TY - JOUR
T1 - Prediction of self-diffusion coefficients of chemically diverse pure liquids by all-atom molecular dynamics simulations
AU - Baba, Hiromi
AU - Urano, Ryo
AU - Nagai, Tetsuro
AU - Okazaki, Susumu
N1 - Publisher Copyright:
© 2022 The Authors. Journal of Computational Chemistry published by Wiley Periodicals LLC.
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
KW - liquid state
KW - mean square displacement
KW - molecular dynamics simulation
KW - self-diffusion coefficient
KW - water model
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U2 - 10.1002/jcc.26975
DO - 10.1002/jcc.26975
M3 - Article
C2 - 36128785
AN - SCOPUS:85135587983
SN - 0192-8651
JO - Journal of Computational Chemistry
JF - Journal of Computational Chemistry
ER -