AIMNet2
AIMNet2 is a neural network potential that provides broad element coverage (14 elements) with ωB97M-D3BJ accuracy. It is one of only two models in MAPLE (along with UMA) that natively supports charged and open-shell molecular systems.
Variants
| Model | Keyword | Elements | Description |
|---|---|---|---|
| AIMNet2 | aimnet2 |
H, B, C, N, O, F, Si, P, S, Cl, As, Se, Br, I | Standard variant with ωB97M-D3BJ accuracy |
| AIMNet2-NSE | aimnet2nse |
H, B, C, N, O, F, Si, P, S, Cl, As, Se, Br, I | Variant including nuclear spin-orbit effects for heavy elements |
Charge and Spin Support
AIMNet2 natively handles charged species and different spin multiplicities. Specify charge and multiplicity in the coordinate block:
#model=aimnet2
#opt(method=lbfgs)
-1 1
C 0.000000 0.000000 0.000000
O 1.250000 0.000000 0.000000
O -1.250000 0.000000 0.000000
The first line specifies charge multiplicity (here: charge = −1, multiplicity = 1 for a formate anion).
Implicit Solvation
AIMNet2 supports GBSA implicit solvation correction. QEq charges are computed automatically:
#model=aimnet2
#solv(method=gbsa, implicit=water)
#opt(method=lbfgs)
-1 1
C 0.000000 0.000000 0.000000
O 1.250000 0.000000 0.000000
O -1.250000 0.000000 0.000000
Usage Examples
Optimization with heavy elements (Br, I)
#model=aimnet2
#device=gpu0
#opt(method=lbfgs)
0 1
C 0.000000 0.000000 0.000000
Br 1.940000 0.000000 0.000000
H -0.390000 0.000000 1.028000
H -0.390000 0.890000 -0.514000
H -0.390000 -0.890000 -0.514000
NSE variant for systems with heavy-element spin-orbit effects
#model=aimnet2nse
#device=gpu0
#opt(method=lbfgs)
0 1
C 0.000000 0.000000 0.000000
I 2.140000 0.000000 0.000000
H -0.390000 0.000000 1.028000
H -0.390000 0.890000 -0.514000
H -0.390000 -0.890000 -0.514000
Limitations
- No D4 dispersion. The ωB97M-D3BJ training already includes dispersion corrections.
- No periodic systems. AIMNet2 does not support periodic boundary conditions.
- 14 elements only. Systems with elements outside the supported set (e.g., transition metals) require
umainstead.
