Provided in this zip file are the inputs for Machine-learned Force Field (MLFF) and their corresponding outputs.

The two folders:

SOAP: Contains the training performed with VASP

  1-train: The training inputs (ICONST, INCAR, KPOINTS, POSCAR, POTCAR) with outputs 
  
  2-refit: Refit the force field with previously generated ML_ABN with resultand force field files (ML_FFN)
  
  3-phonon: The MLFF phonon calculation using finite displacement method with phonopy
  
  4-qha: The quasi-harmonic approximation calculation with phonopy to obtain C_p values

  5-validation: The validation of energy and forces on 1,000 randomly generated K3C60 distortions.

ACE: Contains the training performed with FLARE package combined with Quantem Espresso

  1-train: The training inputs for FLARE (init.xyz, otf_train.yaml) with concised outputs 
  
  2-hyp_scan: The scan for radius cutoff (C-C pair from 3.0 to 4.9 A and C-K pairs from 3.7 to 5.6 A, both with step size of 0.1 A)
              The input given (offline_train.yaml) is for the optimal in the scan, along with its correspponding force field output files (*.flare)
              The model likelihood for all other scans are summarized in K3C60_flare_rcutscan.csv
  
  3-phonon: The MLFF phonon calculation using finite displacement method with phonopy. PhonoLAMMPS is used for interfacing

  4-validation: The validation of energy and forces on the same aforementioned 1,000 randomly generated K3C60 distortions.