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Estimates of Electrical Conductivity from Molecular Dynamics Simulations: How to Invest the Computational Effort
Author(s) -
Piotr Kubisiak,
Andrzej Eilmes
Publication year - 2020
Publication title -
the journal of physical chemistry b
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.864
H-Index - 392
eISSN - 1520-6106
pISSN - 1520-5207
DOI - 10.1021/acs.jpcb.0c07704
Subject(s) - molecular dynamics , conductivity , electrolyte , diagonal , convergence (economics) , electrical resistivity and conductivity , statistical physics , mean squared displacement , ion , displacement (psychology) , trajectory , materials science , mathematics , physics , chemistry , computational chemistry , quantum mechanics , psychology , geometry , electrode , economics , psychotherapist , economic growth
Although the electrical conductivity of an electrolyte can be estimated from the molecular dynamics trajectory, it is often a challenging task because of the need to obtain a substantial amount of data to ensure sufficient averaging. Here, we present an analysis on the convergence of results with the number of simulated trajectories. A series of molecular dynamics simulations have been performed for a model electrolyte (NaCl in water) and the Einstein relation has been used to calculate the electrical conductivity. The standard deviation of the conductivity estimates is relatively large compared to the mean value, and it has been shown that the off-diagonal contributions to the collective displacement of ions are responsible for large deviations between systems. It has been found that about 40 independent MD simulations may be required to reduce the errors. A procedure to improve the final estimate of the conductivity has been proposed.

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