This file is automatically generated. It contains the descriptions of each uploaded file as provided by the user.

  • NOTE: An overview of the data set.
  • NN-potential.zip: The parameters of the water neural network potential based on revPBE0-D3 DFT, and an example on how to use it.
  • input-files.zip: A whole set of input files for running
  • path-integral molecular dynamics simulations ./pimd/
  • Free energy estimation of an ice system using thermodynamic integration method using the NN potential ./NN-TI/
  • revPBE0-D3 DFT calculations using the CP2K code ./cp2k-input/
  • compute the chemical potential difference between ice and liquid water using the interface pinning method ./interface-pinning/
  • Thermodynamic integration between the MBPOL water potential and the neural network potential ./mbpol-TI/
  • a sample python data analysis notebook ./data-analysis/
  • training-set.zip: The training set for ML potentials, based on revPBE0-D3 DFT. 1593 bulk liquid water configurations + energy + forces
  • input.data: the format for training neural network potentials.
  • dataset_1593.xyz: in libatom format.