An Optimized Species-Conserving Monte Carlo Method with Potential Applicability to High Entropy Alloys
ORAL
Abstract
We present a species-conserving Monte Carlo (MC) method, motivated by systems such as high-entropy
alloys. Current fast local-structure MC methods do not conserve the net concentration of atomic species, or
are inefficient for complex atomic systems. By coarse-graining the atomic lattice into clusters and developing
a renormalized MC method that takes advantage of the local structure of the atoms, we are able to significantly
reduce the number of iterations required for MC simulations to reach equilibrium. In addition, the structure of
the method enables easy parallelizability for the future.
alloys. Current fast local-structure MC methods do not conserve the net concentration of atomic species, or
are inefficient for complex atomic systems. By coarse-graining the atomic lattice into clusters and developing
a renormalized MC method that takes advantage of the local structure of the atoms, we are able to significantly
reduce the number of iterations required for MC simulations to reach equilibrium. In addition, the structure of
the method enables easy parallelizability for the future.
*AFOSR (MURI FA9550-18-1-0095), GEM fellowship
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Publication: A. Fall, M. Grasinger, K. Dayal, An Optimized Species-Conserving Monte Carlo Method with Potential Applicability to High Entropy Alloys, 2022
Presenters
-
Aziz Fall
- Carnegie Mellon University