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, multi-objective 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 six-dimensional parameter space were explored during the minimization. A similar parameterization with standard techniques would have taken more than 2000 CPU years but with the application of the newly developed techniques, the computational time was reduced to eight CPU weeks. 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 help 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 twelve 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.
Supplementary materials
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Supporting Information
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The supporting information document includes details of water property calculation from IAPWS95 equations, calculation of thermodynamic properties from simulation, additional details on performing the optimization and tuning the constraints, and tabular versions of data presented graphically in the main text.
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GOPAL GitHub Repository
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Scripts used for parameterizing GOPAL (Gibbs Optimized Potential for Atomistic simulation of Liquid water) and input files for molecular simulations performed.
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