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At least 1,009 records · Page 56

Parallel simulation via SPPARKS of on-lattice kinetic and Metropolis Monte Carlo models for materials processing

Abstract SPPARKS is an open-source parallel simulation code for developing and running various kinds of on-lattice Monte Carlo models at the atomic or meso scales. It can be used to study the properties of solid-state materials as well as model their dynamic evolution during processing. The modular nature of the code allows new models and diagnostic computations to be added without modification to its core functionality, including its parallel algorithms. A variety of models for microstructural evolution (grain growth), solid-state diffusion, thin film deposition, and additive manufacturing (AM) processes are included in the code. SPPARKS can also be used to implement grid-based algorithms such as phase field or cellular automata models, to run either in tandem with a Monte Carlo method or independently. For very large systems such as AM applications, the Stitch I/O library is included, which enables only a small portion of a huge system to be resident in memory. In this paper we describe SPPARKS and its parallel algorithms and performance, explain how new Monte Carlo models can be added, and highlight a variety of applications which have been developed within the code.

36 MATERIALS SCIENCE↗

The solvent component of macromolecular crystals

On average, the mother liquor or solvent and its constituents occupy about 50% of a macromolecular crystal. Ordered as well as disordered solvent components need to be accurately accounted for in modelling and refinement, often with considerable complexity. The mother liquor from which a biomolecular crystal is grown will contain water, buffer molecules, native ligands and cofactors, crystallization precipitants and additives, various metal ions, and often small-molecule ligands or inhibitors. On average, about half the volume of a biomolecular crystal consists of this mother liquor, whose components form the disordered bulk solvent. Its scattering contributions can be exploited in initial phasing and must be included in crystal structure refinement as a bulk-solvent model. Concomitantly, distinct electron density originating from ordered solvent components must be correctly identified and represented as part of the atomic crystal structure model. Herein, are reviewed (i) probabilistic bulk-solvent content estimates, (ii) the use of bulk-solvent density modification in phase improvement, (iii) bulk-solvent models and refinement of bulk-solvent contributions and (iv) modelling and validation of ordered solvent constituents. A brief summary is provided of current tools for bulk-solvent analysis and refinement, as well as of modelling, refinement and analysis of ordered solvent components, including small-molecule ligands.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Fuels and Combustion Technology for Advanced Aircraft Engines [Les Propergols et les Systèmes de Combustion pour les Moteurs d'Aéronefs]

The Conference Proceedings contains the 38 papers presented at the Propulsion and Energetics Panel 81st Symposium on "Fuels and Combustion Technology for Advanced Aircraft Engines" which was held from 10th-14th May 1993, in Fiuggi, Italy. The Technical Evaluation Report and the Keynote Address are included at the beginning, and discussions follow most papers. The Symposium was arranged in the following Sessions: Technology Overview Papers (2); Modelling: Pollutant Formation (4); Modelling: Combustor Design (5); High Temperature Fuels and Fuel Systems (6); Combustion Research: Performance (6); Combustion Research: Emissions (5); Fuel Atomization: Diagnostics and Modelling (5); and Combustion Research: Flowfleld and Mixing (4). The last paper is a contribution from Russia not allocated to a session. New technologies for low NOx combustors and advanced high-pressure/high temperature cycle engines result in unique problems in design and performance. There have been significant advances in modelling and diagnostics to aid the development of these technologies. The purpose of the Symposium was to bring together experts from industry, research establishments and universities to discuss fundamental and applied research in these areas as relevant to the development of advanced gas turbine engines, to exchange practical experience and to discuss the state of the art.

Fuels for aircraft↗

Fourier series of atomic radial distribution functions: A molecular fingerprint for machine learning models of quantum chemical properties

Here we introduce a fingerprint representation of molecules based on a Fourier series of atomic radial distribution functions. This fingerprint is unique (except for chirality), continuous, and differentiable with respect to atomic coordinates and nuclear charges. It is invariant with respect to translation, rotation, and nuclear permutation, and requires no preconceived knowledge about chemical bonding, topology, or electronic orbitals. As such, it meets many important criteria for a good molecular representation, suggesting its usefulness for machine learning models of molecular properties trained across chemical compound space. To assess the performance of this new descriptor, we have trained machine learning models of molecular enthalpies of atomization for training sets with up to 10 k organic molecules, drawn at random from a published set of 134 k organic molecules with an average atomization enthalpy of over 1770 kcal/mol. We validate the descriptor on all remaining molecules of the 134 k set. For a training set of 10 k molecules, the fingerprint descriptor achieves a mean absolute error of 8.0 kcal/mol. This is slightly worse than the performance attained using the Coulomb matrix, another popular alternative, reaching 6.2 kcal/mol for the same training and test sets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Computer-aided design of polymers and composites

This book on computer-aided design of polymers and composites introduces and discusses the subject from the viewpoint of atomic and molecular models. Thus, the origins of stiffness, strength, extensibility, and fracture toughness in composite materials can be analyzed directly in terms of chemical composition and molecular structure. Aspects of polymer composite reliability are considered along with characterization techniques for composite reliability, relations between atomic and molecular properties, computer aided design and manufacture, polymer CAD/CAM models, and composite CAD/CAM models. Attention is given to multiphase structural adhesives, fibrous composite reliability, metal joint reliability, polymer physical states and transitions, chemical quality assurance, processability testing, cure monitoring and management, nondestructive evaluation (NDE), surface NDE, elementary properties, ionic-covalent bonding, molecular analysis, acid-base interactions, the manufacturing science, and peel mechanics.

Kaelble, D. H.↗

Simulation of the Atomic and Electronic Structure of Oxygen Vacancies and Polyvacancies in ZrO{sub 2}

Cubic, tetragonal, and monoclinic phases of zirconium oxide with oxygen vacancies and polyvacancies are studied by quantum chemical modeling of the atomic and electronic structure. It is demonstrated that an oxygen vacancy in ZrO{sub 2} may act as both an electron trap and a hole one. An electron added to the ZrO{sub 2} structure with an oxygen vacancy is distributed between two neighboring Zr atoms and is a bonding orbital by nature. It is advantageous for each subsequent O vacancy to form close to the already existing ones; notably, one Zr atom has no more than two removed O atoms related to it. Defect levels from oxygen polyvacancies are distributed in the bandgap with preferential localization in the vicinity of the oxygen monovacancy level.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Outer satellite atmospheres: Their nature and planetary interactions

Significant progress is reported in early modeling analysis of observed sodium cloud images with our new model which includes the oscillating Io plasma torus ionization sink. Both the general w-D morphology of the region B cloud as well as the large spatial gradient seen between the region A and B clouds are found to be consistent with an isotropic flux of sodium atoms from Io. Model analysis of the spatially extended high velocity directional features provided substantial evidence for a magnetospheric wind driven gas escape mechanism from Io. In our efforts to define the source(s) of hydrogen atoms in the Saturn system, major steps were taken in order to understand the role of Titan. We have completed the comparison of the Voyager UVS data with previous Titan model results, as well as the update of the old model computer code to handle the spatially varying ionization sink for H atoms.

Smyth, W. H.↗

Gaussian approximation potential for amorphous Si : H

Hydrogenation of amorphous silicon (a–Si : H) is critical for reducing defect densities, passivating midgap states and surfaces, and improving photoconductivity in silicon-based electro-optical devices. Modeling the atomic-scale structure of this material is critical to understanding these processes, which in turn is needed to describe c–Si/a–Si : H heterojunctions that are at the heart of modern solar cells with world-record efficiency. Density functional theory (DFT) studies achieve the required high accuracy but are limited to moderate system sizes of 100 atoms or so by their high computational cost. Simulations of amorphous materials have been hindered by this high cost because large structural models are required to capture the medium-range order that is characteristic of such materials. Empirical potential models are much faster, but their accuracy is not sufficient to correctly describe the frustrated local structure. Data-driven, machine-learned interatomic potentials have broken this impasse and have been highly successful in describing a variety of amorphous materials in their elemental phase. Here, we extend the Gaussian approximation potential (GAP) for silicon by incorporating the interaction with hydrogen, thereby significantly improving the degree of realism with which amorphous silicon can be modeled. We show that our Si : H GAP enables the simulation of hydrogenated silicon with an accuracy very close to DFT but with computational expense and run times reduced by several orders of magnitude for large structures. Here, we demonstrate the capabilities of the Si : H GAP by creating models of hydrogenated liquid and amorphous silicon and showing that their energies, forces, and stresses are in excellent agreement with DFT results, and their structure as captured by bond and angle distributions are in agreement with both DFT and experiments.

36 MATERIALS SCIENCE↗

ADVANCING TURBULENT SPRAY AND COMBUSTION MODELS FOR COMPRESSION IGNITION ENGINE SIMULATIONS

This thesis seeks to investigate the turbulent mixing influence on spray atomization and combustion processes encountered in compression ignition diesel engines. Despite greater thermal efficiency of diesel engine than spark ignition engine, the nature of stratified air-fuel mixture and non-premixed flame gives rise to unacceptable levels of nitrogen oxides (NOx) and particulate matter (PM), thus the use of diesel engines has often been limited to heavy-duty vehicle and industrial power sources. However, recent advancement in diesel engine combustion strategies, e.g. low temperature combustion (LTC), has demonstrated promising pathways towards improvement in the engine-out pollutants. Therefore, particularly in the effort of computer-aided engine design tasks, such a new engine design concept requires more accurate modeling techniques applicable over a broader range of engine operating conditions than those of conventional engine strategies. In the notion of challenges in new engine operating conditions, this thesis aims to present successful implementation of improvement in numerical modeling techniques in high-pressure spray atomization and resulting turbulent spray flame of interest. Three-dimensional Computational Fluid Dynamics (CFD) in in-cylinder turbulent combustion is considered an integral part of engine design progress, but rather a cost-prohibitive to apply over a broad range of engine relevant conditions. In spite of successful use of existing spray atomization modeling, prior researchers have pointed out some degree of failure in LTC targeted injection strategies. Furthermore, finite rate and strong nonlinearity of chemistry influenced by local turbulent mixing still remain in challenges to account for in cost-efficient CFD analysis. In this context, a new attempt of hybrid spray primary breakup modeling is presented and demonstrated in successful application aimed at LTC technique. In addition, the Representative Interactive Flamelets (RIF) model with aid of multi-flamelets approach is extensively assessed in terms of predictive capability against classical combustion model. The combustion model employed in this study are fully examined in the general diesel combustion metric, e.g., ignition delay and flame lift-off length as well as newly suggested test metric, combustion recession. The combustion recession has been recently idenfied, but still remain largely unknown. Since the governing physics of this phenomenon is characterized by turbulent mixing coupled with finite rate chemistry, this can be considered as a relevant test metric for turbulent combustion models. In addition, very recent experimental studies have introduced a new non-sooting diesel combustion technique by manipulating direct injection method. The ducted fuel injection (DFI) has thus been demonstrated with its potential of low soot emissions. Knowing that the duct equipped ahead of injector nozzle was identifed to enhance turbulent mixing, investigations of DFI combustion may prove the effectiveness of turbulece-chemistry interaction modeling. This thesis presents comprehensive understandings of aformentioned diesel combustion techniques in terms of several important physics keywords, e.g., turbulent mixing and detailed chemistry.

33 ADVANCED PROPULSION SYSTEMS↗

Energy-efficient, Large-scale Molecular Dynamics Simulations via Hardware- and Algorithm-level Optimization

This work aims to develop a framework for energy-efficient computing that will enable molecular dynamics (MD) simulations of large-scale phenomena with atomic precision and simultaneously remove computational bottlenecks limiting the speed of MD simulations. We seek to implement such an approach through the development of surrogate models for the interatomic force calculation combined with the use of mixed numerical precision formats. For a model system of neutral atoms (only pairwise interactions), significant force calculation efficiency improvements were achieved, without detrimental effects on atomic structures or average energies, using single precision, by developing a surrogate model (deep neural network), and by quantizing this surrogate model. For a model system of charged atoms, the reciprocal-space calculation of electrostatic interactions was identified as the main bottleneck, and the development of a surrogate model should be pursued to achieve an estimated one-order-of-magnitude additional speedup.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Thermal nonequilibrium in partially ionized atomic oxygen

A stationary, nonlinear collisional-radiative model for high-temperature atomic oxygen is presented. Populations of electrons, ions, and excited atoms and intensities of spectral, continuum, and dielectronic recombination lines are calculated in a wide range of conditions. Transport of radiation is included by coupling the rate equations for production of the electrons, ions, and excited atoms with the concept of the escape factors that are not constant but dependent upon plasma conditions. The calculated total continuum emission is in good agreement with existing measurements.

Soon, W. H.↗

High fidelity modeling of thermal relaxation and dissociation of oxygen

A master equation study of vibrational relaxation and dissociation of oxygen is conducted using state-specific O{sub 2}–O transition rates, generated by extensive trajectory simulations. Both O{sub 2}–O and O{sub 2}–O{sub 2} collisions are concurrently simulated in the evolving nonequilibrium gas system under constant heat bath conditions. The forced harmonic oscillator model is incorporated to simulate the state-to-state relaxation of oxygen in O{sub 2}–O{sub 2} collisions. The system of master equations is solved to simulate heating and cooling flows. The present study demonstrates the importance of atom-diatom collisions due to the extremely efficient energy randomization in the intermediate O{sub 3} complex. It is shown that the presence of atomic oxygen has a significant impact on vibrational relaxation time at temperatures observed in hypersonic flow. The population of highly-excited O{sub 2} vibrational states is affected by the amount of atomic oxygen when modeling the relaxation under constant heat bath conditions. A model of coupled state-to-state vibrational relaxation and dissociation of oxygen is also discussed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Atomic Mechanisms for the Si Atom Dynamics in Graphene: Chemical Transformations at the Edge and in the Bulk

The dynamic behavior of e-beam irradiated Si atoms in the bulk and at the edges of single-layer graphene is examined using scanning transmission electron microscopy (STEM). A deep learning network is used to convert experimental STEM movies into coordinates of individual Si and carbon atoms. A Gaussian mixture model is further used to establish the elementary atomic configurations of the Si atoms, defining the bonding geometries and chemical species and accounting for the discrete rotational symmetry of the host lattice. The frequencies and Markov transition probabilities between these states are determined. This analysis enables insight into the defect populations and chemical transformation networks from the atomically resolved STEM data. Here, a clear tendency is observed for the formation of a 1D Si crystal along zigzag direction of graphene edges and for the Si impurity coupling to topological defects in bulk graphene.

36 MATERIALS SCIENCE↗

General multi-group macroscopic modeling for thermo-chemical non-equilibrium gas mixtures

This paper opens a new door to macroscopic modeling for thermal and chemical non-equilibrium. In a game-changing approach, we discard conventional theories and practices stemming from the separation of internal energy modes and the Landau-Teller relaxation equation. Instead, we solve the fundamental microscopic equations in their moment forms but seek only optimum representations for the microscopic state distribution function that provides converged and time accurate solutions for certain macroscopic quantities at all times. The modeling makes no ad hoc assumptions or simplifications at the microscopic level and includes all possible collisional and radiative processes; it therefore retains all non-equilibrium fluid physics. We formulate the thermal and chemical non-equilibrium macroscopic equations and rate coefficients in a coupled and unified fashion for gases undergoing completely general transitions. All collisional partners can have internal structures and can change their internal energy states after transitions. The model is based on the reconstruction of the state distribution function. The internal energy space is subdivided into multiple groups in order to better describe non-equilibrium state distributions. The logarithm of the distribution function in each group is expressed as a power series in internal energy based on the maximum entropy principle. The method of weighted residuals is applied to the microscopic equations to obtain macroscopic moment equations and rate coefficients succinctly to any order. The model’s accuracy depends only on the assumed expression of the state distribution function and the number of groups used and can be self-checked for accuracy and convergence. We show that the macroscopic internal energy transfer, similar to mass and momentum transfers, occurs through nonlinear collisional processes and is not a simple relaxation process described by, e.g., the Landau-Teller equation. Unlike the classical vibrational energy relaxation model, which can only be applied to molecules, the new model is applicable to atoms, molecules, ions, and their mixtures. Numerical examples and model validations are carried out with two gas mixtures using the maximum entropy linear model: one mixture consists of nitrogen molecules undergoing internal excitation and dissociation and the other consists of nitrogen atoms undergoing internal excitation and ionization. Results show that the original hundreds to thousands of microscopic equations can be reduced to two macroscopic equations with almost perfect agreement for the total number density and total internal energy using only one or two groups. We also obtain good prediction of the microscopic state populations using 5-10 groups in the macroscopic equations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

First‐principles study in an inter‐granular glassy film model of silicon nitride

Abstract Based on a previously constructed intergranular glassy film ( IGF ) model for bulk silicon nitride, a large periodic model of 3864 atoms containing 2 grains of different orientations from the main bulk β‐Si 3 N 4 and 2 IGF s was fully relaxed using the ab initio density‐functional theory package VASP . The relaxed structure was then used to calculate the electronic structure, density of states, interatomic bonding, partial charge distribution, and electron localization using the OLCAO method. Analysis of the data focuses on the interfacial regions between bulk β‐Si 3 N 4 and the Si‐O‐N glass layer with different orientations. The total bond order density ( TBOD ) is evaluated in different interfacial and bulk regions. We show minor differences in the internal cohesion between crystalline grains of different facets. However, the overall charges in the bulk crystal grains and in the glassy regions are electropositive which are balanced by the negatively charged interfacial region between the two. The presence of a less rigid glassy layer is the reason for structural flexibility in ceramics without a huge penalty in the steric energy. The optimization of the interfacial structure and bonding via the creation of defective sites is the atomic origin for the existence of the IGF in silicon nitride. The insights obtained from this detailed quantum mechanical analysis of a realistic IGF model are discussed including implications on the strength, fracture toughness, and processing methods. We also discuss the potential applications of our method to other complex materials systems.

Ching, Wai‐Yim↗

On the Extended Holstein–Hubbard Model for Epitaxial Graphene on Metal

A model that combines the extended Hubbard model involving intra-atomic and interatomic Coulomb repulsion and the Holstein model describing the interaction of a band electron with an Einstein phonon is proposed. Three regions of the phase diagram are considered. The regions correspond to the states of spin- and charge-density waves and the state uniform in spin and charge. Numerical estimations for the Rh, Ir, and Pt substrates show that Coulomb interaction plays a leading part, making possible transitions from the uniform state to the states of spin- and charge-density waves.

36 MATERIALS SCIENCE↗

Physics-assisted Latent Space Dynamics Learning for Stiff Collisional-radiative Models

Collisional-radiative (CR) models describe the atomic processes in a plasma by tracking the population density in the ground and excited states for each charge state of the atom/ion. These models predict important plasma properties such as charge state distributions and radiative emissivity and opacity. Accurate descriptions of the CR balance of the plasma are essential in fusion whole device modeling, especially when significant impurities are introduced into the plasmas. In an integrated fusion plasma and CR simulation, a CR model, which is a high-dimensional stiff ODE, needs to be solved on each grid point in the configuration space, and can overwhelm the overall computational cost. In this work, we propose a machine-learning-based method that discovers a latent space and learns its corresponding latent dynamics, which can capture the essential physics to make accurate predictions at much lower online computational cost. The proposed approach is physics-assisted, due to its combination of a physical latent space and a data-driven latent space. It has been demonstrated that the proposed architecture can predict both the full-order CR dynamics and a physical quantity of interest accurately.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗