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ANI Models

The ANI (Accurate NeurAl networK engINe for Molecular Energies) family is a set of neural network potentials developed by the Roitberg group. ANI models are among the fastest ML potentials available, making them ideal for high-throughput screening and rapid prototyping of organic molecular systems.

Available Variants

Model Keyword Elements Training Level Best For
ANI-2x ani2x H, C, N, O, F, S, Cl ωB97X / 6-31G(d) General organic chemistry with halogens
ANI-1x ani1x H, C, N, O ωB97X / 6-31G(d) Fast calculations on HCNO-only systems
ANI-1ccx ani1ccx H, C, N, O CCSD(T)/CBS (transfer-learned) Publication-quality accuracy for small molecules
ANI-1xnr ani1xnr H, C, N, O ωB97X / 6-31G(d) (non-reactive) Equilibrium geometries without bond-breaking

DFT-D4 Dispersion Correction

ANI models are the only models in MAPLE that support the DFT-D4 dispersion correction. D4 adds London dispersion (van der Waals) interactions, which is critical for non-covalent binding, molecular stacking, and conformational energetics.

#model=ani2x
#d4
#opt(method=lbfgs)

Tip

Always enable #d4 when studying systems with significant non-covalent interactions (hydrogen bonds, pi-stacking, host-guest complexes). The computational overhead is minimal.

Usage Examples

General organic optimization

#model=ani2x
#device=gpu0
#opt(method=lbfgs)

0 1
C    0.000000    0.000000    0.000000
O    1.200000    0.000000    0.000000
H   -0.540000    0.940000    0.000000
H   -0.540000   -0.940000    0.000000

High-accuracy with coupled-cluster potential

#model=ani1ccx
#device=gpu0
#opt(method=lbfgs, convergence=extratight)

0 1
O    0.000000    0.000000    0.117300
H    0.000000    0.756900   -0.469200
H    0.000000   -0.756900   -0.469200

With D4 dispersion for non-covalent interactions

#model=ani2x
#d4
#device=gpu0
#opt(method=lbfgs, convergence=tight)

XYZ /path/to/dimer_complex.xyz

Limitations

  • No charge/multiplicity support. ANI models always assume neutral, singlet ground state. Charged or open-shell species will be treated as neutral singlets without warning.
  • Limited elements. ANI-2x covers 7 elements; ANI-1x/1ccx/1xnr cover only H, C, N, O.
  • No periodic systems. ANI models do not support periodic boundary conditions.
  • No implicit solvation. GBSA solvation is not available for ANI models.