Presented in this thesis are the results from an integrated experimental and modeling study on damage cascade formation in ion bombarded solids. The molecular dynamics (MD) simulations were performed by using LAMMPS (Large-scale Atomic/Molecular Massively Parallel Simulator). In one subtask, we studied damage cascade interactions caused by two 2 keV Si atoms simultaneously bombarding a crystalline Si substrate. We found that the enhanced displacement creation appears primarily in the thermal spike stage with all atoms at energies less than the displacement threshold. The study lead to the conclusion that the cascade interactions increased local melting by increasing energy deposition density, thus promoting defect creation. In another subtask, we studied radiation damage in Si0.8Ge2 layer caused by Agn clusters with number of atoms in a cluster, n, taking values from 1 to 4. It showed that strained SiGe, a material known to have poor radiation tolerance, still follows the overlap model, rather than the direct amorphization model. In the third subtask, MD simulation has shown that crowdion defects formed in bcc Fe are propagating along <111> directions. Crowdion defect starts to form when damage cascade reaches the maximum volume and contributes a second peak in defect buildups with increasing times. Upon defect recombination, crowdion defects shrink and form <111> oriented dumbbell defects at the crowdion end. In subsequent structural relaxation, <111> dumbbell defects rotate and finally align themselves with <110> directions. The surviving dumbbell defects represent a significant contribution to the final defect distribution after thermal spike formation. The overall research reveals atomic scale details of damage buildups at early stages of defect developments. Although the target systems cover both semiconductor materials and metal, these results show that MD simulation is a powerful tool to show the details at a spatial and time scale beyond experiments. These details are very important to develop understanding the precursor formation in defect clustering in such a case.

Nanoparticles (NP) offer great merits over controlling thermal, chemical and physical properties when compared to their micro-sized counterparts. The effectiveness of the dispersion of the NP is the key aspect of the applications in nanotechnology. The project studies the characterization and modification of functional NPs aided by the means of large scale molecular thermal dynamic computerized dispersing simulations, in the level of Nanoclusters (NC). Carrying out NP functionality characterisation in fluids can be enhanced, and analysed through computational simulation based on their interactions with fluidic media; in terms of thermo-mechanical, dynamic, physical, chemical and rheological properties. From the engineering perspective, effective characterizations of the nanofluids have also been carried out based on the particles sizes and particle-fluids Brownian motion (BM) theory. The study covered firstly, investigation of the pure CuO NP diffusion in water and hydrocarbon fluids, secondly, examination of the modified CuO NP diffusion in water. In both cases the studies were put under experiments and simulations for data collection and comparison. For simulation the COMPASS forcefield, smoothed particle hydrodynamic potential (SPH) and discrete particle dynamics potential (DPD) were implemented through the system. Excellent prediction of BM, Van der Waals interaction, electrostatic interaction and a number of force-fields in the system were exploited. The experimental results trend demonstrated high coherence with the simulation results. At first the diffusion coefficient was found to be 1.7e-8m2/s in the study of CuO NC in water based fluidic system. Secondly highly concurrent simulation results (i.e. data for viscosity and thermal conductivity) have been computed to experimental coherence. The viscosity trend of MD simulation and experimental results show a high level of convergence for temperatures between 303-323K. The simulated thermal conductivity of the water-CuO nanofluid was between 0.6—0.75W•m−1•K−1, showing a slight increase following a rise in temperature from 303 to 323 K. Moreover, the alkane-CuO nanofluid experimental and simulated work was also carried out, for analysing the thermo-physical quantities. The alkane-CuO nanofluid viscosity was found 0.9—2.7mpas and thermal conductivity is between 0.1—0.4W•m−1•K−1. Finally, the successful modification of the NPs on experimental and simulation platform has been analysed using different characterization variables. Experimental modification data has been quantified by using Fourier Transformation Infrared (FTIR) peak response, from particular ranges of interest i.e. 1667-1609cm-1 and 1668-1557cm-1. These FTIR peaks deduced Carboxylate attachment on the surface of NPs. Later, MD simulation was approached to mimic experimental setup of modification chemistry and similar agglomerations were observed as during experimental conditions. However, this approach has not been presented before; therefore this study has a significant impact on describing the agglomeration of modified NPs on simulation and experimental basis. Henceforth, the methodology established for metal oxide nanoparticle dispersion simulation is a novelty of this work.

Thermal transport properties are critical for applications ranging from thermal management to energy conversion. Passive thermal management has been an area of study for over a century and has only grown as technology has advanced because it requires no additional energy to remove heat. Changing the nanostructure of the materials involved in passive heat transfer methods, either by geometric changes or stoichiometric changes, can greatly improve the effectiveness of this heat transfer method. In order to explore this further, this work employs LAMMPS molecular dynamics (MD) simulation software to calculate the lattice thermal conductivity (λp) of a nanoparticle (NP) and material used indifferent passive heat transfer methods after either modifying their geometry or stoichiometry. The NPs this work will simulate are single-wall carbon nanotubes (SWCNTs), which have been well known for high λp, and their applications in improving thermal conductivity in matrix materials. The material this work will simulate is magnesium silicide (Mg2Si), a thermoelectric material. Thermoelectric materials, in general, become more efficient in converting heat into electrical power as their λp decreases. λp will be calculated for SWC-NTs of varying lengths, diameters, and at varying equilibration temperatures (Teq). λp will be calculated for samples of pure Mg2Si and Mg2Si with off-stoichiometry over a range of Teq values. Two methods will be used to induce the off-stoichiometry: atomic silicon (Si) substitutionals, and Si NPs. A range of stoichiometric ratios will be applied to the material by both methods, and then λp will be calculated for each of these cases. This is done so as to observe which method of stoichiometric change, given the same stoichiometric ratio, decreases λp greater, and, therefore, causes Mg2Si to be a better thermoelectric material. It is expected that increases in length will increase the λp of the SWCNT, while increases in diameter and Teq will decrease λp. It is expected that increases in atomic percent (a/o) Si and Teq will decrease λp regardless of the method of stoichiometric change, and that the Si NP method will decrease λp more than the atomic Si substitutional method.

Model of nanoscale deformation mechanisms of cellular structures could render different results depending on the molecular dynamics (MD) simulator chosen. Also, the comparison of different MD simulators is typically an intricate task, requiring all configurations be converted appropriately with available parameter choices. This study aims to perform and compare MD simulations between two MD programs (GROMACS and LAMMPS), in which a phospholipid bilayer is deformed under different strain states. The two systems produced similar deformation behaviors and strain state effect on bilayer failure. However, GROMACS produced more pores at lower strains, lower stress, and higher damage values. Multiple setting options and algorithm variations have been considered as possible explanations for the differences. Overall, the study aids in the cross-check of parameter settings and simulation results in MD research, particularly on the mechanical damage of bilayer membranes. Besides, based on that, GROMACS and LAMMPS could be further exploited with better reproducibility.

As terascale supercomputers become more common, and as the high-performance computing community turns its attention to petascale machines, the challenge of providing effective resource management for high-end machines grows in both importance and difficulty. These computing resources are by definition expensive, so the cost of underutilization is also high, e.g., wasting 5% of the compute nodes on a 10,000 node cluster is a much more serious problem than on a 100 node cluster. Moreover, the high energy and cooling costs incurred in maintaining these high end machines (often millions of dollars per year) can be justified only when these machines are used to their full capacity. On large clusters, conventional jobs schedulers are hard-pressed to achieve over 90% utilization with typical job-mixes. A fundamental problem is that most conventional parallel job schedulers only support static scheduling, so that the number of processors allocated to an application cannot be changed at runtime. As a result, it is common to see jobs stuck in the queue because they require just a few more processors than are currently available, resulting in long queue wait times for applications and low overall system utilization. A more flexible and effective approach is to support dynamic resource management and scheduling, where the number of processors allocated to jobs can be expanded or contracted at runtime. This is the focus of this dissertation --- dynamic resizing of parallel applications. Dynamic resizing significantly improves individual application turn-around time and helps the scheduler to achieve higher machine utilization and job throughput. This dissertation focuses on the potential benefits and challenges of dynamic resizing using ReSHAPE, a new framework for dynamic Resizing and Scheduling of Homogeneous Applications in a Parallel Environment. It also details several interesting and effective scheduling policies implemented in ReSHAPE and demonstrates their effectiveness to improve overall cluster utilization and individual application turn-around time. / Ph. D.

Dans ce rapport de mémoire, nous avons utilisé les méthodes numériques telles que la dynamique moléculaire (code de Lammps) et ART-cinétique. Ce dernier est un algorithme de Monte Carlo cinétique hors réseau avec construction du catalogue d'événements à la volée qui incorpore exactement tous les effets élastiques. Dans la première partie, nous avons comparé et évalué des divers algorithmes de la recherche du minimum global sur une surface d'énergie potentielle des matériaux complexes. Ces divers algorithmes choisis sont essentiellement ceux qui utilisent le principe Bell-Evans-Polanyi pour explorer la surface d'énergie potentielle. Cette étude nous a permis de comprendre d'une part, les étapes nécessaires pour un matériau complexe d'échapper d'un minimum local vers un autre et d'autre part de contrôler les recherches pour vite trouver le minimum global. En plus, ces travaux nous ont amené à comprendre la force de ces méthodes sur la cinétique de l'évolution structurale de ces matériaux complexes. Dans la deuxième partie, nous avons mis en place un outil de simulation (le potentiel ReaxFF couplé avec ART-cinétique) capable d'étudier les étapes et les processus d'oxydation du silicium pendant des temps long comparable expérimentalement. Pour valider le système mis en place, nous avons effectué des tests sur les premières étapes d'oxydation du silicium. Les résultats obtenus sont en accord avec la littérature. Cet outil va être utilisé pour comprendre les vrais processus de l'oxydation et les transitions possibles des atomes d'oxygène à la surface du silicium associée avec les énergies de barrière, des questions qui sont des défis pour l'industrie micro-électronique. / In this Master's thesis, we use the numerical methods such as molecular dynamics (LAMMPS's code) and kinetic-ART which is an on-the-fly off-lattice kinetic Monte Carlo algorithm that incorporates exactly all elastic effects. In the first, we compare a number of various algorithms used for sampling energy landscape of complex materials. The various algorithms chosen are those that use the Bell-Evans-Polanyi principle to progress on the potential energy surface.This study allowed us to understand the steps needed to escape a local minimum to another and to control research to quickly find the global minimum. This study also allowed us to understand the power of these methods on the kinetics of the structural evolution of complex materials. In the second part, we have developed a simulation tool (ReaxFF potential coupled with Kinetics-ART) able to study the first stages and oxidation process of silicon compare to the experimental time. To validate the system in place, we have tested the very first step of the silicon oxidation. The results obtained are in agreement with the literature. This tool will be used to understand the true oxidation process, the possible transitions of oxygen atoms at the silicon surface and the barrier associated with. Problem that are real challenges for the microelectronics industry.

A great interest has been shown for self-assembled organic nano-structures that can be used in a variety of optoelectronic applications, from element detection to home electronics. It is known from experimental research that sexiphenyl (6P) grown on muscovite mica substrate form uniaxially self-assembled nanofibers which together with sexithiophene (6T) deposited on top gives the possibility to tune their polarized emission. A key to continue develop and explore the full potential of this technique is to understand the mechanisms behind the growth. This thesis investigate the initial growth of 6P and 6T on a 6Pˆ<img src="http://www.diva-portal.org/cgi-bin/mimetex.cgi?%5Cleft(11%20%5Cbar%7B1%7D%20%5Cright)%20%20%20" /> nanofiber substrate through Molecular Dynamics (MD) simulations. The adsorption of the molecules has been simulated with Simulated Annealing (SA) where 6P align perfectly with the substrate for all coverage while 6T starts to align after a certain amount of coverage. Both molecules show a monotonic increase in the adsorption energy per molecule with an increasing coverage. The surface diffusion of the molecules has been studied and shows a higher movement for both in the direction of the longmolecular axis. / Project P25154-N20 "Hetero-epitaxy of organic-organic nanofibers"

Using equilibrium molecular dynamics simulations, an analysis of the key thermophysical properties critical to heat transfer processes is performed. Replication of thermal conductivity and shear viscosity observations found in experimental investigations were performed using a theoretical nanopthesis-fluid system and a novel colloid-fluid interaction potential to investigate the key nanofluid parameters. Analysis of both the heat current (thermal conductivity) and stress (shear viscosity) autocorrelation functions have suggested that the dominant physical mechanisms for thermal and momentum transport arises from enhancements to the longitudinal and transverse acoustic modes energy transfer brought about by the increased mass ratio of the nanopthesis to the fluid. This conclusion was further supported by analysis of the local density fluctuations surrounding increasing nanopthesis diameters where the longitudinal acoustic mode characteristics for density fluxes were seen to be enhanced by the presence of the heavier platinum nanopthesiss. It is then concluded that the key macroscopic characteristic in obtaining the largest thermal energy transfer enhancement is through the mass of the nanopthesis relative to the base fluid. Also, the small local density effects in the nanofluid are greatly affects the viscosity calculations. These conclusions provide the theoretical framework for many of the experimental results obtained.

<p>To achieving successfully commercial nuclear fusion energy, fully understanding of the interaction between plasma particles and plasma facing components is one of the essential issues. Tungsten, due to good thermal and mechanical properties such as high thermal conductivity and melting temperature, is one of the most promising candidates. However, the plasma facing components interacting with the extreme environmental conditions such as high temperature and radiation may lead to nanostructure formation, sputtering and erosion that will lead to material degradation. And these deformations may influence not only properties of plasma facing components but also might affect the plasma itself. For example, the contamination of plasma with a few amounts of tungsten, a high Z element, as a result of erosion or sputtering may cause core plasma cooling that results in loss of plasma confinement. Additionally, the retention of hydrogen isotopes, especially tritium, in tungsten is essential issue because of its radioactivity and market value.</p> In this study, deuterium trapping in tungsten is analyzed by molecular dynamics method and the effect of pre-irradiation on trapping is studied. Non-cumulative studies show that the increase in the energy of hydrogen isotopes rises the absorption rate, the initial implantation depth, and the average resting time for initial implantation. Additionally, the effect of implanted deuterium due to pre-irradiation on the hydrogen isotopes trapping is analyzed by combining both cumulative and non-cumulative simulations, and results indicate that while the increase in the pre-irradiation time raises the absorption rate of deuterium with higher energy than 80 eV, it causes a decrease the initial implantation depth and the average resting time for initial implantation because of deuterium-deuterium interactions. Additionally, the deuterium-deuterium interactions may transfer enough energy to implanted deuterium to start a motion which may lead to deeper implantation or escaping from the surface of tungsten. The escaping from surface as a result of deuterium-deuterium interaction could explain the decrease in accumulation rate of deuterium while absorption rate rises.

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