A fundamental quantum mechanical modelling approach is used for calculating liquid diffusion parameters in cemented carbides. Up to now, no detailed description of diffusion for alloying elements in a liquid Co matrix is available. Neither are experimental measurements found in the literature for the self- or impurity diffusion in the liquid Co system. State of the art application is the description of gradient formation in cemented carbide systems using DICTRA. In this work it is assumed that diffusion during sintering of cemented carbides takes place mainly in the liquid Co binder phase. With this assumption one can calculate the diffusion coefficient for different alloying elements like W, Ti, N and C in a liquid Co matrix phase. The mean square displacement (MSD) of the diffusing atoms is used to obtain the diffusion coefficients which could be simulated by Ab initio Molecular Dynamics (AIMD). By fitting the computed temperature dependence with the Arrhenius relation one can determine the frequency factor and the activation energy which allows to give a quantitative description of the diffusion. Three methods will be used for validating the data from this work. Available estimated literature values based on calculations (scaling laws, a modified Sutherland equation and classical molecular dynamics) will be used to compare the results in a first instance. The general agreement for diffusion in liquid metals will be done by comparison with experimental data for the liquid Fe system. In a last step, the diffusion values obtained by this work will be used to create a kinetic database for DICTRA. The gradient simulations will be compared with experimentally measured gradients. The AIMD simulations are performed for binary diffusion systems to investigate the diffusion between the liquid Co matrix and one type of alloying element. In a second approach the diffusion for a multicomponent systems with Co, W, Ti and C has been performed. The results from the present AIMD simulations could be shown to be in good agreement with the literature. Only two DICTRA simulations could be performed within the timeframe of this work. Both are predicting a ~3 times bigger gradient zone whereas the initial choice of the labyrinth factor λ = f could be identified as a possible source of disagreement. A labyrinth factor of λ = f2 with the calculated mobility values from the AIMD calculations should give improved results. Although the results from those simulations are not available to this date. The two approaches of the diffusion simulations in the binary and multicomponent system are giving matching results. The non-metallic elements C and N are diffusing two times faster than the fastest metallic element Co. The diffusivity of Ti is slightly lower than Co and W could be identified as the element with the slowest diffusion within the liquid Co matrix. Further investigations of the liquid structure could indicate the tendency to form bonds between C and W and between C and Ti. This gives slowed down diffusion of C in the multicomponent system compared to the diffusion in the binary Co-C system.

<div>The recent decades have witnessed increased efforts to push the efficiency of energy systems beyond existing limits in order to keep pace with the rising global energy demands. Such efforts involve finding bulk materials and nanostructures with desired thermal properties such as thermal conductivity (k). For example, identifying high k materials is crucial in thermal management of vertically integrated circuits (ICs) and flexible nanoelectronics, which will power the next generation personal computing devices. On the opposite end of the spectrum, designing ultra-low k materials is essential for improving thermal barrier coatings in turbines and creating high performance thermoelectric (TE) devices for waste heat harvesting. In this dissertation, we identify nanostructures with such extreme thermal transport properties and explore the underlying phonon and photon transport mechanisms. Our approach follows two main avenues for evaluating potential candidates: (a) high fidelity atomistic simulations and (b) rapid machine learning-based property prediction and design optimization. The insight gained into the governing physics enables us to theoretically predict new materials for specific applications requiring high or low k, propose accelerated design optimization pathways which can significantly reduce design time, and advance the general understanding of energy transport in semiconductors and dielectric materials.</div><div><br></div><div>Bi2Te3, Sb2Te3 and nanostructures have long been the best TE materials due to their low κ at room temperatures. Despite this, computational studies such as molecular dynamics (MD) simulations on these important systems have been few, due to the lack of a suitable interatomic potential for Sb2Te3. We first develop interatomic potential parameters to predict thermal transport properties of bulk Sb2Te3. The parameters are fitted to a potential energy surface comprised of density functional theory (DFT) calculated lattice energies, and validated by comparing against experimental and DFT calculated lattice constants and phonon properties. We use the developed parameters in equilibrium MD simulations to calculate the thermal conductivity of bulk Sb2Te3 at different temperatures. A spectral analysis of the phonon transport is also performed, which reveals that 80% of the total cross-plane k is contributed by phonons with mean free paths (MFPs) between 3-100 nm. </div><div><br></div><div>We then use MD simulations to calculate phonon transport properties such as thermal conductance across Bi2Te3 and Sb2Te3 interface, which may account for the major part of the total thermal resistance in nanostructures. By comparing our MD results to an elastic scattering model, we find that inelastic phonon-phonon scattering processes at higher temperatures increases interfacial conductance by providing additional channels for energy transport. Finally, we calculate the thermal conductivities of Bi2Te3/Sb2Te3 superlattices (SLs) of varying period. The results show the characteristic minimum thermal conductivity, which is attributed to the competition between incoherent and coherent phonon transport regimes. Our MD simulations are the first fully predictive studies on this important TE system and pave the way for further exploration of nanostructures such as SLs with interface diffusion and random multilayers (RMLs).</div><div><br></div><div>The MD simulations described in the previous section provide high-fidelity data at a high computational cost. As such, manual intuition-based search methods using these simulations are not feasible for searching for low-probability-of-occurrence systems with extreme thermal conductivity. In view of this, we use machine learning (ML) techniques to accelerate and efficiently perform nanostructure design optimization within such large design spaces. First, we use a Genetic Algorithm (GA) based optimization method to efficiently search the design space of fixed length Si/Ge random multilayers (RMLs) for the structure with lowest k, which is found to be lower than the SL k by 33%. By comparing thermal conductivity and interface resistances between optimal and sub-optimal structures, we identify non-intuitive trends in design parameters such as average period and degree of randomness of layer thicknesses. </div><div><br></div><div>While machine learning (ML) has shown increasing effectiveness in optimizing materials properties under known physics, its application in discovering new physics remains challenging due to its interpolative nature. We demonstrate a general-purpose adaptive ML-accelerated search process that can discover unexpected lattice thermal conductivity (k) enhancement in aperiodic superlattices (SLs) as compared to periodic superlattices, with implications for thermal management of multilayer-based electronic devices. We use molecular dynamics simulations for high-fidelity calculations of k, along with a convolutional neural network (CNN) which can rapidly predict k for a large number of structures. To ensure accurate prediction for the target unknown SLs, we iteratively identify aperiodic SLs with structural features leading to locally enhanced thermal transport and include them as additional training data for the CNN. The identified structures exhibit increased coherent phonon transport owing to the presence of closely spaced interfaces.</div><div><br></div><div>We also demonstrate the application of ML in optimization of photonic multilayered structures with enhanced reflectivity to radiation heat flux, which is required for applications such as high temperature thermal barrier coatings (TBCs). We first perform a systematic variation of design parameters such as total thickness and average layer thickness of CeO2-MgO multilayers, and quantify their influence on the spectral and total reflectivity. The effect of randomization of layer thicknesses is also studied, which is found to increase the reflectivity due to localization of photons in certain spatial regions of the multilayer structure. Next, we employ a GA search method which can efficiently identify RML structures with reflectivity enhancements of ~22%, 20%, 20% and 10% over that obtained in randomly generated RML structures for total thicknesses of 5,10,20 and 30 microns respectively. We also calculate the spectral reflectivity and the field intensity distribution within the optimal and sub-optimal RML structures. We find that the electric field intensity can be significantly enhanced within certain spatial regions within the GA-optimized RMLs in comparison to non-optimized and periodic structures, which implies the high degree of randomness-induced photon localization leading to enhanced reflectivity in the GA-optimized structures.</div><div><br></div><div>In summary, our work advances the design or search for materials and nanostructures with targeted thermal transport properties such as low and high thermal conductivity and high reflectivity. The new insights provided into the underlying physics will guide the design of promising nanostructures for high efficiency energy systems. </div><div><br></div>

In order to study the electronic and optical properties of complex materials an approach providing a reliable estimate of band gaps in combination with the reasonable description of the ground state is required. In the present study of pure and defective perovskite crystals, the fulfillment of such requirements is clearly demonstrated using a simple hybrid HF/DFT scheme containing an admixture of non-local Fock exchange. In present theoretical investigations, a wide class of perovskite oxides is represented by three, the most attractive (from a scientific point of view) crystals of SrTiO3, BaTiO3, and PbTiO3 in their high symmetry cubic phases. These perovskite crystals present a great technological and fundamental interest due to their numerous applications related to ferroelectricity, non-linear and electro-optics, superconductivity, and catalysis. Although the above-mentioned perovskite-type materials have been intensively investigated theoretically and experimentally at least in the last fifteen years, a proper description of their electronic properties is still an area of active research. In order to make a contribution to the explanation of various electro-optical effects observed in perovskite materials, their ground-state properties have been calculated from first principles and analyzed in the present study.

京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第17985号 / 工博第3814号 / 新制||工||1584(附属図書館) / 80829 / 京都大学大学院工学研究科電子工学専攻 / (主査)教授 川上 養一, 教授 藤田 静雄, 准教授 浅野 卓 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

In der vorliegenden Arbeit wird die Aufklärung der Konformation von Peptiden mit speziell modifizierten Aminosäuren beschrieben. Die Methoden der theoretischen Chemie (Quantenchemie, Molekülmechanik, Moleküldynamik) bilden dabei die Grundlage der Konformationsanalysen. Durch systematische Anwendung dieser Methoden werden im ersten Teil der Arbeit die konformativen Eigenschaften verschiedener [beta]-Aminosäuren und ihrer Oligomere ([beta]-Peptide) untersucht. Aus diesen Ergebnissen werden anschließend Regeln für das Sekundärstrukturdesign von ß-Peptiden abgeleitet. Der zweite Teil beschäftigt sich mit der theoretischen Konformationsanalyse von [alpha]- Hydrazinosäuren und ihrer Oligomere (Hydrazinopeptide). Aus den gewonnenen Erkenntnissen über die Ausbildung charakteristischer Sekundärstrukturelemente in diesen Verbindungen wird ebenfalls ein Regelwerk für das Design von Sekundärstrukturen aufgestellt. / The present work describes the conformational characteristics of pepttides with specifically modified amino acid constituents. For this purpose, the methods of theoretical chemistry (quantum chemistry, molecular mechanics, molecular dynamics) are utilisied for the conformational analyses. The conformation of various [beta]-amino acids and their oligomers ([beta]-peptides) are inverstigated in the first part of this work applying these methods. Rules for the design of definite secondary structures in [beta]-peptides are then derived from the obtained results. In the second part, systematic theoretical conformational analyses on [alpha]-hydrazino acids and their oligomers (hydrazino peptides) are described. The results are then used to compile a set of rules for the formation of characteriasitc secondary structures in this class of compounds.

The importance of radical-water complexes in the atmosphere is explored in this dissertation. Radicals, although present in small concentrations in the atmosphere, play a significant role in creating and removing atmospheric pollution. As the atmosphere warms and consequently gets wetter, it is essential to understand the effects of water vapor on radical chemistry. This dissertation reports studies on the effects of water vapor on the kinetics of the self-reaction of β-hydroxyethyl peroxy radical (β-HEP), a prominent organic peroxy radical in the atmosphere. Both experimental and computational studies have been performed to examine the effects of water vapor on the kinetics of the self-reaction. The influence of water vapor and temperature on the reaction rate constant is presented. The rate of the self-reaction increases between 2 to 6 times with an increase in water vapor and decrease in temperature. The products of the self-reaction in the presence and absence of water vapor have been computed using high level ab initio calculations. Major products include alkoxy radicals, peroxides, aldehydes, alcohols and oxygen. A new reaction pathway leading to formation of hydroperoxy radical (HO2) from the self-reaction of β-HEP in the presence of water vapor was identified. In the presence of high NOx concentration HO2, forms tropospheric ozone, which is classified as a harmful pollutant by the Environmental Protection Agency (EPA). Like tropospheric ozone, aerosols are also classified as harmful pollutants by the EPA. Sulfuric acid-water complexes are estimated to be the primary reason for new aerosol formation in the atmosphere. However, the sulfuric acid concentration in the atmosphere alone is not sufficient to account for observed aerosol concentrations. Classical nucleation theory is used to explain new particle formation (NPF), which is initiated by the formation of a nucleating site (a highly polar complex). This dissertation explores the role of various radical-molecule complexes acting as the nucleating site. Experimentally, the HO2-water complex is studied as a possible nucleating site for NPF. A new instrument was developed to create and measure radical-water complex initiated particle formation. The instrument incorporates two scanning mobility particle sizers (SMPS) to measure the size distribution and number density of the aerosol particles formed. The experimental setup uses UV absorption spectroscopy and wavelength modulated spectroscopy to measurethe HO2 radical and water vapor concentrations in the reaction cell. No significant particle formation was observed at room temperature and pressure. Particle formation from the HO2-water complex, may occur at lower temperatures. Additional radical-molecule complexes have been studied computationally in an effort to identify other possible nucleating sites for particle formation. In particular, the complexes of sulfuric acid, nitric acid, acetic acid and formic acid with ammonia, amidogen radical (NH2) and imidogen radical (NH) have been studied. H2SO4-NH2 and HNO3-NH2 complexes show the potential to act as nucleating sites for formation of aerosol particles in the atmosphere. In summary, water mediated chemistry plays a significant role in the atmosphere and must be included in scientific models to better predict pollution levels in the atmosphere.

<p>Ni-base superalloys are among the highest temperature capable alloys and are used pervasively throughout the transportation, energy, and nuclear industries. However, their microstructures have been largely limited to containing the γ´ (cubic) and γ´´ (tetragonal) phases to enable high strength at elevated temperatures, and this fixation has restricted alloy development opportunities. In the past three decades, a new set of alloys, strengthened by the γ´´´ (orthorhombic) phase, was developed by Haynes International. The alloys exhibit comparable strength to existing Ni-based superalloys and show a 25% decrease in the thermal expansion coefficient, designed for tighter clearances (thus improving engine efficiency) and help to reduce thermally induced fatigue from engine cycling. </p> <p>The newest iteration of such alloys, HAYNES^® 244^®, has a nominal composition of Ni-22.5Mo-8Cr-6W (wt.%), and each alloying element is used to help precipitate the γ´´´-Ni₂(Cr, Mo, W) phase. The deformation mechanisms of this material are currently unknown. Previous studies investigating the predecessor alloy, HAYNES^® 242^® alloy, showed deformation twinning to be the dominant deformation mechanism during mechanical testing, but the physical phenomena responsible for this mode of deformation were not clearly elucidated. As a result, the primary motivation of this project is to understand the deformation behavior of the 244 alloy from the atomistic level and upwards. </p> <p>This work details efforts to elucidate these deformation mechanisms using an integrated computational and experimental approach. First-principles calculations were performed to determine the entire generalized stacking fault energy (GSFE) surface and slip pathways of the γ´´´ phase for dislocation slip. The various planar defects that could form from dislocation slip were predicted to provide significant barriers for dislocation motion due to their very high planar defect energies (~1000 mJ/m²), likely precluding shearing of the precipitates. We incorporated these results into phase field dislocation dynamics (PFDD) to simulate dislocation-precipitate interactions of finite size. These results showed that the planar defect energies of the γ´´´ phase largely govern the deformation behavior and critical resolved shear stress for precipitate shearing, regardless of precipitate shape, size, or orientation. Extensive mechanical testing conducted from room temperature up to 760 ºC over strain rates ranging from 10^-9 s^-1 to 10^-4 s^-1 combined with transmission electron microscopy validated the predicted deformation structures of creep and tensile samples. Shearing of individual precipitates by intrinsic and extrinsic stacking faults, as well as extensive deforming twinning, was observed. The integrated GSFE and PFDD simulations showed that the precipitates would resist dislocation shearing and favor twinning as the preferred deformation mechanism at all temperatures and strain rates investigated. These results provide pathways for microstructural and composition modification to further increase the strength of γ´´´ strengthened alloys in the future.</p> <p><br></p>

This dissertation undertakes theoretical and computational research to characterize and understand in detail atomic configurations and electronic structural properties of surfaces and interfaces at the nano-scale, with particular emphasis on identifying the factors that control atomic-scale diffusion and transport properties. The overarching goal is to outline, with examples, a predictive modeling procedure of stable structures of novel materials that, on the one hand, facilitates a better understanding of experimental results, and on the other hand, provide guidelines for future experimental work. The results of this dissertation are useful in future miniaturization of electronic devices, predicting and engineering functional novel nanostructures. A variety of theoretical and computational tools with different degrees of accuracy is used to study problems in different time and length scales. Interactions between the atoms are derived using both ab-initio methods based on Density Functional Theory (DFT), as well as semiempirical approaches such as those embodied in the Embedded Atom Method (EAM), depending on the scale of the problem at hand. The energetics for a variety of surface phenomena (adsorption, desorption, diffusion, and reactions) are calculated using either DFT or EAM, as feasible. For simulating dynamic processes such as diffusion of adatoms on surfaces with dislocations the Molecular Dynamics (MD) method is applied. To calculate vibrational mode frequencies, the infinitesimal displacement method is employed. The combination of non-equilibrium Green’s function (NEGF) and DFT is used to calculate electronic transport properties of molecular devices as well as interfaces and junctions.

Ion implantation of titania nanotubes is a highly versatile approach for tailoring structural and electrical properties. While recently self-organized nanoscale compositional patterning has been reported, the atomistic foundations and impact on electronic structure are not established at this point. To study these aspects, ab initio molecular dynamic simulations based on atomic compositions in C implanted titania nanotubes according to elastic recoil detection analysis are employed. Consistent with experimental data, carbon accumulates in chainlike precipitates, which are favorable for enhancing conductivity, as revealed by density-functional theory electronic ground states calculations are demonstrated.

This dissertation is a collection of works that investigate non-prototypical sources leading to new particle formation in the atmosphere. Particles play a major role in atmospheric chemistry. For example, particles are a component of smog and are commonly found in high concentrations under conditions of atmospheric inversions. In order to reconcile the difference between measured and modeled particle concentrations new mechanisms from non-prototypical sources for particle formation need to be determined. Formation of particles has frequently been modeled using classical nucleation theory (CNT). The first step in CNT is the nucleation step where molecular clusters form. In a second step, these clusters grow into particles through coagulation or condensation. First, this research aims to improve the modeling of equilibrium constants for the formation of peroxy radical-water complexes. Failure of the harmonic approximation in the partition function for describing the low frequency vibrational modes of the complexes was explored. Instead the dissociative hydrogen bond mode using a Lennard-Jones 6-3 potential and the other low frequency vibrational modes using one- and two-fold hindered rotors was modeled. It was determined that the contribution of the two-fold hindered rotors is more important than the long-range dipole-dipole potentials and of vibration-rotation coupling. In related work, the hydroperoxy radical was investigated as a non-prototypical source of particles using high level ab initio calculations. The results indicate that the addition of an amine to the dimer increased the overall stability of complex through the increased number and strength of the hydrogen bonds. When compared to prototypical systems, sulfuric acid and methane sulfonic acid, the strength of the complex was found to be similar to the peroxy radical system. Finally, carboxylic acids, formic acid and acetic acid, were investigated as a source for new particle formation using computational and experimental techniques. Using a slow flow reactor cell particle formation was enhanced by the addition of trimethylamine. High level ab initio calculations indicate like the peroxy radicals, carboxylic acids may act as a molecular cluster in particle formation