AIMNet2

What is AIMNet2?

AIMNet2 is a neural network potential for quantum-informed molecular property prediction. Given a coordinate-bearing molecular structure, AIMNet2 predicts energies, forces, atomic charges, NSE spin charges, dipole vectors, stress tensors, and Hessians from its trained model families.

AIMNet2 is designed for isolated molecules and molecular clusters rather than protein-scale biomolecular simulation. It is useful when you need rapid energy, force, charge, or second-derivative estimates for supported organic and elemental-organic chemistry.

How to use AIMNet2 online

ProteinIQ runs AIMNet2 on cloud GPU infrastructure with no Python setup. Upload one or more 3D structure files, choose the model family, and submit the job.

Pricing

Jobs start at 25 credits. The quote scales with the number and approximate size of coordinate records. Ensemble uncertainty, Hessians, stress, and geometry optimization increase the quote. The displayed quote is calculated before submission; CIF atom counts are estimates because symmetry expansion occurs during parsing.

Input

Input

Details

Molecular structure

One to 20 XYZ, extended XYZ, V2000 SDF, MOL, PDB, CIF, MCIF, or mmCIF files with atomic coordinates. Each file may be up to 10 MB, with at most 10,000 atoms across the submitted structures. Every frame in a multi-frame XYZ file, every molecule in an SDF file, every PDB model, and every coordinate-bearing CIF block is calculated separately and counts toward the 20-structure limit. Convert V3000 records to V2000 or XYZ before submission.

SMILES strings are not accepted because AIMNet2 operates on explicit 3D coordinates. Generate a conformer first, then upload the coordinate-bearing structure.

AlphaFold-style mmCIF coordinate layouts cannot be read by AIMNet2's coordinate reader. Export the same coordinates as PDB or XYZ before uploading. These layouts are rejected before a job is created or credits are charged.

Settings

Setting	Description
Model	Selects the AIMNet2 model alias. aimnet2 is the general wB97M-D3 model. aimnet2-2025 is the recommended B97-3c model. aimnet2-nse is intended for radicals and open-shell systems. aimnet2-pd supports palladium chemistry. aimnet2-rxn is a reaction model for neutral H/C/N/O systems.
Model member	Selects member 0, 1, 2, or 3 of the model family. Default: 0. Ensemble uncertainty still evaluates all four members.
Charge	Net molecular charge, from -10 to 10. Default: 0. Native file metadata takes precedence over this fallback. The reaction model requires charge 0.
Multiplicity	Spin multiplicity, from 1 to 10. Default: 1. Native mult or spin file metadata takes precedence for NSE calculations. Use aimnet2-nse for radicals or open-shell systems.
Per-structure charges	Optional comma-separated integer charges in expanded input order. Explicit values override file charge metadata; leave empty to preserve file values and use the global Charge where metadata is absent.
Per-structure multiplicities	Optional comma-separated spin multiplicities in expanded input order. Explicit values override file spin metadata; leave empty to preserve file values and use the global Multiplicity where metadata is absent.
Calculate forces	Returns per-atom forces in eV/A. Enabled by default.
Deterministic inference	Enables AIMNet2 deterministic execution for reproducible inference. It can reduce GPU throughput and does not cover the Ewald or PME Coulomb kernels.
Calculate stress tensor	Requests a stress tensor for periodic inputs. Non-periodic molecules cannot return stress.
Calculate Hessian	Requests the 3N x 3N Hessian in eV/A^2. Default: off. Limited to 100 atoms and non-periodic systems. DSF is supported; Ewald and PME are incompatible with this non-periodic ASE calculation.
Optimize geometry	Runs an ASE geometry optimization with AIMNet2 forces before final property reporting.
Geometry optimizer	Selects FIRE, BFGS, or LBFGS. Default: FIRE.
Optimization steps	Maximum geometry optimization steps, from 1 to 10,000. Default: 200.
Optimization fmax	Force convergence threshold in eV/A, from 0.001 to 5. Default: 0.05.
Ensemble uncertainty	Runs all four AIMNet2 ensemble members for the selected model family and reports energy mean, variance, and standard deviation.
Long-range Coulomb	Optional AIMNet2 Coulomb method: default, simple, DSF, Ewald, or PME. The simple method evaluates all atom pairs. DSF uses cutoff 15 A and alpha 0.2 by default. Ewald and PME use accuracy 1e-6 by default.
Coulomb correction	Uses the model's native default, explicitly enables, or disables the Coulomb correction. Default: native model default.
Dispersion correction	Uses the model's native default, explicitly enables, or disables dispersion. Default: native model default.
D3 cutoff	Dispersion cutoff in Angstrom. The AIMNet2 default is 15 A with smoothing fraction 0.2.

Outputs

The Results table reports one row per submitted structure:

Column	Description
Input	Input file or structure name
Model	AIMNet2 model alias
Atoms	Atom count
Charge	Net molecular charge used for calculation
Multiplicity	Spin multiplicity used for calculation
Energy (eV)	Total predicted molecular energy
Energy (kcal/mol)	Energy converted from eV
Max force (eV/A)	Largest force-vector norm when forces are requested
Charge sum (e)	Sum of AIMNet2 atomic charges
Spin-charge sum (e)	Sum of per-atom spin charges for aimnet2-nse
Dipole moment (eA)	Norm of the AIMNet2 dipole vector
Dipole x/y/z (eA)	Cartesian components of the AIMNet2 dipole vector
Ensemble members	Number of model members used when ensemble uncertainty is enabled
Ensemble mean energy (eV)	Mean energy across ensemble members
Ensemble energy SD (eV)	Standard deviation of ensemble-member energies
Optimization converged	Whether geometry optimization reached the requested force threshold
Optimization steps	Number of optimization steps completed
Optimizer	FIRE, BFGS, or LBFGS optimizer used
Optimization trajectory	Downloadable extended XYZ trajectory
Stress available	Whether stress output was returned
Hessian available	Whether Hessian output was returned

Downloadable files include:

File	Description
Original input file	Unchanged submitted coordinate content. For multi-record files, each calculation retains the full original file; its summary identifies the selected zero-based record index.
aimnet2_summary.json	Settings, scalar properties, dipole vector, source provenance, and file manifest
aimnet2_atomic_charges.csv	Atom index, element, coordinates, AIMNet2 charge, and NSE spin charge when available
aimnet2_forces.csv	Atom index, element, coordinates, and force components when forces are requested
aimnet2_stress.csv	Labeled 3 x 3 stress-tensor components in eV/A^3 when stress is requested and supported
aimnet2_hessian.csv	Hessian matrix when requested and supported
aimnet2_optimized.*	Final optimized coordinates when geometry optimization is enabled
aimnet2_optimization.log	ASE optimization log when geometry optimization is enabled
aimnet2_optimization_trajectory.extxyz	Initial and final coordinates plus optimization-step snapshots; large jobs are sampled to keep the file bounded
aimnet2_ensemble_uncertainty.csv	Per-member ensemble energies when ensemble uncertainty is enabled
aimnet2_run.log	Calculation diagnostics and captured warnings

Batch jobs prefix downloadable filenames with each input name so files remain unique.

Workflow outputs include the results table, summaries, charges, and run logs, plus forces, stress, Hessians, ensemble energies, optimized coordinates, and trajectories when requested. Optimization keeps the results table available.

Model coverage

The standard AIMNet2 models support H, B, C, N, O, F, Si, P, S, Cl, As, Se, Br, and I. The Pd model supports H, B, C, N, O, F, Si, P, S, Cl, Se, Br, Pd, and I. The reaction model supports H, C, N, and O only and requires a neutral net charge.

Use aimnet2-nse for open-shell systems. Use aimnet2-pd for supported palladium chemistry. Use aimnet2-rxn only for neutral H/C/N/O reaction systems.

For charged structures, the dipole vector depends on the coordinate origin. Compare charged-system dipoles only when the structures use a consistent origin.

Limitations

• AIMNet2 is trained for isolated molecules and molecular clusters, not bulk materials, extended surfaces, or metallic systems.
• Alkali and alkaline earth metals are not supported. Transition metals are not supported except Pd in aimnet2-pd.
• aimnet2-rxn only supports neutral H/C/N/O systems.
• Standard models do not include implicit solvation. The Pd model includes the training solvation assumptions from its model family.
• Multi-reference chemistry and systems far outside the training chemistry should be interpreted cautiously.

ProteinIQ runs AIMNet source commit 5916fe76c96d2af00f64359b8db6b7ead0b595b5, identified in results as 0.2.0+5916fe7. AIMNet verifies SHA-256 digests for all 24 registered model artifacts before loading them.