PySCF Support

Compatibility layer for supporting DFT-D4 in pyscf.

class dftd4.pyscf.DFTD4Dispersion(*args, **kwargs)

Implementation of the interface for using DFT-D4 in pyscf.

Examples

>>> from pyscf import gto
>>> import dftd4.pyscf as disp
>>> mol = gto.M(
...     atom='''
...          C   -0.755422531  -0.796459123  -1.023590391
...          C    0.634274834  -0.880017014  -1.075233285
...          C    1.406955202   0.199695367  -0.653144334
...          C    0.798863737   1.361204515  -0.180597909
...          C   -0.593166787   1.434312023  -0.133597923
...          C   -1.376239198   0.359205222  -0.553258516
...          I   -1.514344238   3.173268101   0.573601106
...          H    1.110906949  -1.778801728  -1.440619836
...          H    1.399172302   2.197767355   0.147412751
...          H    2.486417780   0.142466525  -0.689380574
...          H   -2.454252250   0.422581120  -0.512807958
...          H   -1.362353593  -1.630564523  -1.348743149
...          S   -3.112683203   6.289227834   1.226984439
...          H   -4.328789697   5.797771251   0.973373089
...          C   -2.689135032   6.703163830  -0.489062886
...          H   -1.684433029   7.115457372  -0.460265708
...          H   -2.683867206   5.816530502  -1.115183775
...          H   -3.365330613   7.451201412  -0.890098894
...          '''
... )
>>> d4 = disp.DFTD4Dispersion(mol, xc="r2SCAN")
>>> d4.kernel()[0]
array(-0.0050011)

dump_flags(verbose=None)

Show options used for the DFT-D4 dispersion correction.

kernel()

Compute the DFT-D4 dispersion correction.

The dispersion model as well as the parameters are created locally and not part of the state of the instance.

Returns:

The energy and gradient of the DFT-D4 dispersion correction.

Return type:

float, ndarray

reset(mol)

Reset mol and clean up relevant attributes for scanner mode

dftd4.pyscf.energy(mf)

Apply DFT-D4 corrections to SCF or MCSCF methods by returning an instance of a new class built from the original instances class.

Parameters:

mf – The method to which DFT-D4 corrections will be applied.

Return type:

The method with DFT-D4 corrections applied.

Examples

>>> from pyscf import gto, scf
>>> import dftd4.pyscf as disp
>>> mol = gto.M(
...     atom='''
...          N  -1.57871857  -0.04661102   0.00000000
...          N   1.57871857   0.04661102   0.00000000
...          H  -2.15862174   0.13639605   0.80956529
...          H  -0.84947130   0.65819321   0.00000000
...          H  -2.15862174   0.13639605  -0.80956529
...          H   2.15862174  -0.13639605  -0.80956529
...          H   0.84947130  -0.65819321   0.00000000
...          H   2.15862174  -0.13639605   0.80956529
...          '''
... )
>>> mf = disp.energy(scf.RHF(mol)).run()
converged SCF energy = -110.917424528592
>>> mf.kernel()
-110.917424528592

dftd4.pyscf.grad(mfgrad)

Apply DFT-D4 corrections to SCF or MCSCF nuclear gradients methods by returning an instance of a new class built from the original class.

Parameters:

mfgrad – The method to which DFT-D4 corrections will be applied.

Return type:

The method with DFT-D4 corrections applied.

Examples

>>> from pyscf import gto, scf
>>> import dftd4.pyscf as disp
>>> mol = gto.M(
...     atom='''
...          O  -1.65542061  -0.12330038   0.00000000
...          O   1.24621244   0.10268870   0.00000000
...          H  -0.70409026   0.03193167   0.00000000
...          H  -2.03867273   0.75372294   0.00000000
...          H   1.57598558  -0.38252146  -0.75856129
...          H   1.57598558  -0.38252146   0.75856129
...          '''
... )
>>> grad = disp.energy(scf.RHF(mol)).run().nuc_grad_method()
converged SCF energy = -149.939098424774
>>> g = grad.kernel()
--------------- DFTD4 gradients ---------------
         x                y                z
0 O     0.0172438133     0.0508406920     0.0000000000
1 O     0.0380018285    -0.0460223790    -0.0000000000
2 H    -0.0305058266    -0.0126478132    -0.0000000000
3 H     0.0069233858    -0.0382898692    -0.0000000000
4 H    -0.0158316004     0.0230596847     0.0218908543
5 H    -0.0158316004     0.0230596847    -0.0218908543
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