title: Efficient global optimization of reactive force-field parameters.
abstract: 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. © 2015 Wiley Periodicals, Inc.
authors.affiliation: Institute for Physical Chemistry, Christian-Albrechts-University, Olshausenstr. 40, 24098, Kiel, Germany.
authors.forename: Mark
authors.initials: M
authors.lastname: Dittner
authors.affiliation: Institute for Physical Chemistry, Christian-Albrechts-University, Olshausenstr. 40, 24098, Kiel, Germany.
authors.forename: Julian
authors.initials: J
authors.lastname: Müller
authors.affiliation: Department of Computer Science and Engineering, Michigan State University, East Lansing, Michigan, 48824.|Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, California, 94720.
authors.forename: Hasan Metin
authors.initials: HM
authors.lastname: Aktulga
authors.affiliation: Institute for Physical Chemistry, Christian-Albrechts-University, Olshausenstr. 40, 24098, Kiel, Germany.
authors.forename: Bernd
authors.initials: B
authors.lastname: Hartke
keywords: ReaxFF; genetic algorithms; global optimization; reactive force fields