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We’re pleased to announce the full release of the Sage 2.3.0 force field! This is identical to the previous release candidate Sage 2.3.0rc2. Sage 2.3.0 is the first OpenFF force field to use the AshGC neural network charge model. github.com/openforcefie... #compchem

github.comRelease Sage 2.3.0 · openforcefield/openff-forcefieldsThis release adds openff-2.3.0.offxml and openff_unconstrained-2.3.0.offxml. Sage 2.3.0 is the first OpenFF force field to use the AshGC neural network charge model to assign charges. Both vdW para...

Sage 2.3.0 maintains or improves performance on all of our benchmarks except solvation free energies in nonaqueous solvents. Please try it out and let us know if you find any substantial improvements, regressions, or other issues in comparison to Sage 2.2.1!

The easiest way to try out Sage 2.3.0 is by creating a new environment with the latest OpenFF ForceFields: micromamba create -n openff -c conda-forge "openff-toolkit>=0.17" "openff-forcefields==2026.01.0" micromamba activate openff

And in Python: >>> from openff.toolkit import Molecule, ForceField >>> forcefield = ForceField("openff-2.3.0.offxml") >>> molecule = Molecule.from_smiles("CCO") >>> interchange = forcefield.create_interchange(molecule.to_topology())

More details on training and benchmarking Sage 2.3.0 are available in our preprint: bsky.app/profile/open...

Open Force Field@openforcefield.org

New preprint describing our GNN charge model, AshGC! Since QM methods of charge assignment scale poorly to larger molecules, and are also conformation dependent, AshGC leads to major performance improvements in this critical step in force field parameterization. chemrxiv.org/engage/chemr...

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