S
Steven J. Plimpton
Researcher at Sandia National Laboratories
Publications - 133
Citations - 77152
Steven J. Plimpton is an academic researcher from Sandia National Laboratories. The author has contributed to research in topics: Parallel algorithm & Direct simulation Monte Carlo. The author has an hindex of 44, co-authored 128 publications receiving 62532 citations.
Papers
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Crossing the Mesoscale No-Man's Land via Parallel Kinetic Monte Carlo
Cristina Garcia Cardona,Edmund B. Webb,Gregory J. Wagner,Veena Tikare,Elizabeth A. Holm,Steven J. Plimpton,Aidan P. Thompson,Alexander Slepoy,Xiaowang Zhou,Corbett Chandler. Battaile,Michael Chandross +10 more
TL;DR: An overview of the methods and algorithms developed, and the new open-source code called SPPARKS, for Stochastic Parallel PARticle Kinetic Simulator, for materials modeling applications, are described.
Journal ArticleDOI
Evaporation of Lennard-Jones fluids
TL;DR: In this article, the evaporation and condensation coefficients for both monatomic and polyatomic molecules are equal when systems are not far from equilibrium and smaller than one, and decrease with increasing temperature.
Dissertation
1D-to-3D transition of phonon heat conduction in polyethylene using molecular dynamics simulations
TL;DR: In this article, the thermal conductivity of polyethylene with molecular dynamics simulations is investigated. And the results are important for designing inexpensive high thermal-conductivity polymers, which gives rise to an interesting one-dimensional-to-three-dimensional transition in phonon transport.
Journal ArticleDOI
Accurate and efficient methods for modeling colloidal mixtures in an explicit solvent using molecular dynamics
TL;DR: In this paper, the authors present modified algorithms that enable fast single processor performance and reasonable parallel scalability for mixtures with a wide range of particle size ratios, independent of particle sizes and independent of the interaction potential.
Journal ArticleDOI
Massively parallel symplectic algorithm for coupled magnetic spin dynamics and molecular dynamics
TL;DR: A very general parallel algorithm is proposed that allows large spin–lattice systems to be efficiently simulated on large numbers of processors without degrading its mathematical accuracy.