MLPotential Keywords¶
Engine MLPotential¶
Backend- Type:
Multiple Choice
- Options:
[M3GNet, NequIP, SchNetPack, sGDML, TorchANI]
- Description:
The machine learning potential backend.
Device- Type:
Multiple Choice
- Default value:
- Options:
[, cpu, cuda:0, cuda:1, mps]
- Description:
Device on which to run the calculation (e.g. cpu, cuda:0).
If empty, the device can be controlled using environment variables for TensorFlow or PyTorch.
MLDistanceUnit- Type:
Multiple Choice
- Default value:
Auto
- Options:
[Auto, angstrom, bohr]
- GUI name:
Internal distance unit
- Description:
Unit of distances expected by the ML backend (not the ASE calculator). The ASE calculator may require this information.
MLEnergyUnit- Type:
Multiple Choice
- Default value:
Auto
- Options:
[Auto, Hartree, eV, kcal/mol, kJ/mol]
- GUI name:
Internal energy unit
- Description:
Unit of energy output by the ML backend (not the unit output by the ASE calculator). The ASE calculator may require this information.
Model- Type:
Multiple Choice
- Default value:
ANI-2x
- Options:
[Custom, AIMNet2-B973c, AIMNet2-wB97MD3, ANI-1ccx, ANI-1x, ANI-2x, M3GNet-UP-2022]
- Description:
Select a particular parameterization.
ANI-1x and ANI-2x: based on DFT (wB97X)
ANI-1cxx: based on DLPNO-CCSD(T)/CBS
M3GNet-UP-2022: based on DFT (PBE and PBE+U) data.
AIMNet2: based on ωB97m-D3 or B97-3c data.
ANI-1x and ANI-1ccx have been parameterized to give good geometries, vibrational frequencies, and reaction energies for gasphase organic molecules containing H, C, O, and N. ANI-2x can also handle the atoms F, S, and Cl.
M3GNet-UP-2022 is a universal potential (UP) for the entire periodic table and has been primarily trained to crystal data (energies, forces, stresses) from the Materials Project.
AIMNet2 has been parametrized to give good geometries and reaction energies for gasphase molecules and ions containing H, B, C, N, O, F, Si, P, S, Cl, As, Se, Br, I.
Set to Custom to specify the backend and parameter files yourself.
NumThreads- Type:
String
- Default value:
- GUI name:
Number of threads
- Description:
Number of threads.
If not empty, OMP_NUM_THREADS will be set to this number; for PyTorch-engines, torch.set_num_threads() will be called.
ParameterDir- Type:
String
- Default value:
- GUI name:
Parameter directory
- Description:
Path to a set of parameters for the backend, if it expects to read from a directory.
ParameterFile- Type:
String
- Default value:
- Description:
Path to a set of parameters for the backend, if it expects to read from a file.