatures and under significant loading conditions. Body-centred cubic (bcc) transition metals are some of the most promising candidates for structural materials in fusion because of their relatively high density, which allows for effective neutron-shielding with the minimum volume and mass of material. In this work we perform atomistic simulations on two of the most important of these, Fe and W. In this thesis we describe atomic-scale simulations of defects found in bcc systems. In part I we consider the vacancy and interstitial loop defects that are produced and accumulated as a result of irradiation-induced displacement cascades. We show that vacancy dislocation loops have a critical size below which they are highly unstable relative to planar void defects, and thus offer an explanation as to why they are so rarely seen in TEM observations of irradiated bcc metals. Additionally, we compare the diffusion rates of these vacancy loops to their interstitial counterparts and find that, while interstitial loops are more mobile, the difference in mobility is not as significant as might have been expected. In part II we study screw dislocations, which, as the rate limiting carriers of plastic deformation, are significantly responsible for the strength of materials. We present results from large-scale finite temperature molecular dynamics simulations of screw dislocations under stress and observe the thermally-activated kink-pair formation regime at low stress, which appears to be superseded by a frictional regime at higher stresses. The mobility functions fitted to the results are vital components in simulations of dislocation networks and other large-scale phenomena. Lastly, we develop a multi-string Frenkel-Kontorova model that allows us to study the core structure of screw dislocations. Subtle changes in the form of the interaction laws used in this model demonstrate the difference between the non-degenerate and degenerate core structures. We provide simple criteria to guarantee the correct structure when developing interatomic potentials for bcc metals.

<p dir="ltr">Electronic structure calculations, specifically plane wave Density functional theory (DFT) in conjunction with data science resources on the nanoHUB platform, are a powerful tool for the study of materials at extreme conditions. nanoHUB’s resources for FAIR (Findable, Accessible, Interoperable and Reproducible) data and workflows accelerate research and sharing of results. With these combined resources we studied the high-pressure properties and stability of various ceramic materials, such as the polytypes of silicon carbides (SiC).</p><p dir="ltr">Silicon carbides are of interest for their exceptional mechanical strength, thermal stability and chemical resistance making them attractive for applications at extreme conditions. To understand the temperature- and pressure-induced phase transitions we studied the electronic structure, phonon dispersion and elastic constants of major synthesizable SiC polytypes as a function of pressure. In addition, we report on the elastic constants as a function of pressure for the main polymorphs. This DFT workflows are published online, not only enhances the reproducibility of findings, but can also accelerates the discovery and development of new material properties.</p>

En biologie synthétique, il existe plusieurs manières d’adresser les problèmes soulevés dans plusieurs domaines comme la thérapeutique, les biofuels, les biomatériaux ou encore les biocapteurs. Nous avons choisi de nous concentrer sur l’une d’entre elles : les réseaux de régulation génétique (RRG). Un constat peut être fait : la diversité des problèmes résolus grâce aux RRGs est bridée par la complexité de ces RRGs, qui a atteint une limite. Quelles solutions s’offrent aux biologistes, pour repousser cette limite et continuer d’augmenter la complexité de leur système ? Cette thèse a pour but de fournir aux biologistes les outils nécessaires à la conception et à la simulation de RRGs complexes. Un examen de l’état de l’art en la matière nous a mené à adapter les outils de la micro-électronique à la biologie ainsi qu’à créer un algorithme de programmation génétique pour la conception des RRGs. D’une part, nous avons élaboré les modèles Verilog A de différents systèmes biologiques (passe-bande, proie-prédateur, repressilator, XOR) ainsi que de la diffusion spatiotemporelle d’une molécule. Ces modèles fonctionnent très bien avec plusieurs simulateurs électroniques (Spectre et NgSpice). D’autre part, les premières marches vers l’automatisation de la conception de RRGs ont été gravies. En effet, nous avons développé un algorithme capable d’optimiser les paramètres d’un RRG pour remplir un cahier des charges donné. De plus, la programmation génétique a été utilisée pour optimiser non seulement les paramètres d’un RRG mais aussi sa topologie. Ces outils ont su prouver leur utilité en apportant des réponses pertinentes à des problèmes soulevés lors du développement de systèmes biologiques. Ce travail a permis de montrer que notre approche, à savoir adapter les outils de la micro-électronique et utiliser des algorithmes de programmation génétique, est valide dans le contexte de la biologie synthétique. L’assistance que notre environnement de développement fournit au biologiste devrait encourager l’émergence de systèmes plus complexes. / In synthetic biology, Gene Regulatory Networks (GRN) are one of the main ways to create new biological functions to solve problems in various areas (therapeutics, biofuels, biomaterials, biosensing). However, the complexity of the designed networks has reached a limit, thereby restraining the variety of problems they can address. How can biologists overcome this limit and further increase the complexity of their systems? The goal of this thesis is to provide the biologists with tools to assist them in the design and simulation of complex GRNs. To this aim, the current state of the art was examined and it was decided to adapt tools from the micro-electronic field to biology, as well as to create a Genetic Programming algorithm for GRN design. On the one hand, models of diffusion and of other various systems (band-pass, prey-predator, repressilator, XOR) were created and written in Verilog A. They are already implemented and well-functioning on the Spectre solver as well as a free solver, namely NgSpice. On the other hand, the first steps of automatic GRN design were achieved. Indeed, an algorithm able to optimize the parameters of a given GRN according to a specification was developed. Moreover, Genetic Programming was applied to GRN design, allowing the optimization of both the topology and the parameters of a GRN. These tools proved their usefulness for the biologists’ community by efficiently answering relevant biological questions arising in the development of a system. With this work, we were able to show that adapting microelectronics and Genetic Programming tools to biology is doable and useful. By assisting design and simulation, such tools should promote the emergence of more complex systems.