Genetic Algorithm Driven Force Field Parameterization for Molten Alkali-Metal Carbonate and Hydroxide Salts

Anirban Mondal, Jeffrey M. Young, Timothy A. Barckholtz, Gabor Kiss, Lucas Koziol, Athanassios Z. Panagiotopoulos

Research output: Contribution to journalArticle

Abstract

Molten alkali-metal carbonates and hydroxides play important roles in the molten carbonate fuel cell and in Earth's geochemistry. Molecular simulations allow us to study these systems at extreme conditions without the need for difficult experimentation. Using a genetic algorithm to fit ab intio molecular dynamics-computed densities and radial distribution functions, as well as experimental enthalpies of formation, we derive new classical force fields able to accurately predict liquid chemical potentials. These fitting properties were chosen to ensure accurate liquid phase structure and energetics. Although the predicted dynamics is slow when compared to experiments, in general the trends in dynamic properties across different systems still hold true. In addition, these newly parametrized force fields can be extended to the molten carbonate-hydroxide mixtures by using standard combining rules.

Original languageEnglish (US)
Pages (from-to)5736-5746
Number of pages11
JournalJournal of Chemical Theory and Computation
Volume16
Issue number9
DOIs
StatePublished - Sep 8 2020

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Physical and Theoretical Chemistry

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