Computational simulations in materials for energy applications 1. Crystal and electronic structure in \u3ci\u3eLn\u3c/i\u3e-U-O compounds. 2. Dynamics of point defect interaction with dislocations in bcc iron.

Nuclear energy is a viable solution to the world’s energy demands. Nuclear energy applications involve rich and complex physics, with high energy events, the incorporation of fission products, and the production of point and extended defects. All these phenomena have an impact on the microstructure of the constituent materials and represent efficiency and safety concerns. A mature understanding of the microstructural evolution of the component materials in the nuclear reactor core is essential to have a safe and reliable process. Experimental investigation of materials in radiation environments is difficult and expensive, making computational simulations a suitable alternative. In this dissertation, employ computational methods to study the microstructural evolution of both nuclear fuel and the iron based reactor structural components, and the impact on their material properties. In the nuclear fuel side, we investigate the crystallographic and electronic structure of Ln-U-O compounds that may be formed inside nuclear fuel operational life by the incorporation of lanthanide fission products using density functional theory (DFT). We used a layered atomic model to propose ordered structures and compared their stability to disordered phases. We also employed the atom-in-molecule approach to study the oxidation state of uranium atoms, and the iconicity/covalency of the U-O bonds. In the structural components side, we studied the migration mechanisms of self-interstitial dumbbells and vacancies around single edge or screw dislocations. The actual saddle point energy and configuration as a function of position with respect of the dislocation core was calculated with the self-evolving atomistic kinetic Monte Carlo (SEAKMC) method, and used this data as an input for KMC calculations. This allowed the analysis of the migration paths, the range of interaction of point defects with dislocations, and the preferential absorption of self-interstitial dumbbells over vacancies, known as dislocation bias, which is responsible for swelling in irradiated materials. The understanding of the mechanism responsible for the microstructural changes, and how these changes impact the material properties is a key aspect to be able to develop materials with enhanced radiation resistance, and achieve high performance under extreme conditions that are vital for nuclear energy generation with improved efficiency and safety

Itsediffuusion atomistinen simulointi kuparipinnalla ulkoisen sähkökentän kanssa ja ilman

Surface diffusion is the major process that can drive metal surface modification in temperatures significantly below the melting point. Diffusion is random movement with the tendency toward minimization of the total free energy. In the absence of external forces, the equilibrium shape of the metal surface is determined by the anisotropy of the surface energies in different orientations. At finite temperatures, anisotropy also in the temperature dependence of the surface free energies, together with the temperature and orientation dependent kinetic rates of surface diffusion events, make metal surface morphology a multifaceted phenomenon involving a range of competing effects. Computational modeling of surface diffusion process is thus challenging in itself, but the task is even further complicated if the surface is subject to external factors. One such factor can be an applied electric field, the electrostatic contribution to the free energy of which alters the equilibrium shape. This is hypothesized to be one of the contributors to the development of surface roughening that further develops into field emitting tips. The latter, in turn, are thought to evolve into vacuum arc breakdowns, occurring in many devices operating in high electric fields. In this work, surface diffusion in Cu with and without electric field was studied by kinetic Monte Carlo (KMC) and molecular dynamics (MD). A multitude of encountered obstacles are described, from calculating KMC parameters in the highly heterogeneous surface environments, to the challenge of reaching sufficiently long time scales in MD. The pre-parameterized on-lattice KMC model, chosen for efficiency, was improved by employing machine learning for migration barrier prediction. Better accuracy regarding the stability of small nanostructures on differently oriented surfaces was reached this way, compared to the earlier KMC model. The new model also correctly predicts the relative surface energies in Cu and the fragmentation of crossing nanowires at the junction points. The Cu {110} surface also exhibits a self-roughening instability at elevated temperatures, commonly known to occur in this system both in experiments and MD simulations. For simulations in electric fields, we utilized the coupling of MD to a continuum, finite elements method solver of electric fields and surface charges that was earlier developed in our group. This method enables the imposition of a realistic electric field gradient on the MD system, while keeping the number of dynamically simulated atoms very low for improved efficiency. Furthermore, the MD simulations on the surface orientations with the highest migration energy barriers were accelerated by a metadynamics-based method. As a result, we were able to capture the qualitative trend of biased diffusion toward higher electric fields, with the possibility of extracting surface polarization parameters from the MD results to be directly compared to ab initio calculations.Kovimmatkaan metallipinnat eivät pysy täysin muuttumattomina, sillä absoluuttisen nollapisteen yläpuolella lämpövärähtely aiheuttaa kiinteässäkin aineessa atomien satunnaisliikkettä. Yleisellä tasolla tämä atomien satunnaisliike eli diffuusio pyrkii keskimäärin tekemään pinnoista sileämpiä, jolloin metallin pintajännite on pienimmillään. Jos metallipintaan kuitenkin vaikuttaa jokin ulkoinen voima, kuten esimerkiksi sähkökenttä, pintajännitteen ja ulkoisen voiman yhteenlaskettu vaikutus voi ohjata pinnan kehitystä toiseen suuntaan: esimerkiksi mikroskooppisten pienten piikkien kasvu pinnalla saattaa johtaa tasaista pintaa matalampaan kokonaisenergiaan. Pintadiffuusio on yksi tärkeimmistä mekanismeista, jotka voivat mahdollistaa tällaisten piikkien kasvun. Pinnan muutokset sähkökentän alla ovat olennainen ilmiö monissa tieteellisissä ja teollisissa laitteissa, joissa metalli altistuu erittäin voimakkaille sähkökentille, kuten esimerkiksi hiukkaskiihdyttimissa, lääketieteellisissä säteilylaitteissa ja fuusioreaktoreissa. Eräs tällaisten laitteiden toimintaa haittaava ilmiö ovat valokaaret eli virtapurkaukset metallipintojen välillä. Valokaarien vähentämiseksi on olennaista ymmärtää metallipinnan käyttäytymistä sähkökentän alla; suorien kokeellisten havaintojen tekeminen näissä olosuhteissa on kuitenkin vaikeaa. Tässä väitöskirjassa tutkittiin kupariatomien pintadiffuusiota laskennallisten simulaatiomallien avulla. Pintadiffuusio on jo itsessään haastava tutkimuskohde, joten merkittävä osa työstä kului yleispätevien atomististen diffuusiomallien kehittämiseen. Yhdistelemällä modernia koneoppimista ja vakiintuneita fysiikan simulaatiomenetelmiä saavutettiin parempi tarkkuus monien kuparin pintailmiöiden mallintamisessa. Sähkökentän lisääminen malleihin edellytti tutkimusryhmässämme aiemmin kehitettyjen tekniikoiden lisäksi erityisiä kiihdytysmenetelmiä, jotta pintadiffuusiota pystyttiin simuloimaan riittävän pitkällä aikajänteellä. Tulokset ovat hyvin yhteensopivia teoreettisten ennusteiden kanssa, minkä perusteella kehitettyä mallia voidaan pitää tärkeänä askeleena kohti metallipintojen laajempaa ymmärtämistä

Molybdenum carbide nanoparticle: Understanding the surface properties and reaction mechanism for energy production towards a sustainable future

Rational design and synthesis of cheap, noble metal-free, thermal/hydrothermal stable and active catalyst for efficient hydrogenation and hydrogen production reaction is crucial towards renewable and sustainable energy generation. This gives the use of molybdenum carbide nanoparticle considerable attention as an alternative to noble metals. However, the industrial application is not yet feasible due to insufficient stability and activity coupled with the lack of detailed understanding of the reaction mechanism. This work discusses the effect of the operating parameters on the properties and morphology of molybdenum carbide nanoparticle, as well as their impact on the catalytic activity. Critical issues such as structural diversity, surface properties, and multiscale reaction modeling are also discussed for better understanding of the reaction mechanism. This is a promising strategy towards synthesis of cost-effective and efficient catalysts for renewable and sustainable energy production

Structures, Structural Transfromations and Properties of Selected Elemental and Extended Solids

The current boom in computer power has created avenue to study materials’ properties under extreme thermodynamic conditions where experimental characterization is very challenging. This thesis is an aggregation of several objectives ranging from the study of elemental as well as extended materials for technological, high energy density (HED), and geophysical applications; all at high pressure. The density functional theory (DFT), ab initio metadynamics and ab initio molecular dynamics (AIMD) methods have been employed to analyze structural phase transitions, electronic, vibrational, and mechanical properties of selected materials at high pressure. Where available, high-pressure-high-temperature (HPHT) experiments were combined with the various theoretical methods for complete elucidation of the system. The first set of projects in this thesis involve study of structural phase transition in two elements: carbon (C) and nitrogen (N). The first part presents the results of structural phase transition in a two-dimensional polymeric C60 after being subjected to uniaxial compression at high temperature in a metadynamics simulation. The new structure exhibits a mixed sp2/sp3 hybridization. The structure is stable at ambient condition and exhibits superior mechanical performance than most of widely used hard ceramics. The second part presents theoretical results on the identification, and characterization of single bonded nitrogen in crystal structure isostructural to black phosphorus (BP-N) at 146 GPa and 2200 K. The crystal structure exhibits a unique puckered two-dimensional layer exhibiting exciting physical and chemical phenomena including prospect for high energy density (HED) applications. Synchrotron x-ray diffraction and Raman spectroscopy were used for experimental characterization of the BP-N. First-principles methods were employed in the theoretical characterization. The second set of projects involve the theoretical studies of transition metal (TM) -TM alloys/compounds. The first part of the chapter investigates structural phase transition leading to shape memory loss in the shape memory alloy NiTi. The second part investigates the formation of Au-Fe compounds at high pressure. A detailed analysis of the transition kinetics and dynamical pathway in NiTi using the metadynamics method reveals the possibility of the B19′ phase of NiTi losing its shape memory when subjected to high stress conditions and heated above a critical temperature (Tc) of 700 K. Using the particle swarm-intelligence optimization algorithm interfaced with first principles methods, we predicted the formation of bulk intermetallic compounds of two bulk-immiscible components, Fe and Au. the systems are stabilized by pressure and notable electron transfer. Next, the results of theoretical studies of the formation of noble gas element - TM compound were presented. The identification of a thermodynamically stable compound of Argon (Ar) and nickel (Ni) under thermodynamic conditions representative of the Earth’s core using density functional calculations were presented. The study present evidence of the reactability of Ar with one of the Earth’s core’s main constituents, Ni. The compound of Ar and Ni was identified as ArNi with a L11 Laves structure. It was found that ArNi compound is stabilized by notable electron transfer from Ni to Ar. The final project is an extensive theoretical study of the formation of alkali metal-transition metal intermetallic compounds at high pressure and temperature relevant to the upper mantle and the core of the Earth. These studies were carried out using particle swarm-intelligence optimization and genetic algorithms interfaced with first principles methods. The first part investigates the formation of K-Fe compounds at thermodynamics conditions relevant to the Earth’s interior while the second part investigates the formation of K-Ni compounds in the Earth’s interior. It was found that K and Fe can form intermetallic compounds that are stabilized by high pressure and energy reordering of atomic orbital. Phase transitions were also reported and the instabilities that induce them were also investigated. Furthermore, the study on K-Ni systems identify the crystal structure for the long-sought structure of the only experimentally known K-Ni compound to date. The identified K2Ni exhibits a semiconducting ground state with an indirect bandgap. The results of both studies indicate that the chemical properties of elements can change dramatically under extreme conditions and could have significant implications for understanding the Earth’s interior

Low Temperature Phase Transitions of Gadolinium and Ytterbium Using Resonant Ultrasound Spectroscopy

Low temperature phase transitions in the lanthanides gadolinium (Gd) and ytterbium (Yb) were studied using the nondestructive technique of resonant ultrasound spectroscopy (RUS) coupled with a cryogenic system. Previous studies of these materials utilized a pulse-echo method that is not as robust as RUS. The advantagesof RUS include the ability to study very small samples and the ability to obtain all elastic properties of the sample from a single frequency spectrum. A laboratory system was developed combining RUS with a cryogenic cooling system capable of exploring the temperature range 13 K 340 K. The complex 4-f electronic structure of elemental Gd and Yb leads to continuous magnetic and first-order structural phase transitions within this temperature range. The results of measurements on Gd are consistent with those previously reported in literature, supporting the validity of RUS measurements on small lanthanide samples at low temperature. Three new phenomena are observed in the Yb measurements: a positive slope in resonance frequency versus temperature, hysteresis around a previously reported transition temperature of 315 K that decreases with temperature cycling, and hysteresis at low temperatures with discrete memory characteristics

コロイド結晶の不均質核形成についての研究－核形成プロセスに対する界面自由エネルギーの効果－

Tohoku University宇田聡課

Characterization, modeling, and simulation of multiscale directed-assembly systems

Nanoscience is a rapidly developing field at the nexus of all physical sciences which holds the potential for mankind to gain a new level of control of matter over matter and energy altogether. Directed-assembly is an emerging field within nanoscience in which non-equilibrium system dynamics are controlled to produce scalable, arbitrarily complex and interconnected multi-layered structures with custom chemical, biologically or environmentally-responsive, electronic, or optical properties. We construct mathematical models and interpret data from direct-assembly experiments via application and augmentation of classical and contemporary physics, biology, and chemistry methods. Crystal growth, protein pathway mapping, LASER tweezers optical trapping, and colloid processing are areas of directed-assembly with established experimental techniques. We apply a custom set of characterization, modeling, and simulation techniques to experiments to each of these four areas. Many of these techniques can be applied across several experimental areas within directed-assembly and to systems featuring multiscale system dynamics in general. We pay special attention to mathematical methods for bridging models of system dynamics across scale regimes, as they are particularly applicable and relevant to directed-assembly. We employ massively parallel simulations, enabled by custom software, to establish underlying system dynamics and develop new device production methods

Nanoinformatics

Machine learning; Big data; Atomic resolution characterization; First-principles calculations; Nanomaterials synthesi