“In Silico” Seawater

Abstract

Many important processes affecting the earth's climate are determined by the physical properties of seawater. In addition, desalination of seawater is a significant source of drinking water for the human population living in coastal areas. Since the physical properties of seawater governing these processes depend on the molecular interactions among its components, a deeper knowledge of seawater at the molecular level would contribute to a better understanding of these phenomena. However, in strong contrast with the situation in other areas such as biomolecules or materials science, molecular simulation studies reporting the physical properties of seawater are currently lacking. This is probably due to the usual perception of the seawater composition being too complex to approach. This point of view ignores the fact that physical properties of seawater are dependent on a single parameter representing the composition, namely the salinity. This is because the relative proportions of any two major constituents of seasalt are always the same. Another obstacle to performing molecular simulations of seawater could have been the unavailability of a satisfactory force field representing the interactions between water molecules and dissolved substances. However, this drawback has recently been overcome with the proposal of the Madrid-2019 force field. In this work we show for the first time that molecular simulation of seawater is feasible. We have performed molecular dynamics simulations of a system, the composition of which is close to the average composition of standard seawater and with the molecular interactions given by the Madrid-2019 force field. In this way we are able to provide quantitative or semiquantitative predictions for a number of relevant physical properties of seawater for temperatures and salinities from the oceanographic range to those relevant to desalination processes. The computed magnitudes include static (density), dynamical (viscosity and diffusion coefficients), structural (ionic hydration, ion−ion distribution functions), and interfacial (surface tension) properties.

Artificial Intelligence Resolves Kinetic Pathways of Magnesium Binding to RNA

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Engineering Model for Predicting the Intradiffusion Coefficients of Hydrogen and Oxygen in Vapor, Liquid, and Supercritical Water based on Molecular Dynamics Simulations

“…The TIP4P/2005 model is used to model H 2 O. Previous studies have shown that the TIP4P/2005 force field can accurately capture the transport properties of pure H 2 O and aqueous solutions for a broad range of conditions. ,− Table lists all of the components simulated in this study and the force fields used for each one component. All force field details are provided in the Supporting Information (Tables S1–S3).…”

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