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Efficient machine learning interatomic potentials robust for liquid and multiple solid polymorphs of NaF and KF

Zhao Fan1,2, Michael L. Whittaker1,3,*, and Mark Asta1,2,†

  • *Contact author: mwhittaker@lbl.gov
  • †Contact author: mdasta@lbl.gov

Convolutional neural networks enable high-fidelity prediction of rotation-invariant properties of amorphous and crystalline materials

Zhao Fan

Phys. Rev. Materials 10 053803 (2026)

A Framework for Validating ML Potentials against Experimental Phonon Dispersion and Elastic Constants

Sophie Laurent, Pierre Dubois, Marc Lefevre, and Claire Moreau

J. Comput. Data-Driven Mater. Eng. 5 (2026)

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