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abstract: The quest to find efficient algorithms to numerically solve differential equations isubiquitous in all branches of computational science. A natural approach to address this problem is to try all possible algorithms to solve the differential equation and choose the one that is satisfactory to one's needs. However, the vast variety of algorithms in place makes this an extremely time consuming task. Additionally, even after choosing the algorithm to be used, the style of programming is not guaranteed to result in the most efficient algorithm. This thesis attempts to address the same problem but pertinent to the field of computational nanoelectronics, by using PETSc linear solver and SLEPc eigenvalue solver packages to efficiently solve Schrödinger and Poisson equations self-consistently. In this work, quasi 1D nanowire fabricated in the GaN material system is considered as a prototypical example. Special attention is placed on the proper description of the heterostructure device, the polarization charges and accurate treatment of the free surfaces. Simulation results are presented for the conduction band profiles, the electron density and the energy eigenvalues/eigenvectors of the occupied sub-bands for this quasi 1D nanowire. The simulation results suggest that the solver is very efficient and can be successfully used for the analysis of any device with two dimensional confinement. The tool is ported on www.nanoHUB.org and as such is freely available. / Dissertation/Thesis / Masters Thesis Electrical Engineering 2020

Most ab initio simulation packages based on Density Functional Theory (DFT) use the Superposition of Atomic Densities (SAD) as a starting point of the self-consistent fi eld (SCF) iteration. However, this trial charge density without modeling atomic iterations nonlinearly may lead to a relatively slow or even failed convergence. This thesis proposes a machine learning-based scheme to improve the initial guess. We train a 3-Dimensional Convolutional Neural Network (3D CNN) to map the SAD initial guess to the corresponding converged charge density with simple structures. We show that the 3D CNN-processed charge density reduces the number of required SCF iterations at different unit cell complexity levels.

京都大学 / 0048 / 新制・課程博士 / 博士(理学) / 甲第19522号 / 理博第4182号 / 新制||理||1600(附属図書館) / 32558 / 京都大学大学院理学研究科化学専攻 / (主査)教授 吉村 一良, 教授 有賀 哲也, 教授 北川 宏 / 学位規則第4条第1項該当 / Doctor of Science / Kyoto University / DGAM

Titanium is a widely applied material in industries and characterized by highly anisotropic mechanical behaviour. To study the special property of titanium, many kinds of mechanical loading tests have been conducted. Moreover, researchers attempted to reproduce these experiments with numerical methods. This paper will present an overview about the deformation mechanisms and related representative studies of titanium. Among the numerical methods, Taylor type and self-consistent crystal plasticity models are two of the most common ones seen in literature. Simulation of some mechanical loading tests using visco-plastic self-consistent model was carried out and compared with the results given by Taylor type model. It has been found that self-consistent model prevails in the reproduction of stress-strain response and texture evolution. During the calculation of self-consistent model, there are totally 4 kinds of self-consistent schemes available for linearization process. The author investigated 4 groups of simulation works using different self-consistent schemes. But no evident distinction has been observed. The application of visco-plastic self-consistent model in commercial purity titanium is studied at the end. The simulation results successfully captured the general features of 9 mechanical loading tests. / Thesis / Master of Applied Science (MASc)

<p>For many applications within the defense, aerospace, and electricity-producing industries, available material choices for high-performance devices that fulfill necessary requirements are limited. Choosing a metallic material or a ceramic material may be optimal for only some of the required properties. For instance, choosing a metal may optimize ductility but compromise oxidation resistance, yield strength, or creep resistance. Of potential interest, ceramic-metal (cermet) composites can address several fundamental concerns such as high temperature mechanical toughness and stiffness and oxidation/corrosion resistance. However, cost-effective, scalable manufacturing of complex-shaped, high-temperature cermets can be challenging.</p> <p>A cermet of interest is niobium and yttrium oxide, Y2O3. Both materials exhibit high melting points with similar coefficients of thermal expansion. Basic thermodynamic calculations suggest that these materials are chemically compatible, and that Y2O3/Nb cermets may be generated by reactive melt infiltration using the patented Displacive Compensation of Porosity (DCP) process. With the DCP process, a liquid fills a porous perform, and a displacement reaction occurs to produce products of larger solid volume. This reaction yields the cermet of interest, formed in a reduced-stress condition, while maintaining a generally near net shape and high relative density.</p> <p>In order to get to the point of designing cermet components for various applications, a focus of this work has been to create a Y2O3/Nb composite by hot pressing powders at high temperatures at the predicted stoichiometric ratios, and then characterizing the thermal and mechanical properties. The reduction reaction between liquid yttrium and solid niobium (IV) oxide (NbO2) was then characterized to evaluate kinetic mechanisms affecting the reaction rate which is necessary for future DCP-based cermet component manufacturing.</p> <p>Lastly, the mechanical behavior of this cermet was modeled and compared to another cermet processed using liquid metal infiltration using a temperature-dependent elasto-visco-plastic self-consistent model. The effects of cooling from processing temperatures, as well as thermally cycling of these cermets, were quantified. As high temperature experiments can be time intensive with high costs, it is advantageous to have a computationally efficient, desktop design tool to quantify the impacts of changing processing and use conditions on material performance.</p>

京都大学 / 新制・課程博士 / 博士(工学) / 甲第23509号 / 工博第4921号 / 新制||工||1769(附属図書館) / 京都大学大学院工学研究科材料工学専攻 / (主査)教授 田中 功, 教授 中村 裕之, 教授 安田 秀幸 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

The adsorption of cationic and zwitterionic surfactants is studied in aqueous electrolyte solutions. A Maxwell relation is applied to Atomic Force Microscopy (AFM) data to obtain changes in surfactant adsorption as a function of the separation between two glass surfaces. In addition, self-consistent field theory (SCF) is used to calculate the adsorption profiles and interaction energies when two solid surfaces are brought into close proximity. Addition of surfactant is shown to affect the surface forces when lateral surfactant chain interactions are significant. The surfactant adsorbs and desorbs in response to over-lapping electric double-layers, with the adsorption being affected at larger solid-solid separations when the double-layer force is longer ranged. Furthermore, elimination off the surface charge or net surfactant charge eliminates adsorption with decreased solid-solid separation. The magnitude of the changes in surfactant adsorption at decreased separations is shown to scale with the chain length of the surfactant. Surfactant adsorption exceeds that required to regulate the surface charge according to the constant potential boundary condition in Poisson-Boltzmann theory. An equation of state including short-ranged (contact) tail interactions is proposed to describe both the adsorption of surfactant and the surface forces at small separations, where the double-layers overlap. Furthermore, SCF calculations show confinement-induced phase transitions when the surfactant layers on opposite surfaces merge. These phase transitions lead to further surfactant adsorption and a corresponding attractive force. / Ph. D.

The research presented in this thesis was carried out as part of a collaboration between the groups of Dr Tanja van Mourik at the School of Chemistry, University of St Andrews and Professor Jonathan Tennyson at the Department of Physics and Astronomy at University College London. This thesis presents State-Averaged Complete Active Space Self Consistent Field (SA-CASSCF) calculations on nucleic acid bases, deoxyribose and phosphoric acid H₃PO₄). In the case of uracil, for comparison, Multireference Configuration Interaction calculations were also performed. The SA-CASSCF orbitals were subsequently used in R-matrix electron scattering calculations using the close-coupling model. Of major importance for obtaining accurate SA-CASSCF results is the choice of the active space and the number of calculated states. Properties such as the electronic energy, number of configurations, excitation energy and dipole moment were considered in the choice of active space. Electron-collision calculations were performed on two of the most stable isomers of phosphoric acid, a weakly dipolar form with all OH groups pointing up and a strongly dipolar form where one OH group points down. A broad shape resonance at about 7 eV was found for both isomers. Ten-state close-coupling calculations suggest the presence of narrow, Feshbach resonances in a similar energy region. Elastic and electronically inelastic cross sections were calculated for both isomers. The R-matrix calculations on uracil were done by the group from UCL. R-matrix calculations are currently being done on guanine. Scattering calculations on the other DNA bases will be performed in the near future.

O uso de sistemas multiprocessados para a resolução de problemas que demandam um grande poder computacional tem se tornado cada vez mais comum. Porém a conversão de programas seqüenciais para programas concorrentes ainda não é uma tarefa trivial. Dentre os fatores que tornam esta tarefa difícil, destacamos a inexistência de um paradigma único e consolidado para a construção de sistemas computacionais paralelos e a existência de várias plataformas de programação para o desenvolvimento de programas concorrentes. Nos dias atuais ainda é impossível isentar o programador da especificação de como o problema será particionado entre os vários processadores. Para que o programa paralelo seja eficiente, o programador deve conhecer a fundo aspectos que norteiam a construção do hardware computacional paralelo, aspectos inerentes à arquitetura onde o software será executado e à plataforma de programação concorrente escolhida. Isto ainda não pode ser mudado. O ganho que podemos obter é na implementação do software paralelo. Esta tarefa pode ser trabalhosa e demandar muito tempo para a depuração, pois as plataformas de programação não possibilitam que o programador abstraia dos elementos de hardware. Tem havido um grande esforço na criação de ferramentas que otimizem esta tarefa, permitindo que o programador se expresse mais fácil e sucintamente quanto à para1elização do programa. O presente trabalho se baseia na avaliação dos aspectos ligados à implementação de software concorrente utilizando uma plataforma de portabilidade chamada High Performance Fortran, aplicado a um problema específico da física: o cálculo da estrutura de bandas de heteroestruturas semicondutoras. O resultado da utilização desta plataforma foi positivo. Obtivemos um ganho de performance superior ao esperado e verificamos que o compilador pode ser ainda mais eficiente do que o próprio programador na paralelização de um programa. O custo inicial de desenvolvimento não foi muito alto, e pode ser diluído entre os futuros projetos que venham a utilizar deste conhecimento pois após a fase de aprendizado, a paralelização de programas se torna rápida e prática. A plataforma de paralelização escolhida não permite a paralelização de todos os tipos de problemas, apenas daqueles que seguem o paradigma de paralelismo por dados, que representam uma parcela considerável dos problemas típicos da Física. / The employment of multiprocessor systems to solve problems that demand a great computational power have become more and more usual. Besides, the conversion of sequential programs to concurrent ones isn\'t trivial yet. Among the factors that makes this task difficult, we highlight the nonexistence of a unique and consolidated paradigm for the parallel computer systems building and the existence of various programming platforms for concurrent programs development. Nowadays it is still impossible to exempt the programmer of the specification about how the problem will be partitioned among the various processors. In order to have an efficient parallel program the programmer have to deeply know subjects that heads the parallel hardware systems building, the inherent architecture where the software will run and the chosen concurrent programming platform. This cannot be changed yet. The gain is supposed to be on the parallel software implementation. This task can be very hard and consume so much time on debugging it, because the programming platforms do not allow the programmer to abstract from the hardware elements. It has been a great effort in the development of tools that optimize this task, allowing the programmer to work easily and briefly express himself concerning the software parallelization. The present work is based on the evaluation of aspects linked to the concurrent software implementation using a portability platform called High Performance Fortran, applied to a physics specific problem: the calculus of semiconductor heterostructures? valence band structure. The result of the use of this platform use was positive. We obtained a performance gain superior than we expected and we could assert that the compiler is able to be more effective than the programmer on the paralelization of a program. The initial development cost wasn\'t so high and it can be diluted between the next projects that would use the acquired knowledge, because after the learning phase, the programs parallelization task becomes quick and practical. The chosen parallelization platform does not allow the parallelization of all kinds of problems, but just the ones that follow the data parallelism paradigm that represents a considerable parcel of tipical Physics problems.