We report the static and dynamical properties of liquid water at the level of second-order M?ller-Plesset per- perturbation theory (MP2) with classical and quantum nuclear dynamics using a neural network potential. We examined the temperature-dependent radial distribution functions, diffusion, and vibrational dynamics. MP2 theory predicts over-structured liquid water as well as a lower diffusion coefficient at ambient conditions compared to experiments, which may be attributed to the incomplete basis set. A better agreement with experimental structural properties and the diffusion constant are observed at an elevated temperature of 340 K from our simulations. Although the high-level electronic structure calculations are expensive, training a neural network potential requires only a few thousand frames. The approach is promising as it involves modest human effort and is straightforwardly extensible to other simple liquids. Price of 2-Bromo-5-cyanobenzoic acid Formula of endo-BCN-NHS carbonate PMID:25016614
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