Capabilities

Capabilities

SPPARKS: Mesoscale Model for Simulating Microstructural Evolution of Materials

Laboratory

Sandia National Laboratories (SNL)

Capability Expert

John Mitchell, Aidan Thompson, Steven Plimpton

Class

Computational Tools and Modeling

Node Readiness Category

2: High-Temperature Electrolysis (HTE)
3: Photoelectrochemical (PEC)

Description

SPPARKS is a parallel Monte Carlo code for on-lattice and off-lattice models that includes algorithms for kinetic Monte Carlo (KMC), rejection kinetic Monte Carlo (rKMC), and Metropolis Monte Carlo (MMC). It implements several KMC solvers whose serial computational complexity ranges from O(N) to O(NlogN) to O(1) in the number of events N owned by a processor. It has been applied to many oxide microstructural evolution processes such as sintering, Ostwald ripening, devitrification of grain boundary and more. The code is designed to be easy to modify or extended with new functionality.

Capability Bounds‎

To run on a variety of platforms from single processor, small machines to massively parallel computers

Unique Aspects‎

Simulation capabilities for a wide range of microstructural evolution processes such as grain growth, diffusion-controlled phase transformations, two-phase coarsening, deposition by CVD and other processes, recrystallization, welding, and more.

Availability‎

Open source code available under a GPL license.

Benefit‎

Investigating and modeling mesoscale behavior in materials, and at interfaces such as grain boundaries, will enable the exploration and virtual testing of mitigation strategies to prevent material failure.

Images

Grain growth during welding.

References‎

Crossing the Mesoscale No-Man's Land via Parallel Kinetic Monte Carlo, S. Plimpton, C. Battaile, M. Chandross, L. Holm, A. Thompson, V. Tikare, G. Wagner, E. Webb, X. Zhou, C. Garcia Cardona, A. Slepoy, Sandia report SAND2009-6226, October 2009.
Hybrid Potts-Phase Field Model for Coupled Microstructural-Compositional Evolution, E.R. Homer, V. Tikare, E.A. Holm, Comp. Mater. Sci., 69 414–423 (2013).
A hybrid simulation methodology for modeling dynamic recrystallization in UO2 LWR nuclear fuels, J. Madison, V. Tikare and E.A. Holm, J. Nucl. Mater., 425 173-180 (2012).
Website: http://spparks.sandia.gov.