Sandia National Laboratories

Since the classical molecular dynamics simulator LAMMPS was released as an open source code in 2004, it has become a widely-used tool for particle-based modeling of materials at length scales ranging from atomic to mesoscale to continuum. Reasons for its popularity are that it provides a wide variety of particle interaction models for different materials, that it runs on any platform from a single CPU core to the largest supercomputers with accelerators, and that it gives users control over simulation details, either via the input script or by adding code for new interatomic potentials, constraints, diagnostics, or other features needed for their models. As a result, hundreds of people have contributed new capabilities to LAMMPS and it has grown from fifty thousand lines of code in 2004 to a million lines today. In this paper several of the fundamental algorithms used in LAMMPS are described along with the design strategies which have made it flexible for both users and developers. We also highlight some capabilities recently added to the code which were enabled by this flexibility, including dynamic load balancing, on-the-fly visualization, magnetic spin dynamics models, and quantum-accuracy machine learning interatomic potentials. Program Title: Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) CPC Library link to program files: https://doi.org/10.17632/cxbxs9btsv.1 Developer's repository link: https://github.com/lammps/lammps Licensing provisions: GPLv2 Programming language: C++, Python, C, Fortran Supplementary material: https://www.lammps.org Nature of problem: Many science applications in physics, chemistry, materials science, and related fields require parallel, scalable, and efficient generation of long, stable classical particle dynamics trajectories. Within this common problem definition, there lies a great diversity of use cases, distinguished by different particle interaction models, external constraints, as well as timescales and lengthscales ranging from atomic to mesoscale to macroscopic. Solution method: The LAMMPS code uses parallel spatial decomposition, distributed neighbor lists, and parallel FFTs for long-range Coulombic interactions [1]. The time integration algorithm is based on the Størmer-Verlet symplectic integrator [2], which provides better stability than higher-order non-symplectic methods. In addition, LAMMPS supports a wide range of interatomic potentials, constraints, diagnostics, software interfaces, and pre- and post-processing features. Additional comments including restrictions and unusual features: This paper serves as the definitive reference for the LAMMPS code. S. Plimpton, Fast parallel algorithms for short-range molecular dynamics. J. Comp. Phys. 117 (1995) 1–19. L. Verlet, Computer experiments on classical fluids: I. Thermodynamical properties of Lennard–Jones molecules, Phys. Rev. 159 (1967) 98–103.

A novel and robust automated docking method that predicts the bound conformations of flexible ligands to macromolecular targets has been developed and tested, in combination with a new scoring function that estimates the free energy change upon binding. Interestingly, this method applies a Lamarckian model of genetics, in which environmental adaptations of an individual's phenotype are reverse transcribed into its genotype and become heritable traits (sic). We consider three search methods, Monte Carlo simulated annealing, a traditional genetic algorithm, and the Lamarckian genetic algorithm, and compare their performance in dockings of seven protein–ligand test systems having known three-dimensional structure. We show that both the traditional and Lamarckian genetic algorithms can handle ligands with more degrees of freedom than the simulated annealing method used in earlier versions of AUTODOCK, and that the Lamarckian genetic algorithm is the most efficient, reliable, and successful of the three. The empirical free energy function was calibrated using a set of 30 structurally known protein–ligand complexes with experimentally determined binding constants. Linear regression analysis of the observed binding constants in terms of a wide variety of structure-derived molecular properties was performed. The final model had a residual standard error of 9.11 kJ mol−1 (2.177 kcal mol−1) and was chosen as the new energy function. The new search methods and empirical free energy function are available in AUTODOCK, version 3.0. © 1998 John Wiley & Sons, Inc. J Comput Chem 19: 1639–1662, 1998

This survey provides an overview of higher-order tensor decompositions, their applications, and available software. A tensor is a multidimensional or N-way array. Decompositions of higher-order tensors (i.e., N-way arrays with $N \geq 3$) have applications in psycho-metrics, chemometrics, signal processing, numerical linear algebra, computer vision, numerical analysis, data mining, neuroscience, graph analysis, and elsewhere. Two particular tensor decompositions can be considered to be higher-order extensions of the matrix singular value decomposition: CANDECOMP/PARAFAC (CP) decomposes a tensor as a sum of rank-one tensors, and the Tucker decomposition is a higher-order form of principal component analysis. There are many other tensor decompositions, including INDSCAL, PARAFAC2, CANDELINC, DEDICOM, and PARATUCK2 as well as nonnegative variants of all of the above. The N-way Toolbox, Tensor Toolbox, and Multilinear Engine are examples of software packages for working with tensors.

We explore the interrelationships between the green 510 nm emission, the free-carrier concentration, and the paramagnetic oxygen-vacancy density in commercial ZnO phosphors by combining photoluminescence, optical-absorption, and electron-paramagnetic-resonance spectroscopies. We find that the green emission intensity is strongly influenced by free-carrier depletion at the particle surface, particularly for small particles and/or low doping. Our data suggest that the singly ionized oxygen vacancy is responsible for the green emission in ZnO; this emission results from the recombination of a photogenerated hole with the singly ionized charge state of this defect.

Abstract Many of the more useful and powerful nonparametric procedures may be presented in a unified manner by treating them as rank transformation procedures. Rank transformation procedures are ones in which the usual parametric procedure is applied to the ranks of the data instead of to the data themselves. This technique should be viewed as a useful tool for developing nonparametric procedures to solve new problems.

A detailed analysis of the thermal expansion mechanism of graphite oxide to produce functionalized graphene sheets is provided. Exfoliation takes place when the decomposition rate of the epoxy and hydroxyl sites of graphite oxide exceeds the diffusion rate of the evolved gases, thus yielding pressures that exceed the van der Waals forces holding the graphene sheets together. A comparison of the Arrhenius dependence of the reaction rate against the calculated diffusion coefficient based on Knudsen diffusion suggests a critical temperature of 550 °C which must be exceeded for exfoliation to occur. As a result of their wrinkled nature, the functionalized and defective graphene sheets do not collapse back to graphite oxide but are highly agglomerated. After dispersion by ultrasonication in appropriate solvents, statistical analysis by atomic force microscopy shows that 80% of the observed flakes are single sheets.

The fate of chemical and radioactive wastes in the environment is related to the ability of natural phases to attenuate and immobilize contaminants through chemical sorption and precipitation processes. Our understanding of these complex processes at the atomic level is provided by a few experimental and analytical methods such as X-ray absorption and NMR spectroscopies. However, due to complexities in the structure and composition of clay and other hydrated minerals, and the inherent uncertainties of the experimental methods, it is important to apply theoretical molecular models for a fundamental atomic-level understanding, interpretation, and prediction of these phenomena. In this effort, we have developed a general force field, CLAYFF, suitable for the simulation of hydrated and multicomponent mineral systems and their interfaces with aqueous solutions. Interatomic potentials were derived from parametrizations incorporating structural and spectroscopic data for a variety of simple hydrated compounds. A flexible SPC-based water model is used to describe the water and hydroxyl behavior. Metal−oxygen interactions are described by a Lennard-Jones function and a Coulombic term with partial charges derived by Mulliken and ESP analysis of DFT results. Bulk structures, relaxed surface structures, and intercalation processes are evaluated and compared to experimental and spectroscopic findings for validation. Our approach differs from most others in that we treat most interatomic interactions as nonbonded. This allows us to effectively use the force field for a wide variety of phases and to properly account for energy and momentum transfer between the fluid phase and the solid, while keeping the number of parameters small enough to allow modeling of relatively large and highly disordered systems. Simulations of clay, hydroxide, and oxyhydroxide phases and their interfaces with aqueous solutions combine energy minimization and molecular dynamics methods to describe the structure and behavior of water, hydroxyl, surface species, and intercalates in these systems. The results obtained to date demonstrate that CLAYFF shows good promise to evolve into a widely adaptable and broadly effective force field for molecular simulations of fluid interfaces with clays and other clay-related phases, as well as other inorganic materials characterized by complex, disordered, and often ill-determined structure and composition.

Nonparametric density gradient estimation using a generalized kernel approach is investigated. Conditions on the kernel functions are derived to guarantee asymptotic unbiasedness, consistency, and uniform consistency of the estimates. The results are generalized to obtain a simple mcan-shift estimate that can be extended in a <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">k</tex> -nearest-neighbor approach. Applications of gradient estimation to pattern recognition are presented using clustering and intrinsic dimensionality problems, with the ultimate goal of providing further understanding of these problems in terms of density gradients.

Lithiation of individual silicon nanoparticles was studied in real time with in situ transmission electron microscopy. A strong size dependence of fracture was discovered; that is, there exists a critical particle diameter of ∼150 nm, below which the particles neither cracked nor fractured upon first lithiation, and above which the particles initially formed surface cracks and then fractured due to lithiation-induced swelling. The unexpected surface cracking arose owing to the buildup of large tensile hoop stress, which reversed the initial compression, in the surface layer. The stress reversal was attributed to the unique mechanism of lithiation in crystalline Si, taking place by movement of a two-phase boundary between the inner core of pristine Si and the outer shell of amorphous Li-Si alloy. While the resulting hoop tension tended to initiate surface cracks, the small-sized nanoparticles nevertheless averted fracture. This is because the stored strain energy from electrochemical reactions was insufficient to drive crack propagation, as dictated by the interplay between the two length scales, that is, particle diameter and crack size, that control the fracture. These results are diametrically opposite to those obtained previously from single-phase modeling, which predicted only compressive hoop stress in the surface layer and thus crack initiation from the center in lithiated Si particles and wires. Our work provides direct evidence of the mechanical robustness of small Si nanoparticles for applications in lithium ion batteries.

A control law for teleoperators is presented which overcomes the instability caused by time delay. By using passivity and scattering theory, a criterion is developed which shows why existing bilateral control systems are unstable for certain environments, and why the proposed bilateral control law is stable for any environment and any time delay. The control law has been implemented on a single-axis force-reflecting hand controller, and preliminary results are shown. To keep the presentation clear, a single-degree-of-freedom (DOF) linear time-invariant (LTI) teleoperator system is discussed. Nevertheless, results can be extended, without loss of generality, to an n-DOF nonlinear teleoperation system.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

We model indentation of a metal surface by combining an atomistic metal with a hard-sphere indenter. This work provides atomistic imaging of dislocation nucleation during displacement controlled indentation on a passivated surface. Dislocations and defects are located and imaged by local deviations from centrosymmetry. For a Au(111) surface, nucleation of partial dislocation loops occurs below the surface inside the indenter contact area. We compare and contrast these observations with empirical criteria for dislocation nucleation and corresponding continuum elasticity solutions.

By combining electron paramagnetic resonance (EPR), optical absorption, and photoluminescence (PL) spectroscopy, a strong correlation is observed between the green 510 nm emission, the free-carrier concentration, and the density of singly ionized oxygen vacancies in commercial ZnO phosphor powders. From these results, we demonstrate that free-carrier depletion at the particle surface, and its effect on the ionization state of the oxygen vacancy, can strongly impact the green emission intensity. The relevance of these observations with respect to low-voltage field emission displays is discussed.

The role of extended and point defects, and key impurities such as C, O, and H, on the electrical and optical properties of GaN is reviewed. Recent progress in the development of high reliability contacts, thermal processing, dry and wet etching techniques, implantation doping and isolation, and gate insulator technology is detailed. Finally, the performance of GaN-based electronic and photonic devices such as field effect transistors, UV detectors, laser diodes, and light-emitting diodes is covered, along with the influence of process-induced or grown-in defects and impurities on the device physics.

Cantera is a suite of object-oriented software tools for problems involving chemical kinetics, thermodynamics, and/or transport processes. Cantera provides types (or classes) of objects representing phases of matter, interfaces between these phases, reaction managers, time-dependent reactor networks, and steady one-dimensional reacting flows. Cantera is currently used for applications including combustion, detonations, electrochemical energy conversion and storage, fuel cells, batteries, aqueous electrolyte solutions, plasmas, and thin film deposition.

Abstract. Direct search methods are best known as unconstrained optimization techniques that do not explicitly use derivatives. Direct search methods were formally proposed and widely applied in the 1960s but fell out of favor with the mathematical optimization community by the early 1970s because they lacked coherent mathematical analysis. Nonetheless, users remained loyal to these methods, most of which were easy to program, some of which were reliable. In the past fifteen years, these methods have seen a revival due, in part, to the appearance of mathematical analysis, as well as to interest in parallel and distributed computing. This review begins by briefly summarizing the history of direct search methods and considering the special properties of problems for which they are well suited. Our focus then turns to a broad class of methods for which we provide a unifying framework that lends itself to a variety of convergence results. The underlying principles allow generalization to handle bound constraints and linear constraints. We also discuss extensions to problems with nonlinear constraints.

SymPy is an open source computer algebra system written in pure Python. It is built with a focus on extensibility and ease of use, through both interactive and programmatic applications. These characteristics have led SymPy to become a popular symbolic library for the scientific Python ecosystem. This paper presents the architecture of SymPy, a description of its features, and a discussion of select submodules. The supplementary material provide additional examples and further outline details of the architecture and features of SymPy.

A method for inducing a desired rank correlation matrix on a multivariate input random variable for use in a simulation study is introduced in this paper. This method is simple to use, is distribution free, preserves the exact form of the marginal distributions on the input variables, and may be used with any type of sampling scheme for which correlation of input variables is a meaningful concept. A Monte Carlo study provides an estimate of the bias and variability associated with the method. Input variables used in a model for study of geologic disposal of radioactive waste provide an example of the usefulness of this procedure. A textbook example shows how the output may be affected by the method presented in this paper.

We report the creation of a nanoscale electrochemical device inside a transmission electron microscope--consisting of a single tin dioxide (SnO(2)) nanowire anode, an ionic liquid electrolyte, and a bulk lithium cobalt dioxide (LiCoO(2)) cathode--and the in situ observation of the lithiation of the SnO(2) nanowire during electrochemical charging. Upon charging, a reaction front propagated progressively along the nanowire, causing the nanowire to swell, elongate, and spiral. The reaction front is a "Medusa zone" containing a high density of mobile dislocations, which are continuously nucleated and absorbed at the moving front. This dislocation cloud indicates large in-plane misfit stresses and is a structural precursor to electrochemically driven solid-state amorphization. Because lithiation-induced volume expansion, plasticity, and pulverization of electrode materials are the major mechanical effects that plague the performance and lifetime of high-capacity anodes in lithium-ion batteries, our observations provide important mechanistic insight for the design of advanced batteries.

Abstract Ultrawide‐bandgap (UWBG) semiconductors, with bandgaps significantly wider than the 3.4 eV of GaN, represent an exciting and challenging new area of research in semiconductor materials, physics, devices, and applications. Because many figures‐of‐merit for device performance scale nonlinearly with bandgap, these semiconductors have long been known to have compelling potential advantages over their narrower‐bandgap cousins in high‐power and RF electronics, as well as in deep‐UV optoelectronics, quantum information, and extreme‐environment applications. Only recently, however, have the UWBG semiconductor materials, such as high Al‐content AlGaN, diamond and Ga 2 O 3 , advanced in maturity to the point where realizing some of their tantalizing advantages is a relatively near‐term possibility. In this article, the materials, physics, device and application research opportunities and challenges for advancing their state of the art are surveyed.

A discussion of many of the recently implemented features of GAMESS (General Atomic and Molecular Electronic Structure System) and LibCChem (the C++ CPU/GPU library associated with GAMESS) is presented. These features include fragmentation methods such as the fragment molecular orbital, effective fragment potential and effective fragment molecular orbital methods, hybrid MPI/OpenMP approaches to Hartree-Fock, and resolution of the identity second order perturbation theory. Many new coupled cluster theory methods have been implemented in GAMESS, as have multiple levels of density functional/tight binding theory. The role of accelerators, especially graphical processing units, is discussed in the context of the new features of LibCChem, as it is the associated problem of power consumption as the power of computers increases dramatically. The process by which a complex program suite such as GAMESS is maintained and developed is considered. Future developments are briefly summarized.