74
Views
3
CrossRef citations to date
0
Altmetric
Articles

Introducing a novel method based on the imperialistic competitive algorithm to determine fluorine intermolecular potential from ab initio calculations and calculation of some properties via MD simulations

, ORCID Icon, ORCID Icon, &
Pages 243-253 | Received 10 Mar 2017, Accepted 06 Aug 2017, Published online: 21 Aug 2017
 

Abstract

In this work, the possibility of obtaining an accurate site-site potential model suitable for use in molecular dynamics (MD) simulations of fluorine from ab initio calculations has been explored. The exploration was made on ab initio calculations. To reduce the ab initio pair potentials into a site-site potential, a higher significance was assigned to the configuration which is more stable. For this purpose, the imperialistic competitive algorithm (ICA) was implemented as a powerful optimisation tool. The calculated second virial coefficients were compared to the experimental values to test the quality of the presented intermolecular potential. The relative error for the calculated second virial coefficient ranged from 0.1 to 5.6%. MD simulations were used to evaluate the ability of the proposed intermolecular potential function. The relative error for the MD simulations ranged from 0.5 to 5.2%. The results are in good agreement with experimental data.

Acknowledgements

ST is thankful to Yazd University for Ph.D. scholarship. MN is thankful to Prof. M. L. Coote for her continuously kind support.

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.