ML potentials & 2D materials · 2023

Gaussian approximation potentials for accurate thermal properties of two-dimensional materials

Tuğbey Kocabaş, Murat Keçeli, Álvaro Vázquez-Mayagoitia, Cem Sevik

Nanoscale 15, 8772 (2023)

Publisher (DOI) PDF Supplement Code

Summary

Trains Gaussian approximation potentials on ab initio data for graphene, silicene, h-BN, and h-AlN and shows they reproduce first-principles lattice-dynamics and thermal properties at molecular-dynamics cost.

Keywords

Gaussian approximation potentialsmachine-learning interatomic potentials2D materialsthermal propertiesphononsgrapheneh-BNmolecular dynamics

Cite

@article{2023_kocabas_gap_2d_thermal_properties,
  title = {Gaussian approximation potentials for accurate thermal properties of two-dimensional materials},
  author = {Tuğbey Kocabaş and Murat Keçeli and Álvaro Vázquez-Mayagoitia and Cem Sevik},
  journal = {Nanoscale 15, 8772 (2023)},
  year = {2023},
  doi = {10.1039/d3nr00399j}
}