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The script includes all necessary inputs/codes for GAP active learning.

The active learning steps are listed below:

  1. Crack simulation: K test (LAMMPS)
  2. GAP evaluation (QUIP) + Crack tip extraction (PYTHON)
  3. DFT calculation (Quantum Espresso)
  4. GAP training (QUIP) -> 0.K test

The other folders are:

  • GAP_model: current GAP that is used for current atomistic simulation
  • DATA: data produced in each iteration

Prerequisites are needed:

  • Python module ovito/matplotlib are needed.
  • The path for LAMMPS/QE executable needs to be customised by the user in slurm submit file.
  • The path for QUIP need to be defined in 1.GAP_evaluation/100_011/local_variances.sh , 1.GAP_evaluation/110_001/local_variances.sh and 3.NEWGAP_training/submit. -