An efficient iterative grand canonical Monte Carlo algorithm to determine individual ionic chemical potentials in electrolytes

Attila Malasics, Dezs Boda

Research output: Contribution to journalArticle

31 Citations (Scopus)

Abstract

Two iterative procedures have been proposed recently to calculate the chemical potentials corresponding to prescribed concentrations from grand canonical Monte Carlo (GCMC) simulations. Both are based on repeated GCMC simulations with updated excess chemical potentials until the desired concentrations are established. In this paper, we propose combining our robust and fast converging iteration algorithm [Malasics, Gillespie, and Boda, J. Chem. Phys. 128, 124102 (2008)] with the suggestion of Lamperski [Mol. Simul. 33, 1193 (2007)] to average the chemical potentials in the iterations (instead of just using the chemical potentials obtained in the last iteration). We apply the unified method for various electrolyte solutions and show that our algorithm is more efficient if we use the averaging procedure. We discuss the convergence problems arising from violation of charge neutrality when inserting/deleting individual ions instead of neutral groups of ions (salts). We suggest a correction term to the iteration procedure that makes the algorithm efficient to determine the chemical potentials of individual ions too.

Original languageEnglish
Article number244103
JournalJournal of Chemical Physics
Volume132
Issue number24
DOIs
Publication statusPublished - Jun 28 2010

ASJC Scopus subject areas

  • Physics and Astronomy(all)
  • Physical and Theoretical Chemistry

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