Low-Cost Vibrational Free Energies in Solid Solutions with Machine Learning Force Fields
Kasper Tolborg,
Aron Walsh
Abstract:The rational design
of alloys and solid solutions relies
on accurate
computational predictions of phase diagrams. The cluster expansion
method has proven to be a valuable tool for studying disordered crystals.
However, the effects of vibrational entropy are commonly neglected
due to the computational cost. Here, we devise a method for including
the vibrational free energy in cluster expansions with a low computational
cost by fitting a machine learning force field (MLFF) to the relaxation
trajectories availabl… Show more
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