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Publication Detail
Non-equilibrium simulations of thermally induced electric fields in water.
  • Publication Type:
    Journal article
  • Publication Sub Type:
    Article
  • Authors:
    Wirnsberger P, Fijan D, Saric A, Neumann M, Dellago C, Frenkel D
  • Publication date:
    10/06/2016
  • Pagination:
    224102
  • Journal:
    The Journal of chemical physics
  • Volume:
    144
  • Issue:
    22
  • Medium:
    Print
  • Print ISSN:
    0021-9606
  • Language:
    eng
  • Addresses:
    Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, United Kingdom.
Abstract
Using non-equilibrium molecular dynamics simulations, it has been recently demonstrated that water molecules align in response to an imposed temperature gradient, resulting in an effective electric field. Here, we investigate how thermally induced fields depend on the underlying treatment of long-ranged interactions. For the short-ranged Wolf method and Ewald summation, we find the peak strength of the field to range between 2 × 10(7) and 5 × 10(7) V/m for a temperature gradient of 5.2 K/Å. Our value for the Wolf method is therefore an order of magnitude lower than the literature value [J. A. Armstrong and F. Bresme, J. Chem. Phys. 139, 014504 (2013); J. Armstrong et al., J. Chem. Phys. 143, 036101 (2015)]. We show that this discrepancy can be traced back to the use of an incorrect kernel in the calculation of the electrostatic field. More seriously, we find that the Wolf method fails to predict correct molecular orientations, resulting in dipole densities with opposite sign to those computed using Ewald summation. By considering two different multipole expansions, we show that, for inhomogeneous polarisations, the quadrupole contribution can be significant and even outweigh the dipole contribution to the field. Finally, we propose a more accurate way of calculating the electrostatic potential and the field. In particular, we show that averaging the microscopic field analytically to obtain the macroscopic Maxwell field reduces the error bars by up to an order of magnitude. As a consequence, the simulation times required to reach a given statistical accuracy decrease by up to two orders of magnitude.
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