UPET is a family of universal interatomic potentials for advanced materials modeling across the periodic table. These models are based on the Point Edge Transformer (PET) architecture, trained on a variety of popular atomistic datasets, and capable of predicting energies and forces in complex atomistic workflows.
The package also ships PET-MAD-DOS, a universal model for predicting the electronic density of states (DOS) of materials and molecules, as well as their Fermi levels and bandgaps. PET-MAD-DOS uses a slightly modified PET architecture and is trained on the MAD dataset.
Note
The PET-MAD-1.5 models, trained for 102 elements at the r2SCAN level of theory, are now available. These models are more robust, more accurate and faster than the previous PET-MAD models. We highly recommend using them for all applications, especially molecular dynamics simulations.
from upet.calculator import UPETCalculator
calculator = UPETCalculator(model="pet-mad-s", version="1.5.0", device="cuda")
Note
Are you here to try our Matbench model? Here is all you need. Don’t be scared by the parameter count — our model is much faster than you might think. It is excellent for convex hull energies, geometry optimization and phonons, but we highly recommend the lighter and more universal PET-MAD for molecular dynamics.
from upet.calculator import UPETCalculator
calculator = UPETCalculator(model="pet-oam-xl", version="1.0.0", device="cuda")
Warning
This repository is the successor of the PET-MAD repository, which is now
deprecated. The package has been renamed to UPET to reflect the
broader scope of the models and functionalities it provides, which now
go beyond the original PET-MAD model. Please use version 1.4.4 of
the pet-mad package if you need the old API. The older version of
the README and
a migration guide
are available in the repository.
Key features¶
Universality: UPET models are generally applicable, and can be used for predicting energies and forces, as well as the density of states, Fermi levels, and bandgaps for a wide range of materials and molecules.
Accuracy: UPET models achieve excellent accuracies in various types of atomistic simulations of organic and inorganic systems.
Efficiency: UPET models are highly computationally efficient and have low memory usage, which makes them suitable for large-scale simulations.
Infrastructure: Various MD engines are available for diverse research and application needs.
HPC compatibility: Efficient in HPC environments for extensive simulations.
Maintainers¶
This project is maintained by @abmazitov and @frostedoyster, who will reply to issues and pull requests opened on the repository as soon as possible. You can mention them directly if you have not received an answer after a couple of days.