Prediction of self‐diffusion coefficients of chemically diverse pure liquids by all‐atom molecular dynamics simulations. Issue 28 (9th August 2022)

• Record Type: Journal Article
• Authors: Baba, Hiromi; Urano, Ryo; Nagai, Tetsuro; Okazaki, Susumu
• Is Part Of: Journal of computational chemistry. Volume 43:Issue 28(2022)
• Page Start: 1892
• Page End: 1900
• Publication Date: 2022-08-09
• Subjects: liquid state -- mean square displacement -- molecular dynamics simulation -- self‐diffusion coefficient -- water model; Chemistry -- Data processing -- Periodicals; 542.85
• DOI: 10.1002/jcc.26975
• Languages: English
• ISSNs: 0192-8651

Abstract

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. Abstract : All‐atom molecular dynamics calculations with the OPLS4 force field can excellently predict 547 experimentally determined self‐diffusion coefficients of chemically diverse pure liquids. The determination coefficient and root mean square error of the predictions were 0.931 and 0.213, respectively. Both calculated and experimental data were compiled into a database. The 547 experimental data included 424 literature values and 123 newly measured values in our pulsed‐field‐gradient NMR experiments.