Frequently Asked Questions¶
What kind of properties can I fit?¶
In AMS2024 you can only train to
energies
forces
Can I run on the GPU?¶
Yes, both the training and production simulations can be run on a compatible GPU when training/running M3GNet.
Running on the GPU results in significant speedup so it is recommended to do so.
To use the GPU you must install a GPU-compatible version of M3GNet or other machine learning backends.
See the MLPotential and ParAMS documentations.
Note
The engines typically used for DFT reference calculations, like ADF, BAND, and the AMS-bundled version of Quantum ESPRESSO, cannot run on the GPU.
The Active Learning procedure repeatedly switches between ML training, ML production simulations, and reference calculations.
What kinds of MD simulations can I run?¶
Simple Active Learning is compatible with (almost) all types of MD simulations supported by the AMS Driver.
Type |
Comment |
|
|---|---|---|
✔ |
NVE |
|
✔ |
NVT |
|
✔ |
NPT |
|
✔ |
Temperature ramping |
|
✔ |
Multiple thermostats (thermal conductivity) |
|
✔ |
Molecule gun or sink (CVD, ALD) |
|
✔ |
CREST metadynamics |
|
✔ |
Constraints (e.g., fixed positions) |
|
✔ |
Apply force or velocity (friction and viscosity) |
|
✔ |
Lattice deformation linear |
Use Steps%Type = Linear | example |
✔ |
Reaction boost force |
Use committee uncertainties | example |
✔ |
Reaction boost target coordinate |
Use Steps%Type = Linear | example |
✔ |
Force-bias Monte Carlo (fbMC) |
|
(✔) |
Lattice deformation periodic |
Difficult setup to get good training/validation sets |
(✔) |
Nanoreactor |
Difficult setup to get good training/validation data |
❌ |
Very high temperatures (combustion) |
The workflow automatically considers very high temperatures (> 5000 K) to be unrealistic and assumes that they are artifacts of the model |