Systematic Optimization of Water Models Using Liquid/Vapor Surface Tension Data

23 April 2019, Version 1
This content is a preprint and has not undergone peer review at the time of posting.


In this work we investigate whether experimental surface tension measurements, which are less sensitive to quantum and self-polarization corrections, are able to replace the usual reliance on the heat of vaporization as experimental reference data for fitting force field models of molecular liquids. To test this hypothesis we develop the fitting protocol necessary to utilize surface tension measurements in the ForceBalance optimization procedure in order to determine revised parameters for both three-point and four-point water models, TIP3P-ST and TIP4P-ST. We find that the incorporation of surface tension in the fit results in a rigid three-point model that reproduces the correct temperature of maximum density of water for the first time, but also leads to over-structuring of the liquid and less accurate transport properties. The rigid four-point TIP4P-ST model is highly accurate for a broad range of thermodynamic and kinetic properties, with similar performance compared to recently developed four- point water models. The results show surface tension to be a useful fitting property in general, especially when self-polarization corrections or nuclear quantum corrections are not readily available for correcting the heat of vaporization as is the case for other molecular liquids.


water models results
force field studies


Comments are not moderated before they are posted, but they can be removed by the site moderators if they are found to be in contravention of our Commenting Policy [opens in a new tab] - please read this policy before you post. Comments should be used for scholarly discussion of the content in question. You can find more information about how to use the commenting feature here [opens in a new tab] .
This site is protected by reCAPTCHA and the Google Privacy Policy [opens in a new tab] and Terms of Service [opens in a new tab] apply.