Fuel cells represent a promising technology for clean power generation because they convert chemical energy (fuel) into electrical energy with high efficiency and low-to-none emission of pollutants. Direct ethanol fuel cells (DEFCs) have several advantages compared to the most studied hydrogen and methanol fuel cells. First and foremost, ethanol is a non-toxic liquid, which lowers the investment of handling facilities because the current infrastructure for gasoline can be largely used. Second, ethanol can be conveniently produced from biomass, hence is carbon neutral which mitigates increasing atmospheric CO2. Last but not least, if completely oxidized to CO2, ethanol has a higher energy density than methanol since it can deliver 12 electrons per molecule. The almost exclusive oxidation to acetic acid overshadows the attractiveness of DEFCs considerably, as the energy density is divided by 3. The standard potential of acetic acid formation indicates that a reaction path including acetic acid, leads to inevitable potential losses of about 0.4 V (difference between ideal potential for CO2 and acetic acid "production"). The development of alkaline DEFCs had also been hampered by the lack of stable and efficient anion exchange membranes. Fortunately, this challenge has been well tackled in recent years,8,9 making the development of alkaline fuel cells (AFCs) which are of particular technological interest due to their simple designs and ability to operate at low temperatures (25-100 °C). In alkaline conditions, the kinetic of both the cathodic oxygen reduction and the anodic ethanol oxidation is facilitated. Furthermore, the expensive Pt catalyst can be replaced by the lower-cost and more active transition metals such as Pd. The main objectives of this project are: i) to provide detailed fundamental understanding of ethanol oxidation reaction on transition metal surfaces in alkaline media, ii) to propose the best rational catalyst design strategies to cleave the C–C bond during ethanol electrooxidation. To achieve these goals two methodologies are used, i.e., in-situ identification of ethanol electrooxidation products using polarization modulation infrared reflection absorption spectroscopy (PM-IRRAS) and mechanistic investigation using computational studies in the framework of density functional theory (DFT). The PM-IRRAS technique was advanced in this project to the level of distinguishing electrooxidation products at the surface of the nanoparticles (electrode) and in the bulk-phase of the electrolyte. This new PM-IRRAS utility makes it possible to detect molecules such as CO2 which desorbs from the catalyst surface as soon as they are formed. The DFT insights in this project, provides an explanation as to why it is difficult to break the C–C bond in ethanol and is used for screening the top candidate metals for further studies.

The focus of this thesis is on C-O bonds activation by transition metal atoms. Lignin is a potential alternative energy resource, but currently is an underused biomass species because of its highly branched structure. To aid in better understanding this species, the oxidative cleavage of the Cβ-O bond in an archetypal arylglycerol β-aryl ether (β–O–4 Linkage) model compound of lignin with late 3d, 4d, and 5d metals was investigated. Methoxyethane was utilized as a model molecule to study the activation of the C-O bond. Binding enthalpies (ΔHb), enthalpy formations (ΔH) and activation enthalpies (ΔH‡) have been studied at 298K to learn the energetic properties in the C-O bond cleavage in methoxyethane. Density functional theory (DFT) has become a common choice for the transition metal containing systems. It is important to select suitable functionals for the target reactions, especially for systems with degeneracies that lead to static correlation effects. A set of 26 density functionals including eight GGA, six meta-GGA, six hybrid-GGA, and six hybrid-meta-GGA were applied in order to investigate the performance of different types of density functionals for transition metal catalyzed C-O bond cleavage. A CR-CCSD(T)/aug-cc-pVTZ was used to calibrate the performance of different density functionals.

abstract: Losses in commercial microwave dielectrics arise from spin excitations in paramagnetic transition metal dopants, at least at reduced temperatures. The magnitude of the loss tangent can be altered by orders of magnitude through the application of an external magnetic field. The goal of this thesis is to produce “smart” dielectrics that can be switched “on” or “off” at small magnetic fields while investigating the influence of transition metal dopants on the dielectric, magnetic, and structural properties. A proof of principle demonstration of a resonator that can switch from a high-Q “on state” to a low-Q “off state” at reduced temperatures is demonstrated in (Al1-xFex)2O3 and La(Al1-xFex)O3. The Fe3+ ions are in a high spin state (S=5/2) and undergo electron paramagnetic resonance absorption transitions that increase the microwave loss of the system. Transitions occur between mJ states with a corresponding change in the angular momentum, J, by ±ħ (i.e., ΔmJ=±1) at small magnetic fields. The paramagnetic ions also have an influence on the dielectric and magnetic properties, which I explore in these systems along with another low loss complex perovskite material, Ca[(Al1-xFex)1/2Nb1/2]O3. I describe what constitutes an optimal microwave loss switchable material induced from EPR transitions and the mechanisms associated with the key properties. As a first step to modeling the properties of high-performance microwave host lattices and ultimately their performance at microwave frequencies, a first-principles approach is used to determine the structural phase stability of various complex perovskites with a range of tolerance factors at 0 K and finite temperatures. By understanding the correct structural phases of these complex perovskites, the temperature coefficient of resonant frequency can be better predicted. A strong understanding of these parameters is expected to open the possibility to produce new types of high-performance switchable filters, time domain MIMO’s, multiplexers, and demultiplexers. / Dissertation/Thesis / Doctoral Dissertation Materials Science and Engineering 2020

京都大学 / 0048 / 新制・課程博士 / 博士(理学) / 甲第21571号 / 理博第4478号 / 新制||理||1642(附属図書館) / 京都大学大学院理学研究科物理学・宇宙物理学専攻 / (主査)准教授 菅沼 秀夫, 教授 永江 知文, 教授 田中 貴浩 / 学位規則第4条第1項該当 / Doctor of Science / Kyoto University / DFAM

In the pursuit of enhancing the electronic properties of transparent p-type semiconductors, this work uses density functional theory to study the effects of doping tin monoxide with nitrogen, antimony, yttrium and lanthanum. An overview of the theoretical concepts and a detailed description of the methods employed are given, including a discussion about the correction scheme for charged defects proposed by Freysoldt and others [Freysoldt 2009]. Analysis of the formation energies of the defects points out that nitrogen substitutes an oxygen atom and does not provide charge carriers. On the other hand, antimony, yttrium, and lanthanum substitute a tin atom and donate n-type carriers. Study of the band structure and density of states indicates that yttrium and lanthanum improves the hole mobility. Present results are in good agreement with available experimental works and help to improve the understanding on how to engineer transparent p-type materials with higher hole mobilities.

Gaseous pollution has become a global issue and its presence above certain limits is hazardous to human health and environment. Detection of such gases is an immediate need and researchers around the world are trying to solve this problem. Metal oxides are being used as sensing materials for a long time, but a high operating temperature limits applications in many areas. On the other hand, two-dimensional (2D) materials with high surface-to-volume ratio and chemical stability are promising candidates in the field of gas sensing. This includes monolayer transition metal dichalcogenides, such as MoS2 and WS2, which are direct band gap materials. While few layer transition metal dichalcogenides are indirect band gap materials, they are easier to synthesize than monolayers. Therefore, it is important to understand whether few layer transition metal dichalcogenides possess the same sensing behavior as the corresponding monolayers. For this reason the first part of this dissertation compares the sensing behavior of monolayer and few layer MoS2 and WS2. Two dimensional hexagonal boron nitride is a highly stable structural analogue of graphene. However, its insulating behavior with large band gap is not suitable for sensing. Recently, monolayer Si2BN has been proposed to exist. As the presence of Si makes this material reactive, the second part of this dissertation addresses its application as sensing material. In the _nal part of this dissertation, in search of a metal free, non-toxic, and earth abundant sensor material, further structural analogues of graphene are considered, namely monolayer C3N, monolayer C3Si, and monolayer C6BN. In particular, different theoretical approaches for studying the sensing performance of materials are compared to each other.

Functional materials are essential to human welfare and to provide foundations for emerging industries. As an alternative route to experimental materials discovery, computational materials designs are playing an increasingly significant role in the whole discovery process. In this work, we use an in-house developed python utility: PAOFLOW, which generates finite basis Hamiltonians from the projection of first principles plane-wave pseudopotential wavefunctions on pseudo atomic orbitals(PAO) for post-process calculation on various properties such as the band structures, density of states, complex dielectric constants, diffusive and anomalous spin and charge transport coefficients. In particular, we calculated the dielectric function of Sr-, Pb-, and Bi-substituted BaSnO3 over wide concentration ranges. Together with some high-throughput experimental study, our result indicates the importance of considering the mixed-valence nature and clustering effects upon substitution of BaSnO3 with Pb and Bi. We also studied two prototype ferroelectric rashba semiconductors, GeTe and SnTe, and found the spin Hall conductivity(SHC) can be large either in ferroelectric or paraelectric structure phase. Upon doping, the polar displacements in GeTe can be sustained up to a critical hole concentration while the tiny distortions in SnTe vanish at a minimal level of doping. Moreover, we investigated the sensitivity of two dimensional group-IV monochalcogenides to external strain and doping, which reveal for the first time giant intrinsic SHC in these materials, providing a new route for the design of highly tunable spintronics devices based on two-dimensional materials.

Orientador: Vivian Vanessa França / Coorientador: Érica Regina Filetti Nascimento / Banca: Rodrigo Fernando Costa Marques / Banca: Sérgio Ricardo Muniz / Resumo: Nesse trabalho propomos o desenvolvimento de redes neurais artificiais capazes de fornecer a energia do estado fundamental do modelo de Hubbard para nanoestruturas fermiônicas interagentes e homogêneas. Uma vez otimizado o funcional via rede neural, este pode ser usado como input em cálculos de funcionais da densidade para sistemas heterogêneos. O modelo neural obtido mostrou um desempenho excelente, com desvios menores que ∼ 0,2%, recuperando todos os regimes de densidade, magnetização e uma vasta extensão de regimes de interação, quando comparado com resultados numéricos exatos. Comparado à funcionais analíticos, o modelo neural é mais preciso em todos os regimes de parâmetros, especialmente no regime de fraca interação, onde o funcional analítico mais recente apresenta um grande desvio: ∼ 7%, contra ∼ 0,1% para o nosso modelo neural. Aplicado em aproximações de densidade local para cálculos de DFT para cadeias finitas e com heterogeneidades, como impurezas localizadas e potenciais confinantes, nosso modelo neural se mostrou uma alternativa confiável e usando apenas uma fração dos recursos computacionais de outros tratamentos numéricos. / Abstract: In this work we propose an artificial neural network model to the ground-state energy of fermionic interacting particles in homogeneous chains described by the Hubbard model. Once the neural network functional is optimized, it can be used as input in density functional calculations for inhomogeneous systems. The neural network model obtained, showed excellent performance, deviating by less than ∼ 0.2%, recovering all regimes of density and magnetization and for a vast range of interactions when compared to exact numerical results. Compared to analytical functionals, the neural network is more accurate in all regimes of parameters, especially at the weakly interacting regime, where the most recent analytical parametrization fails the most: ∼ 7%, while only ∼ 0.1% for our neural network model. When applied in local density approximations for density functionals calculations for finite chains with inhomogeneities, such as localized impurities and confining potentials, our neural model has proven to be a reliable alternative, while using only a fraction of the computational resources from other numerical treatments. / Mestre

Thermoelectric materials can convert waste heat into electric power and thus provide a way to reduce the dependence on fossil fuels. Our aim is to model the underlying materials properties and, in particular, the transport as controlled by electrons and lattice vibrations. The goal is to develop an understanding of the thermoelectric properties of selected materials at a fundamental level. The structural, electronic, optical, and phononic properties are studied in order to tune the transport, focusing on KxRhO2, NaxRhO2, PtSb2 and Bi2Se3. The investigations are based on density functional theory as implemented in the all electron linearized augmented plane wave plus local orbitals WIEN2k and pseudo potential Quantum-ESPRESSO codes. The thermoelectric properties are derived from Boltzmann transport theory under the constant relaxation time approximation, using the BoltzTraP code. We will discuss first the changes in the electronic band structure under variation of the cation concentration in layered KxRhO2 in the 2H phase and NaxRhO2 in the 3R phase. We will also study the hydrated phase. The deformations of the RhO6 octahedra turn out to govern the thermoelectric properties, where the high Seebeck coefficient results from ”pudding mold" bands. We investigate the thermoelectric properties of electron and hole doped PtSb2, which is not a layered material but shares “pudding mold" bands. PtSb2 has a high Seebeck coefficient at room temperature, which increases significantly under As alloying by bandgap opening and reduction of the lattice thermal conductivity. Bi2Se3 (bulk and thin film) has a larger bandgap then the well-known thermoelectric material Bi2Te3, which is important at high temperature. The structural stability, electronic structure, and transport properties of one to six quintuple layers of Bi2Se3 will be discussed. We also address the effect of strain on a single quintuple layer by phonon band structures. We will analyze the electronic and transport properties of Tl-doped Bi2Se3 under strain, focusing on the giant Rashba spin splitting (Tl doping breaks the inversion symmetry in Bi2Se3) and its dependence on biaxial tensile and compressive strain.

Materials that are light weight, low cost and have high hydrogen storage capacity are essential for on-board vehicular applications. Some reversible complex hydrides are alanates and amides but they have lower capacity than the DOE target (6.0 wt %) for 2010. High capacity, light weight, reversibility and fast kinetics at lower temperature are the primary desirable aspects for any type of hydrogen storage material. Borohydride complexes as hydrogen storage materials have recently attracted great interest. Understanding the above parameters for designing efficient complex borohydride materials requires modeling across different length and time scales. A direct method lattice dynamics approach using ab initio force constants is utilized to calculate the phonon dispersion curves. This allows us to establish stability of the crystal structure at finite temperatures. Density functional theory (DFT) is used to calculate electronic properties and the direct method lattice dynamics is used to calculate the finite temperature thermodynamic properties. These computational simulations are applied to understand the crystal structure, nature of bonding in the complex borohydrides and mechanistic studies on doping to improve the kinetics and reversibility, and to improve the hydrogen dynamics to lower the decomposition temperature. A combined theoretical and experimental approach can better lead us to designing a suitable complex material for hydrogen storage. To understand the structural, bulk properties and the role of dopants and their synergistic effects on the dehydrogenation and/or reversible rehydrogenation characteristics, these complex hydrides are also studied experimentally in this work.