Publications

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For the purposes of making reliable first-principles predictions of defect energies in semiconductors, it is crucial to distinguish between effective-mass-like defects, which cannot be treated accurately with existing supercell methods, and deep defects, for which density functional theory calculations can yield reliable predictions of defect energy levels. The gallium antisite defect GaAs is often associated with the 78/203 meV shallow double acceptor in Ga-rich gallium arsenide. Within a conceptual framework of level patterns, analyses of structure and spin stabilization can be used within a supercell approach to distinguish localized deep defect states from shallow acceptors such as BAs. This systematic approach determines that the gallium antisite supercell results has signatures inconsistent with an effective mass state and cannot be the 78/203 shallow double acceptor. The properties of the Ga antisite in GaAs are described, total energy calculations that explicitly map onto asymptotic discrete localized bulk states predict that the Ga antisite is a deep double acceptor and has at least one deep donor state.

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First-principles calculations are used to characterize the bulk elastic properties of cubic and tetragonal phase metal dihydrides, MH2 {M = Sc, Y, Ti, Zr, Hf, lanthanides} to gain insight into the mechanical properties that govern the aging behavior of rare-earth di-tritides as the constituent 3H, tritium, decays into 3He. As tritium decays, helium is inserted in the lattice, the helium migrates and collects into bubbles, that then can ultimately create sufficient internal pressure to rupture the material. The elastic properties of the materials are needed to construct effective mesoscale models of the process of bubble growth and fracture. Dihydrides of the scandium column and most of the rareearths crystalize into a cubic phase, while dihydrides from the next column, Ti, Zr, and Hf, distort instead into the tetragonal phase, indicating incipient instabilities in the phase and potentially significant changes in elastic properties. We report the computed elastic properties of these dihydrides, and also investigate the off-stoichiometric phases as He or vacancies accumulate. As helium builds up in the cubic phase, the shear moduli greatly soften, converting to the tetragonal phase. Conversely, the tetragonal phases convert very quickly to cubic with the removal of H from the lattice, while the cubic phases show little change with removal of H. The source and magnitude of the numerical and physical uncertainties in the modeling are analyzed and quantified to establish the level of confidence that can be placed in the computational results, and this quantified confidence is used to justify using the results to augment and even supplant experimental measurements.

Carbon nanostructures, such as nanotubes and graphene, are of considerable interest due to their unique mechanical and electrical properties. The materials exhibit extremely high strength and conductivity when defects created during synthesis are minimized. Atomistic modeling is one technique for high resolution studies of defect formation and mitigation. To enable simulations of the mechanical behavior and growth mechanisms of C nanostructures, a high-fidelity analytical bond-order potential for the C is needed. To generate inputs for developing such a potential, we performed quantum mechanical calculations of various C structures.

In this project we developed t he atomistic models needed to predict how graphene grows when carbon is deposited on metal and semiconductor surfaces. We first calculated energies of many carbon configurations using first principles electronic structure calculations and then used these energies to construct an empirical bond order potentials that enable s comprehensive molecular dynamics simulation of growth. We validated our approach by comparing our predictions to experiments of graphene growth on Ir, Cu and Ge. The robustness of ou r understanding of graphene growth will enable high quality graphene to be grown on novel substrates which will expand the number of potential types of graphene electronic devices.

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This Report characterizes the defects in the defect reaction network in silicon-doped, n-type InAs predicted with first principles density functional theory. The reaction network is deduced by following exothermic defect reactions starting with the initially mobile interstitial defects reacting with common displacement damage defects in Si-doped InAs, until culminating in immobile reaction products. The defect reactions and reaction energies are tabulated, along with the properties of all the silicon-related defects in the reaction network. This Report serves to extend the results for the properties of intrinsic defects in bulk InAs as collated in SAND 2013 - 2477: ''Simple intrinsic defects in InAs : numerical predictions'' to include Si-containing simple defects likely to be present in a radiation-induced defect reaction sequence.

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This report summarizes the result of LDRD project 12-0395, titled "Automated Algorithms for Quantum-level Accuracy in Atomistic Simulations." During the course of this LDRD, we have developed an interatomic potential for solids and liquids called Spectral Neighbor Analysis Poten- tial (SNAP). The SNAP potential has a very general form and uses machine-learning techniques to reproduce the energies, forces, and stress tensors of a large set of small configurations of atoms, which are obtained using high-accuracy quantum electronic structure (QM) calculations. The local environment of each atom is characterized by a set of bispectrum components of the local neighbor density projected on to a basis of hyperspherical harmonics in four dimensions. The SNAP coef- ficients are determined using weighted least-squares linear regression against the full QM training set. This allows the SNAP potential to be fit in a robust, automated manner to large QM data sets using many bispectrum components. The calculation of the bispectrum components and the SNAP potential are implemented in the LAMMPS parallel molecular dynamics code. Global optimization methods in the DAKOTA software package are used to seek out good choices of hyperparameters that define the overall structure of the SNAP potential. FitSnap.py, a Python-based software pack- age interfacing to both LAMMPS and DAKOTA is used to formulate the linear regression problem, solve it, and analyze the accuracy of the resultant SNAP potential. We describe a SNAP potential for tantalum that accurately reproduces a variety of solid and liquid properties. Most significantly, in contrast to existing tantalum potentials, SNAP correctly predicts the Peierls barrier for screw dislocation motion. We also present results from SNAP potentials generated for indium phosphide (InP) and silica (SiO 2 ). We describe efficient algorithms for calculating SNAP forces and energies in molecular dynamics simulations using massively parallel computers and advanced processor ar- chitectures. Finally, we briefly describe the MSM method for efficient calculation of electrostatic interactions on massively parallel computers.

This report documents the development, demonstration and validation of a mesoscale, microstructural evolution model for simulation of zirconium hydride {delta}-ZrH{sub 1.5} precipitation in the cladding of used nuclear fuels that may occur during long-term dry storage. While the Zr-based claddings are manufactured free of any hydrogen, they absorb hydrogen during service, in the reactor by a process commonly termed ‘hydrogen pick-up’. The precipitation and growth of zirconium hydrides during dry storage is one of the most likely fuel rod integrity failure mechanisms either by embrittlement or delayed hydride cracking of the cladding. While the phenomenon is well documented and identified as a potential key failure mechanism during long-term dry storage (NUREG/CR-7116), the ability to actually predict the formation of hydrides is poor. The model being documented in this work is a computational capability for the prediction of hydride formation in different claddings of used nuclear fuels. This work supports the Used Fuel Disposition Research and Development Campaign in assessing the structural engineering performance of the cladding during and after long-term dry storage. This document demonstrates a basic hydride precipitation model that is built on a recently developed hybrid Potts-phase field model that combines elements of Potts-Monte Carlo and the phase-field models. The model capabilities are demonstrated along with the incorporation of the starting microstructure, thermodynamics of the Zr-H system and the hydride formation mechanism.

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This Report characterizes the defects in the defect reaction network in silicon-doped, n-type InP deduced from first principles density functional theory. The reaction network is deduced by following exothermic defect reactions starting with the initially mobile interstitial defects reacting with common displacement damage defects in Si-doped InP until culminating in immobile reaction products. The defect reactions and reaction energies are tabulated, along with the properties of all the silicon-related defects in the reaction network. This Report serves to extend the results for intrinsic defects in SAND 2012-3313: %E2%80%9CSimple intrinsic defects in InP: Numerical predictions%E2%80%9D to include Si-containing simple defects likely to be present in a radiation-induced defect reaction sequence.

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In an effort to build a stronger microscopic foundation for radiation damage models in gallium arsenide (GaAs), the electronic properties of radiation-induced damage clusters are studied with atomistic simulations. Molecular dynamics simulations are used to access the time and length scales required for direct simulation of a collision cascade, and density functional theory simulations are used to calculate the electronic properties of isolated damaged clusters that are extracted from these cascades. To study the physical properties of clusters, we analyze the statistics of a randomly generated ensemble of damage clusters because no single cluster adequately represents this class of defects. The electronic properties of damage clusters are accurately described by a classical model of the electrical charging of a semiconducting sphere embedded in a uniform dielectric. The effective band gap of the cluster depends on the degree of internal structural damage, and the gap closes to form a metal in the high-damage limit. We estimate the Fermi level of this metallic state, which corresponds to high-energy amorphous GaAs, to be 0.46 ± 0.07 eV above the valence band edge of crystalline GaAs. © 2013 American Institute of Physics.

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This Report presents numerical tables summarizing properties of intrinsic defects in indium arsenide, InAs, as computed by density functional theory using semi-local density functionals, intended for use as reference tables for a defect physics package in device models.

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This Report characterizes the defect reaction network in carbon doped, p-type GaAs deduced from first principles density functional theory. The reaction network is deduced by following exothermic defect reactions starting with the initially mobile interstitial defects reacting with common displacement damage defects in C-doped GaAs until culminating in immobile reaction products. The defect reactions and reaction energies are tabulated, along with the properties of all the carbon-related defects in the reaction network. This Report serves to extend the results for intrinsic defects in: P.A. Schultz and O.A. von Lilienfeld, “Simple intrinsic defects in GaAs”, Modelling Simul. Mater. Sci Eng., Vol. 17, 084007 (2009) and its numerical supplement in SAND 2012-2675, and the preliminary carbon defect network results in: P.A. Schultz, “First-principles defect chemistry for modeling irradiated GaAs and III-V semiconductors”, J. Rad. Effects, Res. and Eng. Vol. 30, p257 (2012).

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This Report presents numerical tables summarizing properties of intrinsic defects in gallium arsenide, GaAs, as computed by density functional theory. This Report serves as a numerical supplement to the results published in: P.A. Schultz and O.A. von Lilienfeld, 'Simple intrinsic defects in GaAs', Modelling Simul. Mater. Sci Eng., Vol. 17, 084007 (2009), and intended for use as reference tables for a defect physics package in device models. The numerical results for density functional theory calculations of properties of simple intrinsic defects in gallium arsenide are presented.

This Report presents numerical tables summarizing properties of intrinsic defects in aluminum arsenide, AlAs, as computed by density functional theory. This Report serves as a numerical supplement to the results published in: P.A. Schultz, 'First principles predictions of intrinsic defects in Aluminum Arsenide, AlAs', Materials Research Society Symposia Proceedings 1370 (2011; SAND2011-2436C), and intended for use as reference tables for a defect physics package in device models.

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The structures, energies, and energy levels of a comprehensive set of simple intrinsic point defects in aluminum arsenide are predicted using density functional theory (DFT). The calculations incorporate explicit and rigorous treatment of charged supercell boundary conditions. The predicted defect energy levels, computed as total energy differences, do not suffer from the DFT band gap problem, spanning the experimental gap despite the Kohn-Sham eigenvalue gap being much smaller than experiment. Defects in AlAs exhibit a surprising complexity - with a greater range of charge states, bistabilities, and multiple negative-U systems - that would be impossible to resolve with experiment alone. The simulation results can be used to populate defect physics models in III-V semiconductor device simulations with reliable quantities in those cases where experimental data is lacking, as in AlAs. © 2011 Materials Research Society.

The objective of the U.S. Department of Energy Office of Nuclear Energy Advanced Modeling and Simulation Waste Integrated Performance and Safety Codes (NEAMS Waste IPSC) is to provide an integrated suite of computational modeling and simulation (M&S) capabilities to quantitatively assess the long-term performance of waste forms in the engineered and geologic environments of a radioactive-waste storage facility or disposal repository. Achieving the objective of modeling the performance of a disposal scenario requires describing processes involved in waste form degradation and radionuclide release at the subcontinuum scale, beginning with mechanistic descriptions of chemical reactions and chemical kinetics at the atomic scale, and upscaling into effective, validated constitutive models for input to high-fidelity continuum scale codes for coupled multiphysics simulations of release and transport. Verification and validation (V&V) is required throughout the system to establish evidence-based metrics for the level of confidence in M&S codes and capabilities, including at the subcontiunuum scale and the constitutive models they inform or generate. This Report outlines the nature of the V&V challenge at the subcontinuum scale, an approach to incorporate V&V concepts into subcontinuum scale modeling and simulation (M&S), and a plan to incrementally incorporate effective V&V into subcontinuum scale M&S destined for use in the NEAMS Waste IPSC work flow to meet requirements of quantitative confidence in the constitutive models informed by subcontinuum scale phenomena.

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This report summarizes research performed for the Nuclear Energy Advanced Modeling and Simulation (NEAMS) Subcontinuum and Upscaling Task. The work conducted focused on developing a roadmap to include molecular scale, mechanistic information in continuum-scale models of nuclear waste glass dissolution. This information is derived from molecular-scale modeling efforts that are validated through comparison with experimental data. In addition to developing a master plan to incorporate a subcontinuum mechanistic understanding of glass dissolution into continuum models, methods were developed to generate constitutive dissolution rate expressions from quantum calculations, force field models were selected to generate multicomponent glass structures and gel layers, classical molecular modeling was used to study diffusion through nanopores analogous to those in the interfacial gel layer, and a micro-continuum model (K{mu}C) was developed to study coupled diffusion and reaction at the glass-gel-solution interface.

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This report describes the progress in fiscal year 2010 in developing the Waste Integrated Performance and Safety Codes (IPSC) in support of the U.S. Department of Energy (DOE) Office of Nuclear Energy Advanced Modeling and Simulation (NEAMS) Campaign. The goal of the Waste IPSC is to develop an integrated suite of computational modeling and simulation capabilities to quantitatively assess the long-term performance of waste forms in the engineered and geologic environments of a radioactive waste storage or disposal system. The Waste IPSC will provide this simulation capability (1) for a range of disposal concepts, waste form types, engineered repository designs, and geologic settings, (2) for a range of time scales and distances, (3) with appropriate consideration of the inherent uncertainties, and (4) in accordance with robust verification, validation, and software quality requirements. Waste IPSC activities in fiscal year 2010 focused on specifying a challenge problem to demonstrate proof of concept, developing a verification and validation plan, and performing an initial gap analyses to identify candidate codes and tools to support the development and integration of the Waste IPSC. The current Waste IPSC strategy is to acquire and integrate the necessary Waste IPSC capabilities wherever feasible, and develop only those capabilities that cannot be acquired or suitably integrated, verified, or validated. This year-end progress report documents the FY10 status of acquisition, development, and integration of thermal-hydrologic-chemical-mechanical (THCM) code capabilities, frameworks, and enabling tools and infrastructure.

The objective of the U.S. Department of Energy Office of Nuclear Energy Advanced Modeling and Simulation Waste Integrated Performance and Safety Codes (NEAMS Waste IPSC) is to provide an integrated suite of computational modeling and simulation (M&S) capabilities to quantitatively assess the long-term performance of waste forms in the engineered and geologic environments of a radioactive-waste storage facility or disposal repository. To meet this objective, NEAMS Waste IPSC M&S capabilities will be applied to challenging spatial domains, temporal domains, multiphysics couplings, and multiscale couplings. A strategic verification and validation (V&V) goal is to establish evidence-based metrics for the level of confidence in M&S codes and capabilities. Because it is economically impractical to apply the maximum V&V rigor to each and every M&S capability, M&S capabilities will be ranked for their impact on the performance assessments of various components of the repository systems. Those M&S capabilities with greater impact will require a greater level of confidence and a correspondingly greater investment in V&V. This report includes five major components: (1) a background summary of the NEAMS Waste IPSC to emphasize M&S challenges; (2) the conceptual foundation for verification, validation, and confidence assessment of NEAMS Waste IPSC M&S capabilities; (3) specifications for the planned verification, validation, and confidence-assessment practices; (4) specifications for the planned evidence information management system; and (5) a path forward for the incremental implementation of this V&V plan.