The random phase approximation applied to ice

Abstract

Standard density functionals without van der Waals interactions yield an unsatisfactory description of ice phases, specifically, high density phases occurring under pressure are too unstable compared to the common low density phase I${}_h$ observed at ambient conditions. Although the description is improved by using functionals that include van der Waals interactions, the errors in relative volumes remain sizable. Here we assess the random phase approximation (RPA) for the correlation energy and compare our results to experimental data as well as diffusion Monte Carlo data for ice. The RPA yields a very balanced description for all considered phases, approaching the accuracy of diffusion Monte Carlo in relative energies and volumes. This opens a route towards a concise description of molecular water phases on surfaces and in cavities.

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• Singles correlation energy contributions in solids
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• Assessing the performance of the Random Phase Approximation for exchange and superexchange coupling constants in magnetic crystalline solids
• Machine learning density functionals from the random-phase approximation
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• Approaching the basis-set limit of the dRPA correlation energy with explicitly correlated and Projector Augmented-wave methods