An Accurate
Machine-Learned Potential for Krypton
under Extreme Conditions
Posted on 2025-02-05 - 01:32
We have developed two machine-learned pair potentials
for krypton
based on CCSD(T) quantum chemical calculations on two and three atom
clusters. Through extensive testing with molecular dynamics, we find
both potentials give good agreement with the experimental equation
of state, melting point, and neutron scattering data for the fluid.
Compared with the most widely used Lennard-Jones model, our potentials
produced similar results in low-pressure melting and equation of state.
However, extending the regime to higher pressures of ≤30 GPa
showed a remarkable divergence of the Lennard-Jones model from the
experimental (solid) equation of state. Our potential showed extremely
good agreement, despite having no solid phases in the training set.
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Iwasaki, Asuka
J.; Kirsz, Marcin; Pruteanu, Ciprian G.; Ackland, Graeme J. (2025). An Accurate
Machine-Learned Potential for Krypton
under Extreme Conditions. ACS Publications. Collection. https://doi.org/10.1021/acs.jpclett.4c03272