AIMNet2 Backend
AIMNet2 is a machine-learning-potential backend available in PyAR. It is useful when you want fast molecular energy and force evaluations without calling an external quantum-chemistry executable.
When to use AIMNet2
Use aimnet_2 when you want:
fast optimisation of molecular structures
a machine-learning-potential route for aggregation, solvation, or reaction exploration
AFIR/geomeTRIC reaction searches without relying on Turbomole coordinate updates
Example commands
Molecular cluster search:
pyar-cli -s water.xyz water.xyz --software aimnet_2 -ss 10 -N 16 -c 0 0 -m 1 1
Reaction search:
pyar-cli react A.xyz B.xyz -N 8 -gmin 100 -gmax 1000 --software aimnet_2
Practical notes
PyAR bundles AIMNet2 model assets for its AIMNet2 interfaces.
AIMNet2 is a third-party project from the Isayev Lab and is MIT licensed upstream. See
THIRD_PARTY_LICENSES/AIMNet2-LICENSEandTHIRD_PARTY_LICENSES/AIMNet2-PROVENANCE.md.As with all ML potentials, use AIMNet2 aggressively for exploration but validate important structures and energetics with an appropriate higher-level method.
AFIR/geomeTRIC status
aimnet_2 is registered as an energy-gradient provider for the
geomeTRIC-backed AFIR reaction route.