Tutorials

Here you will find several notebooks to show how to use the package for different types of simulations. The notebooks can also be found in the repository, in the tutorials folder.

Caution:

For most of the example here, the parameters used were chosen in order to increase the speed of the simulations. Some of these parameters are not adequate for accurate production simulations.

Machine-Learning Interatomic Potential

• Training a Spectral Neighbor Analysis Potential
• Training a Moment Tensor Potential model

Machine-Learning Assisted Sampling

• Introduction to Machine-Learning Assisted Sampling
  • Setting up the simulation
  • Gathering everything and launching the simulation
• Using MLACS with the Multi-Bennett Aceptance Ratio (MBAR)
  • Setting up the simulation
  • Gathering everything and launching the simulation with MBAR
  • Launch the same simulation with Uniform weighting policy
  • Replay the simulation with MBAR and the Database Calculator
• Structural optimization assisted by machine-learning interatomic potentials
  • Setting up the simulation
  • Gathering everything and launching the simulation

Thermodynamic integration