355
Views
19
CrossRef citations to date
0
Altmetric
Articles

Application of the interface potential approach to calculate the wetting properties of a water model system

&
Pages 1143-1152 | Received 05 Apr 2013, Accepted 14 Jun 2013, Published online: 11 Sep 2013
 

Abstract

The interface potential approach is used to compute the interfacial properties of a model system consisting of SPC/E water at a structureless non-polar surface. Both the spreading and drying versions of the method, in which one focuses on the growth of a thin liquid and vapour film from the surface, respectively, are employed. We examine the substrate strength dependence of interfacial properties, including the spreading and drying coefficients, contact angle and liquid–vapour surface tension at temperatures between 300 and 500 K as well as the temperature dependence of these properties at various substrate strengths. Two schemes are used to handle electrostatic interactions. In the first, the Coulomb potential is simply truncated, and in the second, Ewald summations are used to compute long-range electrostatic interactions. We find that the two schemes provide quantitatively different, but qualitatively consistent results.

Acknowledgements

The authors gratefully acknowledge the financial support of the National Science Foundation (Grant No. CHE-1012356). Computational resources were provided in part by the University at Buffalo Center for Computational Research and the Rensselaer Polytechnic Institute Computational Center for Nanotechnology Innovations.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 827.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.