SAPT(KS) calculations and their many-body extension, XSAPT(KS), uses a
Kohn-Sham DFT description of the monomers in order to introduce
intramolecular electron correlation in a low-cost way, then described
the intermolecular interactions using second-order SAPT. As mentioned
in The resulting interaction energies, however, are not of benchmark quality
even when tuned LRC functionals are employed,
690
J. Chem. Phys.
(2014),
140,
pp. 044108.
Link
because although
the use of DFT for the monomers often improves the description of hydrogen
bonding (relative to Hartree-Fock-based SAPT0 calculations), the description of
dispersion often deteriorates.
498
Phys. Chem. Chem. Phys.
(2012),
14,
pp. 7679.
Link
In any case, SAPT0
dispersion is not of benchmark quality anyway, as it suffers from the usual MP2
overestimation of dispersion. At the same time the dispersion and
exchange-dispersion terms are the most expensive parts of a SAPT0 or SAPT(KS)
calculation, with a formal scaling of and ,
respectively, with respect to system size. Other terms in SAPT0 scale no
worse than and can be computed efficiently for large monomers using
an atomic orbital (AO)-based implementation of the non-dispersion terms in
SAPT.
693
J. Chem. Theory Comput.
(2018),
14,
pp. 2955.
Link
In view of this, both the efficiency and the accuracy of XSAPT(KS) calculations
is improved if second-order dispersion, i.e., in Eqs (12.58) and
(12.62), is replaced by an ad hoc atom–atom dispersion
potential of the variety. This is reminiscent of
dispersion-corrected DFT or DFT-D, as described in Section 5.7.3.
Unlike the situation in DFT, however, the dispersion energy is well-defined and
separable within the SAPT formalism, so it can be replaced by atom–atom
potentials without any fear of double counting of correlation effects, as there
inevitably is in DFT-D. Moreover, in the present case the dispersion
potentials can be fit directly to ab initio dispersion energies from
high-level SAPT calculations [SAPT(DFT) and SAPT2+(3)], since the dispersion
contribution is separable. As such, while the dispersion potentials that are
described here are classical in form and do contain fitting parameters, they
can nevertheless reasonably be described as ab initio dispersion
potentials. We therefore describe this method as
“+aiD”,
693
J. Chem. Theory Comput.
(2018),
14,
pp. 2955.
Link
to distinguish it from the “+D” dispersion
corrections of DFT-D, although we simply called it “+D” in earlier
work.
688
J. Phys. Chem. Lett.
(2012),
3,
pp. 3241.
Link
,
689
J. Chem. Phys.
(2013),
139,
pp. 034107.
Link
,
691
J. Phys. Chem. A
(2015),
119,
pp. 235.
Link
The composite method is called
XSAPT(KS)+aiD; see Ref.
689
J. Chem. Phys.
(2013),
139,
pp. 034107.
Link
for an overview and
Ref.
693
J. Chem. Theory Comput.
(2018),
14,
pp. 2955.
Link
for an efficient implementation in the AO basis.
The latter version exhibits scaling without significant memory
bottlenecks, and is applicable to supramolecular complexes whose monomers
contain atoms.
693
J. Chem. Theory Comput.
(2018),
14,
pp. 2955.
Link
To request an XSAPT(KS)+aiD calculation, set JOBTYPE =
XSAPT in the $rem section to perform XSAPT, with an appropriate
choice of SCF method (Hartree-Fock or DFT). The +aiD part of the
algorithm is invoked by two keywords in the $sapt input section: first, set
Algorithm to AO to select the AO-based version of
XSAPT; and second, set Dispersion equal to aiD, aiD2, aiD3, or MBD.
The latter choices correspond, respectively, to the “first generation" (+aiD1)
potential,
688
J. Phys. Chem. Lett.
(2012),
3,
pp. 3241.
Link
the second-generation (+aiD2)
potential,
689
J. Chem. Phys.
(2013),
139,
pp. 034107.
Link
, the third-generation (+aiD3) dispersion
potential,
691
J. Phys. Chem. A
(2015),
119,
pp. 235.
Link
or the many-body dispersion (+MBD) potential.
174
J. Phys. Chem. Lett.
(2019),
10,
pp. 2706.
Link
All four versions exhibit similar performance for
total interaction energies in small molecules,
691
J. Phys. Chem. A
(2015),
119,
pp. 235.
Link
,
174
J. Phys. Chem. Lett.
(2019),
10,
pp. 2706.
Link
but
unlike its successors, the
+aiD1 potential was fit to reproduce total interaction energies rather than
being fit directly to ab initio dispersion data, and as a consequence
does a much poorer job of reproducing individual energy components. (It was
later discovered that the performance of +aiD1 benefits from some error
cancellation amongst energy components,
689
J. Chem. Phys.
(2013),
139,
pp. 034107.
Link
,
691
J. Phys. Chem. A
(2015),
119,
pp. 235.
Link
and as such
its use is not recommended.) The difference between +aiD2 and
+aiD3 is a larger training set for the latter, which was designed to
afford better coverage of -stacked systems. As such, the +aiD3 correction
is the superior choice out of the pairwise potentials in the +aiD suite of methods.
The first three generations of +aiD potentials make the pairwise approximation, where the interaction potential is assumed to be additive across all pairs of atoms. The pairwise dispersion approximation employs sums over atom pairs of the form,
(12.65) |
where and are nuclei in molecules and , respectively.
The pairwise approximation breaks down in the limit of very large systems because
the interactions between atom pairs are modulated by the local electrodynamic environment
in the molecule. It was discovered that even the +aiD3 potential (the best of the pairwise +aiD potentials)
suffers from this approximation in large systems,
693
J. Chem. Theory Comput.
(2018),
14,
pp. 2955.
Link
and a correction based on the difference
between XSAPT and SAPT dispersion energies was proposed.
694
J. Chem. Theory Comput.
(2018),
14,
pp. 5128.
Link
While this correction performs well, all of the pairwise dispersion potentials (+aiD1, +aiD2, and +aiD3)
are rather ad hoc and their corrections do not depend on the applied level of theory.
The most recent +MBD potential uses a modified version of the
many-body dispersion potential of Ambrosetti et al.
41
J. Chem. Phys.
(2014),
140,
pp. 18A508.
Link
(see Section 5.7.6
in order to naturally account for nonadditive dispersion effects.
174
J. Phys. Chem. Lett.
(2019),
10,
pp. 2706.
Link
Because the +MBD method is based on the electron density it is much more
connected to the ab initio method being used, and this is presently the more accurate version of XSAPT.
173
Acc. Chem. Res.
(2021),
54,
pp. 3679.
Link
When combined with the XSAPT procedure, the XSAPT+MBD energy decomposition accounts
for nonadditive polarization and dispersion effects. Due to its excellent performance regardless of
system size, the +MBD potential (Dispersion MBD) is recommended,
but the +aiD3 potential (Dispersion aiD3) remains quite good for smaller systems.
As with XPol, the XSAPT and XSAPT(KS)+aiD methods do not function with
a solvation model or with external changes. Only single-point energies are
available, and frozen orbitals orbitals are not allowed. Both restricted and
unrestricted versions are available. Researchers who use XSAPT(KS)+aiD
are asked to cite Ref.
688
J. Phys. Chem. Lett.
(2012),
3,
pp. 3241.
Link
for +aiD1,
Ref.
689
J. Chem. Phys.
(2013),
139,
pp. 034107.
Link
for +aiD2, Ref.
691
J. Phys. Chem. A
(2015),
119,
pp. 235.
Link
for
+aiD3, or Ref.
174
J. Phys. Chem. Lett.
(2019),
10,
pp. 2706.
Link
for +MBD, along with Ref.
693
J. Chem. Theory Comput.
(2018),
14,
pp. 2955.
Link
for the AO-based version of XSAPT.
Dispersion
Requests a +aiD dispersion potential.
INPUT SECTION: $sapt
TYPE:
STRING
DEFAULT:
aiD3
OPTIONS:
aiD
First-generation pairwise dispersion potential
aiD2
Second-generation pairwise dispersion potential
aiD3
Third-generation pairwise dispersion potential
MBD
Many-body dispersion potential
RECOMMENDATION:
Use MBD. The aiD2, aiD3, and MBD potentials were
parameterized using ab initio dispersion data and afford accurate energy
components, in addition to accurate total interaction energies. The
aiD3 potential was parameterized using an expanded data set designed
to reduce some large errors observed for -stacked complexes using
aiD2. The MBD potential accounts for many-body dispersion
effects that are very important even in moderately large systems.