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An efficient iterative grand canonical Monte Carlo algorithm to determine individual ionic chemical potentials in electrolytes.
MedLine Citation:
PMID:  20590177     Owner:  NLM     Status:  PubMed-not-MEDLINE    
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.
Attila Malasics; Dezso Boda
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  The Journal of chemical physics     Volume:  132     ISSN:  1089-7690     ISO Abbreviation:  J Chem Phys     Publication Date:  2010 Jun 
Date Detail:
Created Date:  2010-07-01     Completed Date:  2010-09-24     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  0375360     Medline TA:  J Chem Phys     Country:  United States    
Other Details:
Languages:  eng     Pagination:  244103     Citation Subset:  -    
Department of Physical Chemistry, University of Pannonia, P.O. Box 158, H-8201 Veszprém, Hungary.
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