23 citations · 30 across the 13 of their papers we have counts for
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cond-mat.mtrl-sci2024★ 4 cited
Universal Machine Learning Interatomic Potentials are Ready for Phonons
Antoine Loew, Dewen Sun, Hai-Chen Wang +2
There has been an ongoing race for the past several years to develop the best universal machinelearning interatomic potential. This progress has led to increasingly accurate models…
cond-mat.mtrl-sci2024
A non-orthogonal representation of the chemical space
Tiago F. T. Cerqueira, Haichen Wang, Silvana Botti +1
We present a novel approach to generate a fingerprint for crystalline materials that balances efficiency for machine processing and human interpretability, allowing its application…