Publications

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Grain boundary engineered materials are of immense interest for their resistance to hydrogen embrittlement. This work builds on the work undertaken in Part I on the thermodynamic stability and structure of misoriented grain boundaries vicinal to the (coherent-twin) boundary to examine hydrogen segregation to those boundaries. The segregation of hydrogen reflects the asymmetry of the boundary structure with the sense of rotation of the grains about the coherent-twin boundary, and the temperature-dependent structural transition present in one sense of misorientation. This work also finds that the presence of hydrogen affects a change in structure of the boundaries with increasing concentration. The structural change effects only one sense of misorientation and results in the reduction in length of the emitted stacking faults. Moreover, the structural change results in the generation of occupied sites populated by more strongly bound hydrogen. The improved understanding of misoriented twin grain boundary structure and the effect on hydrogen segregation resulting from this work is relevant to higher length-scale models. To that end, we examine commonly used metrics such as free volume and atomic stress at the boundary. Free volume is found not to be useful as a surrogate for predicting the degree of hydrogen segregation, whereas the volumetric virial stress reliably predicts the locations of hydrogen segregation and exclusion at concentrations below saturation or the point where structural changes are induced by increasing hydrogen concentration. This manuscript has been authored by Sandia Corporation under Contract No. DE-AC04-94AL85000 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes.

Grain boundary-engineered materials are of immense interest for their corrosion resistance, fracture resistance and microstructural stability. This work contributes to a larger goal of understanding both the structure and thermodynamic properties of grain boundaries vicinal (within) to the (coherent twin) boundary which is found in grain boundary-engineered materials. The misoriented boundaries vicinal to the twin show structural changes at elevated temperatures. In the case of nickel, this transition temperature is substantially below the melting point and at temperatures commonly reached during processing, making the existence of such boundaries very likely in applications. Thus, the thermodynamic stability of such features is thoroughly investigated in order to predict and fully understand the structure of boundaries vicinal to twins. Low misorientation angle grain boundaries () show distinct disconnections which accommodate misorientation in opposite senses. The two types of disconnection have differing lowerature structures which show different temperature-dependent behaviours with one type undergoing a structural transition at approximately 600 K. At misorientation angles greater than approximately, the discrete disconnection nature is lost as the disconnections merge into one another. Free energy calculations demonstrate that these high-angle boundaries, which exhibit a transition from a planar to a faceted structure, are thermodynamically more stable in the faceted configuration.

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Displacement damage caused by ions or neutrons in microelectronic devices can have significant effect on the performance of these devices. Therefore, it is important to predict not only the displacement damage profile, but also its magnitude precisely. Analytical methods and binary collision approximation codes working with amorphous targets use the concept of displacement energy, the energy that a lattice atom has to receive to create a permanent replacement. It was found that this "displacement energy" is direction dependent; it can range from 12 to 32 eV in silicon. Obviously, this model fails in BCA codes that work with crystalline targets, such as Marlowe. Marlowe does not use displacement energy; instead, it uses lattice binding energy only and then pairs the interstitial atoms with vacancies. Then based on the configuration of the Frenkel pairs it classifies them as close, near, or distant pairs, and considers the distant pairs the permanent replacements. Unfortunately, this separation is an ad hoc assumption, and the results do not agree with molecular dynamics calculations. After irradiation, there is a prompt recombination of interstitials and vacancies if they are nearby, within a recombination radius. In order to implement this recombination radius in Marlowe, we used the comparison of MD and Marlowe calculation in a range of ion energies in single crystal silicon target. The calculations showed that a single recombination radius of ∼7.4 Å in Marlowe for a range of ion energies gives an excellent agreement with MD.

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The formation of He bubbles in erbium tritides is a significant process in the aging of these materials. Due to the long-standing uncertainty about the initial nucleation process of these bubbles, there is interest in mechanisms that can lead to the localization of He in erbium hydrides. Previous work has been unable to identify nucleation sites in homogeneous erbium hydride. This work builds on the experimental observation that erbium hydrides have nano- scale erbium oxide precipitates due to the high thermodynamic stability of erbium oxide and the ubiquitous presence of oxygen during materials processing. Fundamental DFT calculations indicate that the He is energetically favored in the oxide relative to the bulk hydride. Activation energies for the motion of He in the oxide and at the oxide-hydride interface indicate that trapping is kinetically feasible. A simple kinetic Monte Carlo model is developed that demonstrates the degree of trapping of He as a function of temperature and oxide fraction.

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Nanostructuring has been proposed as a method to enhance radiation tolerance, but many metallic systems are rejected due to significant concerns regarding long term grain boundary and interface stability. This work utilized recent advancements in transmission electron microscopy (TEM) to quantitatively characterize the grain size, texture, and individual grain boundary character in a nanocrystalline gold model system before and after in situ TEM ion irradiation with 10 MeV Si. The initial experimental measurements were fed into a mesoscale phase field model, which incorporates the role of irradiation-induced thermal events on boundary properties, to directly compare the observed and simulated grain growth with varied parameters. The observed microstructure evolution deviated subtly from previously reported normal grain growth in which some boundaries remained essentially static. In broader terms, the combined experimental and modeling techniques presented herein provide future avenues to enhance quantification and prediction of the thermal, mechanical, or radiation stability of grain boundaries in nanostructured crystalline systems.

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We present a new interatomic potential for solids and liquids called Spectral Neighbor Analysis Potential (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 onto a basis of hyperspherical harmonics in four dimensions. The bispectrum components are the same bond-orientational order parameters employed by the GAP potential [1]. The SNAP potential, unlike GAP, assumes a linear relationship between atom energy and bispectrum components. The linear SNAP coefficients 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. We demonstrate that a previously unnoticed symmetry property can be exploited to reduce the computational cost of the force calculations by more than one order of magnitude. We present results for a SNAP potential for tantalum, showing that it accurately reproduces a range of commonly calculated properties of both the crystalline solid and the liquid phases. In addition, unlike simpler existing potentials, SNAP correctly predicts the energy barrier for screw dislocation migration in BCC tantalum.

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This report summarizes a project in which the authors sought to develop and deploy: (i) experimental techniques to elucidate the complex, multiscale nature of thermal transport in particle-based materials; and (ii) modeling approaches to address current challenges in predicting performance variability of materials (e.g., identifying and characterizing physical- chemical processes and their couplings across multiple length and time scales, modeling information transfer between scales, and statically and dynamically resolving material structure and its evolution during manufacturing and device performance). Experimentally, several capabilities were successfully advanced. As discussed in Chapter 2 a flash diffusivity capability for measuring homogeneous thermal conductivity of pyrotechnic powders (and beyond) was advanced; leading to enhanced characterization of pyrotechnic materials and properties impacting component development. Chapter 4 describes success for the first time, although preliminary, in resolving thermal fields at speeds and spatial scales relevant to energetic components. Chapter 7 summarizes the first ever (as far as the authors know) application of TDTR to actual pyrotechnic materials. This is the first attempt to actually characterize these materials at the interfacial scale. On the modeling side, new capabilities in image processing of experimental microstructures and direct numerical simulation on complicated structures were advanced (see Chapters 3 and 5). In addition, modeling work described in Chapter 8 led to improved prediction of interface thermal conductance from first principles calculations. Toward the second point, for a model system of packed particles, significant headway was made in implementing numerical algorithms and collecting data to justify the approach in terms of highlighting the phenomena at play and pointing the way forward in developing and informing the kind of modeling approach originally envisioned (see Chapter 6). In both cases much more remains to be accomplished.

Over the past decade, numerous efforts have sought to understand the influence of twin boundaries on the behavior of polycrystalline materials. Early results suggested that twin boundaries within nanocrystalline face-centered cubic metals have a considerable effect on material behavior by altering the activated deformation mechanisms. In this work, we employ molecular dynamics simulations to elucidate the role of twin boundaries on the deformation of 〈100〉 columnar nanocrystalline copper at room temperature under uniaxial strain. We leverage non-local kinematic metrics, formulated from continuum mechanics theory, to compute atomically-resolved rotational and strain fields during plastic deformation. These results are then utilized to compute the distribution of various nanoscale mechanisms during straining, and quantitatively resolve their contribution to the total strain accommodation within the microstructure, highlighting the fundamental role of twin boundaries. Our results show that nanoscale twins influence nanocrystalline copper by altering the cooperation of fundamental deformation mechanisms and their contributed role in strain accommodation, and we present new methods for extracting useful information from atomistic simulations. The simulation results suggest a tension-compression asymmetry in the distribution of deformation mechanisms and strain accommodation by either dislocations or twin boundary mechanisms. In highly twinned microstructures, twin boundary migration can become a significant deformation mode, in comparison to lattice dislocation plasticity in non-twinned columnar microstructures, especially during compression.

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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.

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