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Planar defects such as free surfaces and grain boundaries in metals and alloys play important roles affecting many material properties such as fracture toughness, corrosion resistance, wetting, and catalysis. Their interactions with point defects and solute elements also play critical roles on governing the microstructural evolution and associated property changes in materials. This work seeks to use atomistic modeling to obtain a fundamental understanding of many surface and interface related properties and phenomena, namely: orientation-dependent surface energy of elemental metals and alloys, segregation of solute elements at grain boundaries and their impact on grain boundary cohesive strength, and the controversial sluggish diffusion in both the bulk and grain boundaries of high entropy alloys. First, an analytical formula is derived, which can predict the surface energy of any arbitrary (h k l) crystallographic orientation in both body-centered-cubic (BCC) and face-centered-cubic (FCC) pure metals, using only two or three low-index (e.g., (100), (110), (111)) surface energies as input. This analytical formula is validated against 4357 independent single element surface energies reported in literature or calculated by the present author, and it proves to be highly accurate but easy to use. This formula is then expanded to include the simple-cubic (SC) structure and tested against 4542 surface energies of metallic alloys of different cubic structures, and good agreement is achieved for most cases. Second, the effect of segregation of substitutional solute elements on grain boundary cohesive strength in BCC Fe is studied. It is found that the bulk substitution energy can be used as an effective indicator to predict the embrittlement or strengthening potency induced by the solute segregation at grain boundaries. Third, the controversial vacancy-mediated sluggish diffusion in an equiatomic FeNiCrCoCu FCC high entropy alloy is studied. Many literature studies have postulated that the compositional complexity in high entropy alloys could lead to sluggish diffusion. To test this hypothesis, this work compares the vacancy-mediated self-diffusion in this model high entropy alloy with a hypothetical single-element material (called average-atom material) that has similar average properties as the high entropy alloy but without the compositional complexity. The results show that the self-diffusivities in the two bulk systems are very similar, suggesting that the compositional complexity in the high entropy alloy may not be sufficient to induce sluggish diffusion in bulk high entropy alloys. Based on the knowledge learned from the bulk alloy, the exploration of the possible sluggish diffusion has been extended to grain boundaries, using a similar approach as in the study of self-diffusion in bulk. Interestingly, the results show that sluggish diffusion is evident at a Σ5(210) grain boundary in the high entropy alloy due to the compositional complexity, especially in the low temperature regime, which is different from the bulk diffusion. The underlying mechanisms for the sluggish diffusion at this grain boundary is discussed. / Doctor of Philosophy / Human beings have utilized metals and alloys for over ten millennia and learned much from them. Based on the accumulated knowledge, they have countless applications in our current daily life. However, there is still much to learn for improving our current technology and even opening new opportunities. Throughout most of history, our understanding of these materials was largely obtained through empirical experimentation and refining them into theories and scientific laws. Nowadays, due to the advancements in computer simulations, we can learn more by modeling the behaviors of metals and alloys at the length and time scales that are either be too arduous, costly, or currently impossible experimentally. This work aims at using computer modeling to study some important surface/interface related physical behaviors and properties in metals and alloys at the atomistic scale. First, this work intends to develop a robust surface energy model in an analytical form for any crystallographic orientation. Surface energy is an important material property for many surface-related processes such as fracturing, wetting, sintering, catalysis, and crystalline particle shape. Surface energy is different at different surface orientations, and predicting this difference is important for understanding these surface phenomena. Second, the effect of solute segregation on grain boundary cohesive strength is studied. Most commonly used metallic materials consist of many small crystalline grains and the borders between them are called grain boundaries, which are weak spots for fracture. The minimum energy required to split a boundary is called the grain boundary cohesive strength. The presence of solutes or impurities at grain boundaries can further alter the cohesive strength. A better understanding of this phenomena will eventually help us develop more fracture-resistant materials. The third project deals with the possible sluggish/retarded diffusion in high entropy alloys, which contain five or more principal alloying elements and have many unique mechanical, radiation-resistant, and corrosion-resistant properties. Many researchers attribute these unique properties to the slow species diffusion in these alloys, but its existence is still controversial. This work studies the atomic-level diffusion mechanisms in an FeNiCrCoCu high entropy alloy both in bulk (grain interior) and at grain boundaries in order to determine if sluggish diffusion is present and its causes.

Some aspects of grain boundary segregation (GBS) are discussed. This paper adds two new sprouts. The first is connected with formation of the atomic complexes in boundary region and their effect on grain boundary diffusion (GBD). The second – with a nonhomogeneity of energy distribution between boundary sites.

No / The conformational propensities of amino acids are an amalgamation of sequence effects, environmental effects and underlying intrinsic behavior. Many have attempted to investigate neighboring residue effects to aid in our understanding of protein folding and improve structure prediction efforts, especially with respect to difficult to characterize states, such as disordered or unfolded states. Host-guest peptide series are a useful tool in examining the propensities of the amino acids free from the surrounding protein structure. Here, we compare the distributions of the backbone dihedral angles (φ/ψ) of the 20 proteogenic amino acids in two different sequence contexts using the AAXAA and GGXGG host-guest pentapeptide series. We further examine their intrinsic behaviors across three environmental contexts: water at 298 K, water at 498 K, and 8 M urea at 298 K. The GGXGG systems provide the intrinsic amino acid propensities devoid of any conformational context. The alanine residues in the AAXAA series enforce backbone chirality, thereby providing a model of the intrinsic behavior of amino acids in a protein chain. Our results show modest differences in φ/ψ distributions due to the steric constraints of the Ala side chains, the magnitudes of which are dependent on the denaturing conditions. One of the strongest factors modulating φ/ψ distributions was the protonation of titratable side chains, and the largest differences observed were in the amino acid propensities for the rarely sampled αL region. / NIH

The size effect in the thermo-mechanical behavior of polymeric materials is a critically important phenomenon and has been the subject of many researches in past decades. For example, polystyrene (PS), a widely used polymeric material, is brittle at the bulk state. When the dimensions decreases to the nanoscale, such as PS in nanofibers, their ductility becomes orders higher than their bulk state. In recent years a number of diverse applications, such as scaffolds in tissue engineering, drug delivery devices, as well as soft robotics, are designed by utilizing the unique properties of polymers at nanoscale. However, the inside mechanism of the size dependency in polymeric materials are still not clear yet. In this dissertation, systematic computational and experimental studies are made in order to understand the origins of the size effect for one- and two-dimensional polymeric materials. This framework is also expanded to investigate the size-dependent multi-physics response of functional polymeric materials (shape memory polymers) which are actuated by high-intensity focused ultrasound (HIFU). Our computational studies are based on molecular dynamic (MD) simulations at the atomistic scale, and experimentally-validated finite element models at the bulk level. From bottom-up direction, molecular dynamics can reveal the mechanisms of the size effect in polymers at molecular level, and help predict properties of the bulk materials. In this research, MD simulations are performed to track the origins of the size-effect in the mechanical properties of PE and PS nanofibers. In addition, the size-dependent thermal response of functional polymeric films is also studied at the atomistic scale by utilizing molecular dynamics simulations to predict the thermal properties and actuation mechanisms in these materials when subjected to HIFU fields. From top-down direction, experiments and finite element analysis, are also conducted in this research. An experimentally-validated finite element framework is built to study the mechanical response of shape memory polymers (SMPs) triggered by HIFU. As an external trail towards application fields, a SMP composite with enhanced shape memory ability and also a two-way SMP are synthesized. A smart gripper and also a self-rolling structure are designed by using these SMPs, which approves that these SMPs are good components in designing soft robotics. Finally, The influence of evaporation during fiber forming process is investigated by molecular dynamics simulation. It is found that the formation of the microstructure of polymeric fibers at nanoscale depends on the balance of stretching force and evaporation rate when the fiber is forming. / Doctor of Philosophy / Thermomechanical properties of a thin fiber, a thin film and a cube made of a polymer are significantly different. Although, based on the extensive research that has been performed in recent years our understanding of this size-dependency is advanced to a great degree in the past decades, there are still many unanswered basic questions that can only be addressed by performing computational and experimental investigation at different length scales, from atomistic up to bulk level in polymers. In this research we target exploring some unknown aspects of the size dependency in the thermomechanical properties of polymers by investigating their deformation mechanisms at different length scales. As the first step, we will investigate the mechanical properties of polymeric fibers. For these fibers, the mechanical properties are strongly connected to the fiber's diameter. The prevailing hypothesis is that this size dependency is closely related to the thickness of the surface layer of the nanofibers. Our results show some unknown origins behind the size dependency of the mechanical properties in polyethylene (PE) and polystyrene (PS) nanofibers, which originate from the deformation mechanisms at the atomistic scale. In addition, not just the mechanical properties, the thermal properties and response of functional polymers subjected to an external stimulation are also related to their size. For example, the thermal conductivity of a fiber, a sheet and a cube may be significantly different. Our study shows the thermal responses of different polymers triggered by ultrasound are also different. The size and the type of the polymers will both have influence on the final temperature in the polymeric materials, when the polymeric materials are heated by same ultrasound source. We also have applied our computational and experimental frameworks to investigate this phenomenon. In addition, we also used a new shape memory polymer composite and a two-way shape memory polymer on designing soft robotics-like structures. Overall this research indicates that both mechanical response and thermal responses of polymers are highly related to their dimension. Taking advantage of these unique size effects, and by tailoring this property, diverse devices can be made for being used in a broad range of applications.

The depletion of conventional oil reservoirs forced companies and consequently researchers to pursue alternatives such as resources that in the past were considered not economically viable, in consequence of the high depth, low porosity and permeability of the play zone. The exploration challenges were overcome mainly by the development of horizontal drilling and hydraulic fracturing. However, the extremely high temperatures and pressures, in association to a complex nanopore structure, in which reservoir fluids are now encountered, instigate further investigation of fluid phase behavior and composition, and challenge conventional macroscale reservoir simulation predictions. Moreover, the unusual high temperatures and pressures have increased the cost as well as the hazardous level for reservoir analyzes by lab experiments. Molecular Dynamics (MD) simulation of reservoirs can be a safe and inexpensive alternative tool to replicate reservoir pore and fluid conditions, as well as to monitor fluid behavior. In this study, a MD simulation of nanoconfinement effect on hydrocarbon fluid phase and compositional behavior in organic shale rocks is presented. Chapter 1 reviews and discusses previous works on MD simulations of geological resources. With the knowledge acquired, a fully atomistic squared graphite pore is proposed and applied to study hydrocarbon fluid phase and compositional behavior in organic shale rocks in Chapter 2. Results demonstrate that nano-confinement increases fluid mass density, which can contribute to phase transition, and heptane composition inside studied pores. The higher fluid density results in an alteration of oil in place (OIP) prediction by reservoir simulations, when nano-confinement effect is not considered. / Master of Science / Petroleum sub products are present in the day to day life of almost any human. The list include gasoline, plastics, perfumes, medications, polyester for clothing. Petroleum is naturally encountered in the void space, known as pores, inside rocks at reservoirs thousands of feet underground. In the past, the pores of oil reservoirs in development were larger and interconnected, which facilitates its extraction and reserve predictions. Most of reservoirs being developed nowadays have pores in the nanoscale and with poor interconnection as well as higher reservoir temperatures and pressure. These "new conditions", instigates further investigation of fluid phase behavior and composition, and challenge macroscale reservoir simulation predictions. In this study, the effect of decrease in pore size, as well as higher temperature and pressure conditions, in fluid behavior and composition is studied. Chapter 1 reviews and discusses previous works on geological resources modeling and simulation. With the knowledge acquired, a fully squared shale pore is proposed and applied to study hydrocarbon fluid phase and compositional behavior in organic shale rocks in Chapter 2. Results demonstrate that pores in the nanoscale region tend to increase fluid mass density, which can contribute to phase transition, and heptane composition inside studied pores. The higher fluid density results in an underestimation of reserves prediction by reservoir simulations, when the change in density is not considered.

京都大学 / 新制・課程博士 / 博士(工学) / 甲第25301号 / 工博第5260号 / 新制||工||2001(附属図書館) / 京都大学大学院工学研究科物質エネルギー化学専攻 / (主査)教授 作花 哲夫, 教授 安部 武志, 教授 佐藤 啓文 / 学位規則第4条第1項該当 / Doctor of Agricultural Science / Kyoto University / DGAM