DeePKS+ABACUS as a Bridge between Expensive Quantum Mechanical Models and Machine Learning Potentials

no code implementations • 21 Jun 2022 • Wenfei Li, Qi Ou, Yixiao Chen, Yu Cao, Renxi Liu, Chunyi Zhang, Daye Zheng, Chun Cai, Xifan Wu, Han Wang, Mohan Chen, Linfeng Zhang

However, for high-level QM methods, such as density functional theory (DFT) at the meta-GGA level and/or with exact exchange, quantum Monte Carlo, etc., generating a sufficient amount of data for training a ML potential has remained computationally challenging due to their high cost.

Efficient Neural Network

Isotope effects on molecular structures and electronic properties of liquid water via deep potential molecular dynamics based on SCAN functional

no code implementations • 9 Dec 2020 • Jianhang Xu, Chunyi Zhang, Linfeng Zhang, Mohan Chen, Biswajit Santra, Xifan Wu

Feynman path-integral deep potential molecular dynamics (PI-DPMD) calculations have been employed to study both light (H$_2$O) and heavy water (D$_2$O) within the isothermal-isobaric ensemble.

Chemical Physics Computational Physics