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Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, UK, Lennard-Jones Centre, University of Cambridge, Trinity Ln, Cambridge, CB2 1TN, UK
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Widely used simulations of liquid water are surprisingly inconsistent, with errors exceeding 20% in key properties, but this work provides a robust, reproducible benchmark.
Widely used short-ranged MLIPs can spuriously predict metallization in water due to missing long-range electrostatics, a flaw that can be fixed by including these interactions explicitly.
Achieve sub-chemical accuracy in predicting the lattice energies of complex molecular crystals, including drug-like molecules, at DFT-level computational cost, unlocking high-throughput polymorph screening.
