GOPAL: A Water Model with Improved Thermodynamic Properties over a Large Pressure and Temperature Range Optimized Using Multistate Reweighting and Configuration Space Mapping

We show how reweighting and configuration mapping algorithms can be used to efficiently optimize molecular models using thermodynamic properties at a large number of state points from molecular simulations. As a proof of concept, we perform a multidimensional, multiobjective parameterization of a rigid water model over a large pressure [1-5000 atm] and temperature [274.15-372.15 K] range to the experimental property surfaces estimated using the IAPWS95 equation of state for water. Over 4000 parameter combinations in a six-dimensional parameter space were explored during the minimization. A similar parameterization with standard techniques would have taken more than 250 CPU years, but with the application of the newly developed techniques, the computational time was reduced to four CPU months. Without the added efficiency of the methods presented here, the optimization could not have simultaneously taken into account the large range of temperature and pressure points used in the fitting. The paper also describes how and why incorporating the thermodynamic properties from the first and second derivatives of Gibbs energy into the objective function helps improve the parameterization process. The resulting water model reproduces liquid phase density within the upper limit of experimental uncertainty of 0.02% over a large range of temperatures and pressures, the most accurate model yet at this low level of theory over the entire range of temperature and pressure, with little loss of fidelity in other properties. We compare the performance of this water model with 11 other rigid water models in predicting a number of other thermodynamic and kinetic properties. This process illustrates the surprising fact that a simple point charge model is able to accurately capture a substantial range of both temperature- and pressure-dependent thermodynamics without substantial deviation from experiment at ambient temperatures and pressures.

Authors

Institutions

Publication Details

Journal
Journal of Chemical Theory and Computation
Published
2025-09-16
DOI
https://doi.org/10.1021/acs.jctc.5c00978
Primary Topic
Phase Equilibria and Thermodynamics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

GOPAL: A Water Model with Improved Thermodynamic Properties over a Large Pressure and Temperature Range Optimized Using Multistate Reweighting and Configuration Space Mapping

Himanshu Paliwal, Michael R. Shirts
Journal of Chemical Theory and Computation
Phase Equilibria and Thermodynamics
article

GOPAL: A Water Model with Improved Thermodynamic Properties over a Large Pressure and Temperature Range Optimized Using Multistate Reweighting and Configuration Space Mapping

Himanshu Paliwal, Michael R. Shirts
article en

Abstract

We show how reweighting and configuration mapping algorithms can be used to efficiently optimize molecular models using thermodynamic properties at a large number of state points from molecular simulations. As a proof of concept, we perform a multidimensional, multiobjective parameterization of a rigid water model over a large pressure [1-5000 atm] and temperature [274.15-372.15 K] range to the experimental property surfaces estimated using the IAPWS95 equation of state for water. Over 4000 parameter combinations in a six-dimensional parameter space were explored during the minimization. A similar parameterization with standard techniques would have taken more than 250 CPU years, but with the application of the newly developed techniques, the computational time was reduced to four CPU months. Without the added efficiency of the methods presented here, the optimization could not have simultaneously taken into account the large range of temperature and pressure points used in the fitting. The paper also describes how and why incorporating the thermodynamic properties from the first and second derivatives of Gibbs energy into the objective function helps improve the parameterization process. The resulting water model reproduces liquid phase density within the upper limit of experimental uncertainty of 0.02% over a large range of temperatures and pressures, the most accurate model yet at this low level of theory over the entire range of temperature and pressure, with little loss of fidelity in other properties. We compare the performance of this water model with 11 other rigid water models in predicting a number of other thermodynamic and kinetic properties. This process illustrates the surprising fact that a simple point charge model is able to accurately capture a substantial range of both temperature- and pressure-dependent thermodynamics without substantial deviation from experiment at ambient temperatures and pressures.

Journal of Chemical Theory and ComputationVol. 21(19)
Indian Institute of Technology Ropar (IN), University of Colorado Boulder (US), University of Colorado System (US)
Openalex Percentile: Top 76%
Phase Equilibria and Thermodynamics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.