kmc.txt

"Return to Steve Plimpton's home page"_main.html :c

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Kinetic Monte Carlo :h3

Kinetic Monte Carlo (KMC) is a method for stochastically modeling
"events" in a way that correctly samples the relative probabilities of
each event occurring.  An event can be a diffusive hop by an atom, the
deposition of an atom, a spin flip in a lattice model, a chemical
reaction in a biochemical network, or even a person buying a widget in
a discrete-event model.

KMC models are typically "coarse-grain" in that an entire event occurs
in one iteration/timestep of the simulation code, without the need to
track low-level dynamics leading up to the event, e.g. atomic
vibrations.

We've written an open-source KMC simulator called "SPPARKS"_spparks
which can perform both KMC and Metropolis Monte Carlo updating of
various models.  The goal of SPPARKS is to provide a framework where
basic algorithms for KMC and MMC are provided both in serial and
parallel, and which allows new applications to be easily added.  Our
main focus thus far has been on-lattice KMC for materials phenonmena
like grain growth, surface growth and deposition, and void growth.
But we have also been working to develop off-lattice KMC applications
as well.

"SPPARKS"_spparks can be downloaded "here"_download.html, and the
"SPPARKS doc pages"_spparksdoc describes the software in more detail.

:link(spparks,https://spparks.github.io)
:link(spparksdoc,https://spparks.github.io/doc/Manual.html)

Collaborators on SPPARKS:

  Aidan Thompson, Sandia
  Liz Holm, Sandia
  Corbett Battaile, Sandia
  Ed Webb, Sandia
  Alex Slepoy, DOE/NNSA :ul

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This paper describes the SPPARKS KMC and MMC code, including its
algorithms, code design, and applications:

[Parallel simulation via SPPARKS of on-lattice kinetic and Metropolis
Monte Carlo models for materials processing], J. A. Mitchell,
F. Abdeljawad, C. Battaile, C. Garcia-Cardona, E. A. Holm,
E. R. Homer, J. Madison, T. M. Rogers, A. P. Thompson, V. Tikare,
E. Webb, S. J. Plimpton, Modelling and Simulation in Materials Science
and Engineering, 31, 055001 (2023).
("abstract"_abstracts/msmse23.html)

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This paper describes an efficient kinetic Monte Carlo algorithm,
implemented in SPPARKS, which can be used for modeling biochemical
reactions, a la the Gillespie Stochastic Simulation Algorithm (SSA):

[A Constant-Time Kinetic Monte Carlo Algorithm for Simulation of Large
Biochemical Reaction Networks], A. Slepoy, A. P. Thompson,
S. J. Plimpton, J Chem Phys, 128, 205101
(2008). ("abstract"_abstracts/jcp08.html)

This paper describes work in SPPARKS to develop a KMC model of
sintering that captures the coupled effects of grain growth, pore
migration, and vacancy annihilation to the surface:

[Parallel Simulation of 3D Sintering], C. G. Cardona, V. Tikare,
S. J. Plimpton, Int J Computational Materials Science and Surface
Engineering, 4, 37-54 (2011).  ("abstract"_abstracts/ijcmsse11.html)

This paper describes work to couple KMC and SPPARKS to a
continuum-level description of a solid surface via the equation-free
methodology:

[Equation-Free Accelerated Simulations of the Morphological Relaxation
of Crystal Surfaces], G. J. Wagner, X. Zhou, S. J. Plimpton, Int J for
Multiscale Computational Engineering, 8, 423-439 (2010).
("abstract"_abstracts/ijmce10.html)

This technical report gives an overall description of SPPARKS and its
applications and algorithms.  It includes the above J Chem Phys paper
as one section:

[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. ("abstract"_abstracts/sand09.html)

You can download the entire report via "this link"_papers/sand09.pdf.