uMLIP for 2D materials

Data for manuscript, entitled: "Remarkable Accuracy of Universal Machine Learning Potentials for Mechanical and Phononic Properties of 2D Materials" DFT_Details.zip contains representative computational details for the DFT calculations, with examples for AIMD, phonon dispersion, and structural relaxation calculations using the VASP package. This dataset also includes the complete training datasets generated for defective graphene, hexagonal boron nitride (hBN), and nanoporous carbon-nitride covalent organic frameworks (CN-COFs), together with the corresponding passively-fitted MTP potentials.

The datasets are provided in both CFG and XYZ formats. In the CFG and MTP files, the atomic type indices 1, 5, 6, and 7 correspond to H, B, C, and N atoms, respectively.