Journal
JOURNAL OF COMPUTATIONAL CHEMISTRY
Volume 36, Issue 20, Pages 1550-1561Publisher
WILEY
DOI: 10.1002/jcc.23966
Keywords
reactive force fields; ReaxFF; global optimization; genetic algorithms
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Reactive force fields make low-cost simulations of chemical reactions possible. However, optimizing them for a given chemical system is difficult and time-consuming. We present a high-performance implementation of global force-field parameter optimization, which delivers parameter sets of the same quality with much less effort and in far less time than before, and also offers excellent parallel scaling. We demonstrate these features with example applications targeting the ReaxFF force field. (c) 2015 Wiley Periodicals, Inc.
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