Prediction of self-diffusion coefficients of chemically diverse pure liquids by all-atom molecular dynamics simulations

Hiromi Baba, Ryo Urano, Tetsuro Nagai, Susumu Okazaki

Research output: Contribution to journalArticlepeer-review

Abstract

Molecular self-diffusion coefficients underlie various kinetic properties of the liquids involved in chemistry, physics, and pharmaceutics. In this study, 547 self-diffusion coefficients are calculated based on all-atom molecular dynamics (MD) simulations of 152 diverse pure liquids at various temperatures employing the OPLS4 force field. The calculated coefficients are compared with experimental data (424 extracted from the literature and 123 newly measured by pulsed-field gradient nuclear magnetic resonance). The calculations well agree with the experimental values. The determination coefficient and root mean square error between the observed and calculated logarithmic self-diffusion coefficients of the 547 entries are 0.931 and 0.213, respectively, demonstrating that the MD calculation can be an excellent industrial tool for predicting, for example, molecular transportation in liquids such as the diffusion of active ingredients in biological and pharmaceutical liquids. The self-diffusion coefficients collected in this study are compiled into a database for broad researches including artificial intelligence calculations.

Original languageEnglish
JournalJournal of Computational Chemistry
DOIs
Publication statusAccepted/In press - 2022

Keywords

  • liquid state
  • mean square displacement
  • molecular dynamics simulation
  • self-diffusion coefficient
  • water model

ASJC Scopus subject areas

  • Chemistry(all)
  • Computational Mathematics

Fingerprint

Dive into the research topics of 'Prediction of self-diffusion coefficients of chemically diverse pure liquids by all-atom molecular dynamics simulations'. Together they form a unique fingerprint.

Cite this