Publications

Proposed for publication in Materials Research Society.

Plimpton, Steven J.; Thompson, Aidan P.

Abstract not provided.

Berry, Jonathan W.; Plimpton, Steven J.; Comandur, Seshadhri C.

Abstract not provided.

Holm, Elizabeth A.; Tikare, Veena T.; Plimpton, Steven J.

Abstract not provided.

Plimpton, Steven J.

Abstract not provided.

Computer Physics Communications

Plimpton, Steven J.

Abstract not provided.

Berry, Jonathan W.; Plimpton, Steven J.

Abstract not provided.

Parks, Michael L.; Plimpton, Steven J.; Silling, Stewart A.; Lehoucq, Richard B.

Peridynamics is a nonlocal extension of classical continuum mechanics. The discrete peridynamic model has the same computational structure as a molecular dynamics model. This document provides a brief overview of the peridynamic model of a continuum, then discusses how the peridynamic model is discretized within LAMMPS. An example problem is also included.

Lechman, Jeremy B.; Plimpton, Steven J.; Grest, Gary S.

Abstract not provided.

Deng, Jie D.; Erickson, Lindsay C.; Plimpton, Steven J.; Thompson, Aidan P.; Zhou, Xiaowang Z.; Zimmerman, Jonathan A.

Many of the most important and hardest-to-solve problems related to the synthesis, performance, and aging of materials involve diffusion through the material or along surfaces and interfaces. These diffusion processes are driven by motions at the atomic scale, but traditional atomistic simulation methods such as molecular dynamics are limited to very short timescales on the order of the atomic vibration period (less than a picosecond), while macroscale diffusion takes place over timescales many orders of magnitude larger. We have completed an LDRD project with the goal of developing and implementing new simulation tools to overcome this timescale problem. In particular, we have focused on two main classes of methods: accelerated molecular dynamics methods that seek to extend the timescale attainable in atomistic simulations, and so-called 'equation-free' methods that combine a fine scale atomistic description of a system with a slower, coarse scale description in order to project the system forward over long times.

Berry, Jonathan W.; Plimpton, Steven J.

Abstract not provided.

Plimpton, Steven J.

Abstract not provided.

Journal of Chemical Physics

Cheng, Shengfeng C.; Lechman, Jeremy B.; Plimpton, Steven J.; Grest, Gary S.

Abstract not provided.

Deng, Jie D.; Plimpton, Steven J.; Thompson, Aidan P.; Zimmerman, Jonathan A.

Abstract not provided.

Cheng, Shengfeng C.; Lechman, Jeremy B.; Plimpton, Steven J.; Grest, Gary S.

Abstract not provided.

Madison, Jonathan D.; Tikare, Veena T.; Holm, Elizabeth A.; Plimpton, Steven J.

Abstract not provided.

Plimpton, Steven J.

Abstract not provided.

Grest, Gary S.; Cheng, Shengfeng C.; Lechman, Jeremy B.; Plimpton, Steven J.

The most feasible way to disperse particles in a bulk material or control their packing at a substrate is through fluidization in a carrier that can be processed with well-known techniques such as spin, drip and spray coating, fiber drawing, and casting. The next stage in the processing is often solidification involving drying by solvent evaporation. While there has been significant progress in the past few years in developing discrete element numerical methods to model dense nanoparticle dispersion/suspension rheology which properly treat the hydrodynamic interactions of the solvent, these methods cannot at present account for the volume reduction of the suspension due to solvent evaporation. As part of LDRD project FY-101285 we have developed and implemented methods in the current suite of discrete element methods to remove solvent particles and volume, and hence solvent mass from the liquid/vapor interface of a suspension to account for volume reduction (solvent drying) effects. To validate the methods large scale molecular dynamics simulations have been carried out to follow the evaporation process at the microscopic scale.

Parallel Computing

Plimpton, Steven J.; Devine, Karen D.

Abstract not provided.

Plimpton, Steven J.; Schunk, Randy; Lechman, Jeremy B.; Grest, Gary S.; Pierce, Flint P.; Grillet, Anne M.

In this presentation we examine the accuracy and performance of a suite of discrete-element-modeling approaches to predicting equilibrium and dynamic rheological properties of polystyrene suspensions. What distinguishes each approach presented is the methodology of handling the solvent hydrodynamics. Specifically, we compare stochastic rotation dynamics (SRD), fast lubrication dynamics (FLD) and dissipative particle dynamics (DPD). Method-to-method comparisons are made as well as comparisons with experimental data. Quantities examined are equilibrium structure properties (e.g. pair-distribution function), equilibrium dynamic properties (e.g. short- and long-time diffusivities), and dynamic response (e.g. steady shear viscosity). In all approaches we deploy the DLVO potential for colloid-colloid interactions. Comparisons are made over a range of volume fractions and salt concentrations. Our results reveal the utility of such methods for long-time diffusivity prediction can be dubious in certain ranges of volume fraction, and other discoveries regarding the best formulation to use in predicting rheological response.

Brown, William M.; Crozier, Paul C.; Plimpton, Steven J.

LAMMPS is a classical molecular dynamics code, and an acronym for Large-scale Atomic/Molecular Massively Parallel Simulator. LAMMPS has potentials for soft materials (biomolecules, polymers) and solid-state materials (metals, semiconductors) and coarse-grained or mesoscopic systems. It can be used to model atoms or, more generically, as a parallel particle simulator at the atomic, meso, or continuum scale. LAMMPS runs on single processors or in parallel using message-passing techniques and a spatial-decomposition of the simulation domain. The code is designed to be easy to modify or extend with new functionality.

Devine, Karen D.; Plimpton, Steven J.; Bayer, Gregory B.; Barrett, Brian B.; Berry, Jonathan W.

Abstract not provided.

Schunk, Randy; Lechman, Jeremy B.; Grest, Gary S.; Plimpton, Steven J.; Grillet, Anne M.; Brotherton, Christopher M.

Abstract not provided.

Plimpton, Steven J.; Battaile, Corbett C.; Chandross, M.; Holm, Elizabeth A.; Thompson, Aidan P.; Tikare, Veena T.; Webb, Edmund B.; Zhou, Xiaowang Z.

The kinetic Monte Carlo method and its variants are powerful tools for modeling materials at the mesoscale, meaning at length and time scales in between the atomic and continuum. We have completed a 3 year LDRD project with the goal of developing a parallel kinetic Monte Carlo capability and applying it to materials modeling problems of interest to Sandia. In this report we give an overview of the methods and algorithms developed, and describe our new open-source code called SPPARKS, for Stochastic Parallel PARticle Kinetic Simulator. We also highlight the development of several Monte Carlo models in SPPARKS for specific materials modeling applications, including grain growth, bubble formation, diffusion in nanoporous materials, defect formation in erbium hydrides, and surface growth and evolution.

Zhou, Xiaowang Z.; Plimpton, Steven J.

Abstract not provided.

Computer Physics Communications

Parks, Michael L.; Lehoucq, Richard B.; Plimpton, Steven J.; Silling, Stewart A.

Peridynamics (PD) is a continuum theory that employs a nonlocal model to describe material properties. In this context, nonlocal means that continuum points separated by a finite distance may exert force upon each other. A meshless method results when PD is discretized with material behavior approximated as a collection of interacting particles. This paper describes how PD can be implemented within a molecular dynamics (MD) framework, and provides details of an efficient implementation. This adds a computational mechanics capability to an MD code, enabling simulations at mesoscopic or even macroscopic length and time scales. © 2008 Elsevier B.V.