TY - JOUR
AB - A machine learning framework that uses atomic orbital-based Hamiltonian matrices and gradients predicted by an equivariant graph neural network is established to calculate electron–phonon coupling (EPC). This approach accelerates the calculations by several orders of magnitude, enabling EPC-related properties to be predicted for complex systems using highly accurate functionals.
TI - A machine learning tool to efficiently calculate electron–phonon coupling
JF - Nature Computational Science
DO - 10.1038/s43588-024-00680-x
DA - 2024-08-01
UR - https://www.deepdyve.com/lp/springer-journals/a-machine-learning-tool-to-efficiently-calculate-electron-phonon-ne80ig8Fqj
SP - 565
EP - 566
VL - 4
IS - 8
DP - DeepDyve
ER -