From the 1 of 93 linked papers with an AI index.
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A first-principles machine-learning force field for heterogeneous ice nucleation on microcline feldspar
Pablo M. Piaggi, Annabella Selloni, Athanassios Z. Panagiotopoulos +2
The formation of ice in the atmosphere affects precipitation and cloud properties, and plays a key role in the climate of our planet. Although ice can form directly from liquid wat…
Thermal Conductivity of Water at Extreme Conditions
Cunzhi Zhang, Marcello Puligheddu, Linfeng Zhang +2
Measuring the thermal conductivity () of water at extreme conditions is a challenging task and few experimental data are available. We predict for temperatures and pressures…
Ab Initio bulk free energy surface of proper ferroelectrics
Pinchen Xie, Yixiao Chen, Xinyu Xu +3
We report a systematic and accurate approach for deriving the bulk free energy surface (FES), a function of temperature, polarization, and strain, from the first-principles density…
Homogeneous ice nucleation in an ab initio machine learning model of water
Pablo M. Piaggi, Jack Weis, Athanassios Z. Panagiotopoulos +2
Molecular simulations have provided valuable insight into the microscopic mechanisms underlying homogeneous ice nucleation. While empirical models have been used extensively to stu…
Viscosity in water from first-principles and deep-neural-network simulations
Cesare Malosso, Linfeng Zhang, Roberto Car +2
We report on an extensive study of the viscosity of liquid water at near-ambient conditions, performed within the Green-Kubo theory of linear response and equilibrium ab initio mol…
Heat transport in liquid water from first-principles and deep-neural-network simulations
Davide Tisi, Linfeng Zhang, Riccardo Bertossa +3
We compute the thermal conductivity of water within linear response theory from equilibrium molecular dynamics simulations, by adopting two different approaches. In one, the potent…