Modeling and Simulation of Compositional Engineering in Sige Films Using Patterned Stress Fields

Semiconductor alloys such as silicon-germanium (SiGe) offer attractive environments for engineering quantum-confined structures that are the basis for a host of current and future optoelectronic devices. Although vertical stacking of such structures is routinely achieved via heteroepitaxy, lateral manipulation has proven much more challenging. I describe a new approach that suggests that a patterned elastic stress field generated with an array of nanoscale indenters in an initially compositionally uniform SiGe substrate will drive atomic interdiffusion, leading to compositional patterns in the near-surface region of the substrate. While this approach may offer a potentially efficient and robust pathway to producing laterally ordered arrays of quantum-confined structures, there is a large set of parameters important to the process. Thus, it is difficult to consider this approach using only costly experiments, which necessitates detailed computational analysis. First, I review computational approaches to simulating the long length and time scales required for this process, and I develop and present a mesoscopic model based on coarse-grained lattice kinetic Monte Carlo that quantitatively describes the atomic interdiffusion processes in SiGe alloy film subjected to applied stress. I show that the model provides predictions that are quantitatively consistent with experimental measurements, and I examine the impact of basic indenter geometries on the patterning process. Second, I extend the model to investigate the impact of several process parameters, such as more complicated indenter shapes and pitches. I find that certain indenter configurations produce compositional patterns that are favorable for use as lateral arrays of quantum-confined structures. Finally, I measure a set of important physical parameters, the so-called “activation volumes” that describes the impact of stress on diffusion. The values of these parameters are not well established in the literature. I make quantitative connections to the range of values found in the literature and characterize the effects of different stress states on the overall patterning process. Finally, I conclude with ideas about alternative pathways to quantum confined structure generation and possible extensions of the framework developed

Modeling and numerical study of the diffusion of point defects in α−iron

Le fer et les alliages à base de fer présentent un intérêt considérable pour la communauté de la modélisation des matériaux en raison de l’immense importance technologique de l’acier. Les alliages ferritiques à base de fer sont largement utilisés dans les industries aéronautique et nucléaire en raison de leur résistance mécanique élevée, de leur faible dilatation à haute température et de leur résistance à la corrosion. Ces propriétés sont cependant affectées par des défauts ponctuels intrinsèques et extrinsèques. Dans cette thèse, nous décrivons en détail la cinétique des défauts ponctuels dans le fer α en utilisant la technique d’activation-relaxation cinétique (ARTc), une méthode de Monte Carlo cinétique hors réseau avec construction de catalogue à la volée. Plus précisément, nous nous intéressons aux mécanismes de diffusion du carbone (C) et des amas de lacunes dans le fer α. Dans un premier temps, nous étudions l’effet de la pression sur la diffusion du carbone dans le joint de grains de fer α. Nous constatons que l’effet de la pression peut fortement modifier la stabilité et la diffusivité du carbon dans le joint de grains d’une manière qui dépend étroitement de l’environnement local et de la nature de la déformation. Ceci peut avoir un impact majeur sur l’évolution des matériaux hétérogènes, avec des variations de pression locale qui altéreraient fortement la diffusion à travers le matériau. Nous étudions également l’évolution structurale des amas de lacunes contenant de deux à huit lacunes dans le fer α. Nous décrivons en détail le paysage énergétique, la cinétique globale et les mécanismes de diffusion associés à ces défauts. Nos résultats montrent des mécanismes de diffusion complexes même pour des défauts aussi simples que de petits amas de lacunes. Enfin, dans le dernier chapitre, nous discutons une approche de gestion de petites barrières par bassin local dans ARTc. Les simulations de Monte Carlo cinétiques deviennent inefficaces dans les systèmes où le paysage énergétique est constitué de bassins avec de nombreux états reliés par des barrières énergétiques très faibles par rapport à celles nécessaires pour quitter ces bassins. Au fur et à mesure que le système évolue état par état, il est beaucoup plus susceptible d’effectuer des événements répétés (appelés oscillateurs) à l’intérieur du bassin d’énergie de piégeage que de s’échapper du bassin. De tels osccilateurs ne font pas progresser la simulation et ne fournissent que peu d’informations au-delà d’uen première évaluation de ces états. Notre algorithme de bassin local détecte, à la volée, des groupes d’états oscillants et les consolide en bassins locaux, que nous traitons avec la méthode de taux moyen d’auto-construction de bassin (bac-MRM), une approche de type équation maîtresse selon la méthode du taux moyen.Iron and iron-based alloys are of considerable interest to the materials modelling community because of the immense technological importance of steel. Iron-based ferritic alloys are widely used in aeronautic and nuclear industries due to their high mechanical strength, low expansion at high temperatures, and corrosion resistance. These properties are affected by intrinsic and extrinsic point defects, however. In this thesis, we describe in detail the kinetics of point defects in α−iron using the kinetic activation-relaxation technique (kART), an off-lattice kinetic Monte Carlo method with on-the-fly catalog building. More specifically, we focus on the diffusion mechanisms of carbon and vacancy clusters in α−iron. First, we study the pressure effect on carbon diffusion in the grain boundary (GB) of α−iron. We find that the effect of pressure can strongly modify the C stability and diffusivity in the GB in ways that depend closely on the local environment and the nature of the deformation. This can have a major impact on the evolution of heterogeneous materials, with variations of local pressure that would strongly alter diffusion across the material. We also study the structural evolution of vacancy clusters containing two to eight vacancies in α−iron. We describe in detail the energy landscape, overall kinetics, and diffusion mechanisms associated with these defects. Our results show complex scattering mechanisms even for defects as simple as small vacancy clusters. Finally, in the last chapter, we discuss a local basin approach to managing low barrier events in the kART. Kinetic Monte Carlo simulations become inefficient in systems where the energy landscape consists of basins with numerous states connected by very low energy barriers compared to those needed to leave these basins. As the system evolves state by state, it is much more likely to perform repeated events (so-called flickers) inside the trapping energy basin than to escape the basin. Such flickers do not progress the simulation and provide little insight beyond the first identification of those states. Our local basin algorithm detects, on the fly, groups of flickering states and consolidates them into local basins, which we treat with the basin-auto-constructing Mean Rate Method (bac-MRM), a master equation-like approach based on the mean-rate method

Atomistic Studies of Point Defect Migration Rates in the Iron-Chromium System

Generation and migration of helium and other point defects under irradiation causes ferritic steels based on the Fe-Cr system to age and fail. This is motivation to study point defect migration and the He equation of state using atomistic simulations due to the steels' use in future reactors. A new potential for the Fe-Cr-He system developed by collaborators at the Lawrence Livermore National Laboratory was validated using published experimental data. The results for the He equation of state agree well with experimental data. The activation energies for the migration of He- and Fe-interstitials in varying compositions of Fe-Cr lattices agree well with prior work. This research did not find a strong correlation between lattice ordering and interstitial migration energ

A hybrid model of ion-induced syrface modification with prompt molecular dynamics and lattice-free kinetic Monte Carlo diffusion

Ion beam nanopatterning is a robust, scalable technique for modification and fabrication of nanostructured surfaces. An ion beam incident on a surface acts as an athermal source of particles and energy, driving the surface far from equilibrium and leading to the emergence of metastable compositional and morphological phases. However, the fine process control needed for advanced nanotechnology applications remains elusive due to a lack of fundamental physical understanding of nanostructure formation and growth on complex, multi-component surfaces such as III-V semiconductors or metal-silicon systems. Recent experimental progress in the field has demonstrated the evolution of a three-dimensionally complex surface compositional profile during low-energy ion beam irradiation of III-V semiconductor systems such as GaSb, which is a necessary precursor to formation of ordered nanostructures. Novel analysis of x-ray scattering measurements indicates that the nanopatterning kinetics are described by highly nonlinear, nucleation-and-growth kinetics which are not included in any theoretical treatment of ion beam nanopatterning of compositionally complex materials. To elucidate the compositionally driven mechanisms which lead to these kinetics, large-scale computational simulations have been designed and carried out on the Blue Waters supercomputer at the University of Illinois and the Advanced Cyberinfrastructure (ACI) system at Pennsylvania State University. Large-scale molecular dynamics (MD) simulations of 500 eV Kr+ ion irradiation of amorphous GaSb surfaces have connected the compositional depth profile observed in experiments to lateral compositional gradients via thermodynamically driven phase separation. This lateral compositional evolution is a necessary precursor for a pattern-forming surface instability. Other large-scale MD studies of GaSb(110) irradiation from initially-pristine surface conditions have shown the formation of Sb protoclusters due to prompt ion-induced collisional effects at high irradiation fluences exceeding 1015 cm-2. The protocluster formation is accompanied by significant structural transformation of the surface, including bulk amorphization, reduction of average per-atom bonding energies, and prevalence of non-tetrahedral bonding states which would otherwise characterize an amorphous semiconductor surface. However, a long temporal scale mechanism such as surface diffusion is necessary to connect these disruptive phenomena into a complete model of nanopattern formation. Finally, a large battery of single-ion impact MD simulations under a range of ion beam parameters into GaSb surfaces with variable compositional depth profiles has elucidated the connection between lateral variation of the compositional depth profile and local morphological instability. Specifically, the presence of a compositional phase interface near the surface leads to an increase in ion-induced energy deposition at or near the surface monolayer, which leads to enhanced surface erosion (i.e., sputtering) when the surface monolayer is Sb-enriched and/or when the sub-surface is Ga-enriched. Given this finding, the key physical mechanisms which remain to be deciphered are those which drive the three-dimensional compositional evolution of the ion-irradiated surface and activate this sputtering instability. Accordingly, the culmination this work is a highly-parallelized, hybrid molecular dynamics/kinetic Monte Carlo (MD/KMC) model designed to simulate nanopattern formation on III-V and other compositionally complex surfaces. This diffusion model relies on a lattice-free point defect characterization method to analyze the defect distribution in the highly disordered ion irradiated surface. These defects then mediate diffusion events which are identified using per-atom neighbor lists and bond structural configurations to determine the activation energy. Therefore, the model is termed structural kinetic Monte Carlo (SKMC). The SKMC approach allows computational modeling to extend beyond the prompt temporal regime accessible by MD alone, addressing the three-dimensionally complex evolution of the surface beyond the microsecond scale. By alternating between MD ion irradiation steps and SKMC steps, a complete atomistic model of ion beam nanopatterning is therefore constructed. The application of this new modeling approach is demonstrated for the case of ion beam irradiation of cleaved GaSb surfaces up to a fluence of 4 × 1015 cm-2. Specifically, hybrid MD/SKMC simulations test the hypothesis that prompt cluster formation, diffusion-driven cluster growth, and compositional depth profile-modulated sputtering yields are the fundamental mechanisms driving nanopattern formation and growth. This modeling approach has broad applications beyond semiconductor surfaces to any class of complex nanomaterials under ion beam or plasma irradiation, such as high-entropy alloys currently under consideration as structural materials for fusion device applications

Multiscale modelling for fusion and fission materials: the M4F project

The M4F project brings together the fusion and fission materials communities working on the prediction of radiation damage production and evolution and its effects on the mechanical behaviour of irradiated ferritic/martensitic (F/M) steels. It is a multidisciplinary project in which several different experimental and computational materials science tools are integrated to understand and model the complex phenomena associated with the formation and evolution of irradiation induced defects and their effects on the macroscopic behaviour of the target materials. In particular the project focuses on two specific aspects: (1) To develop physical understanding and predictive models of the origin and consequences of localised deformation under irradiation in F/M steels; (2) To develop good practices and possibly advance towards the definition of protocols for the use of ion irradiation as a tool to evaluate radiation effects on materials. Nineteen modelling codes across different scales are being used and developed and an experimental validation programme based on the examination of materials irradiated with neutrons and ions is being carried out. The project enters now its 4th year and is close to delivering high-quality results. This paper overviews the work performed so far within the project, highlighting its impact for fission and fusion materials science.This work has received funding from the Euratom research and training programme 2014-2018 under grant agreement No. 755039 (M4F project)