Szymon Śmiga1, Fabio Della Sala2,3, Paola Gori-Giorgi4, Eduardo Fabiano2,3. 1. Institute of Physics, Faculty of Physics, Astronomy and Informatics, Nicolaus Copernicus University in Toruń, ul. Grudziądzka 5, 87-100 Toruń, Poland. 2. Institute for Microelectronics and Microsystems (CNR-IMM), Campus Unisalento, Lecce, Via Monteroni 73100, Italy. 3. Center for Biomolecular Nanotechnologies, Istituto Italiano di Tecnologia, Via Barsanti 14, Arnesano, Lecce 73010, Italy. 4. Department of Chemistry & Pharmaceutical Sciences and Amsterdam Institute of Molecular and Life Sciences (AIMMS), Faculty of Science, Vrije Universiteit, De Boelelaan 1083, 1081HV Amsterdam, The Netherlands.
Abstract
Adiabatic connection models (ACMs), which interpolate between the limits of weak and strong interaction, are powerful tools to build accurate exchange-correlation functionals. If the exact weak-interaction expansion from the second-order perturbation theory is included, a self-consistent implementation of these functionals is challenging and still absent in the literature. In this work, we fill this gap by presenting a fully self-consistent-field (SCF) implementation of some popular ACM functionals. While using second-order perturbation theory at weak interactions, we have also introduced new generalized gradient approximations (GGAs), beyond the usual point-charge-plus-continuum model, for the first two leading terms at strong interactions, which are crucial to ensure robustness and reliability. We then assess the SCF-ACM functionals for molecular systems and for prototypical strong-correlation problems. We find that they perform well for both the total energy and the electronic density and that the impact of SCF orbitals is directly connected to the accuracy of the ACM functional form. For the H2 dissociation, the SCF-ACM functionals yield significant improvements with respect to standard functionals also thanks to the use of the new GGAs for the strong-coupling functionals.
Adiabatic connection models (ACMs), which interpolate between the limits of weak and strong interaction, are powerful tools to build accurate exchange-correlation functionals. If the exact weak-interaction expansion from the second-order perturbation theory is included, a self-consistent implementation of these functionals is challenging and still absent in the literature. In this work, we fill this gap by presenting a fully self-consistent-field (SCF) implementation of some popular ACM functionals. While using second-order perturbation theory at weak interactions, we have also introduced new generalized gradient approximations (GGAs), beyond the usual point-charge-plus-continuum model, for the first two leading terms at strong interactions, which are crucial to ensure robustness and reliability. We then assess the SCF-ACM functionals for molecular systems and for prototypical strong-correlation problems. We find that they perform well for both the total energy and the electronic density and that the impact of SCF orbitals is directly connected to the accuracy of the ACM functional form. For the H2 dissociation, the SCF-ACM functionals yield significant improvements with respect to standard functionals also thanks to the use of the new GGAs for the strong-coupling functionals.
Kohn–Sham (KS)[1] density functional
theory (DFT) is the most used electronic structure computational approach
for molecular and solid-state systems.[2−4] Its accuracy depends
on the choice of the approximation for the exchange–correlation
(XC) functional[5−7] which, at the highest-rung of the Jacob’s
ladder,[8] involves all the occupied and
virtual KS orbitals as well as the eigenvalues. Then, the XC approximation
is no more an explicit functional of the density and, to stay within
the pure KS formalism, the optimized effective potential (OEP) method[9,10] must be employed. Early OEP approaches included exact-exchange (EXX)
and approximated the correlation using the second-order Görling–Levy
perturbation theory (GL2).[11] However, this
led to a large overestimation of correlation effects and to convergence
problems.[12−18]Actually two different main approaches have been explored
to solve
this issue: going beyond the second-order approximation[19−26] or using a semicanonical transformation.[12,13,18] Another possible path is the adiabatic connection
(AC) formalism[27−29] which is a general, powerful tool for the development
of XC functionals. For several decades, it has been used to justify
the introduction of hybrid[30−32] and double hybrid (DH) functionals[33−35] and successively it has been directly employed to construct high-level
XC functionals based on AC models (ACM) interpolating between known
limits of the AC integrand.[36−43] Recently, it has also been employed in the context of the Hartree–Fock
(HF) theory[44,45] to develop corrections to the
Møller–Plesset perturbation series.[46]The XC functionals based on ACMs have the general
formwhere , with W0 = Ex being the exact exchange energy, W0′ =
2EcGL2 being twice the GL2 correlation energy,[11] and W∞ and W∞′ being the indirect part of the minimum expectation value of the
electron–electron repulsion for a given density and the potential
energy of coupled zero-point oscillations around this minimum, respectively.[39,47] The model WλACM is designed to mimic the exact but unknown Wλ, in particular by considering the known
asymptotic expansions[11,39,40,47]In recent
years, several ACMs have been tested for various chemical
applications showing promising results,[48,49] especially
in the description of non-covalent interactions.[46,50] However, most of these recent studies have been performed within
the HF–AC framework, that is, as post-HF calculations. Conversely,
little attention has been devoted to DFT-based ACM functionals. The
main reason for this is that in the HF case, the ACM is applied on
top of the HF ground state,[44,45] which is a simple and
well defined reference; on the contrary, in the DFT framework, the
ACM-based XC functional should be in principle applied inside the
KS equations in a self-consistent-field (SCF) fashion. This requirement
is not trivial because ACM-based functionals are in general not simple
explicit functionals of the density but are instead complicated expressions
depending on KS orbitals and orbital energies as well (through Ex and EcGL2). One notable exception are
the MCY functionals[51] which use semilocal
approximations to set the interpolation points along the AC integrand,
thus allowing for a relatively straightforward SCF implementation.
In the most general case considered in this work, however, ACM functionals
are fifth rung functionals and thus, in practice, also in the context
of DFT, they are always applied in a post-SCF scheme using precomputed
DFT densities and orbitals.[48,52] In this way, the results
depend significantly on the choice of the reference density and orbitals,
making the whole method not fully reliable.[48] On the other hand, an exploratory study of the XC potential derived
from ACM models has shown that this possesses promising features,
indicating that SCF calculations with ACM-based functionals might
be an interesting path to explore.[53]In this work, we tackle this issue by introducing an SCF implementation
of the ACM potential and applying it to some test problems in order
to verify its ability to describe different properties and systems.
One important aim of this work is in fact to measure and assess the
capabilities of some of the most popular ACM presently available in
literature. To this purpose the use of a proper SCF procedure is crucial
as the level of accuracy of such methods can be inspected independently
of an arbitrary reference ground-state as in previous works. In fact,
for any density functional, the energy error can be decomposed into
a contribution due to the approximate nature of the functional (intrinsic
error) and that due to the approximate density used in the calculation
(relaxation error).[54,55] When the functional is evaluated
on an arbitrary (non-SCF) density, the relaxation error may become
important and the whole performance can be influenced by the choice
of the density. Indeed, recent studies have shown how this effect
can be used to improve DFT results by choosing accurate non-SCF densities.[55,56] Nevertheless, within this framework, it is difficult to really understand
the accuracy of the functional form itself and therefore to plan new
advances. On the other hand, the use of a proper SCF procedure provides
a well-defined reference for assessing the intrinsic errors. This
is an extremely important point to clarify in view of future ACM developments.
Note that such a development of new and possibly more accurate ACMs
will instead not be covered in this work but left to upcoming publications.
The development work performed here will instead focus on a second
important goal aimed at solving some open problems with the ACM potential
that hinder its straightforward SCF implementation. These problems
originate mainly from the naive treatment used so far for the large-λ
contributions W∞ and W∞′ which causes an unphysical behavior in the ACM potential. Hence,
in this article, we develop new approximations for both W∞ and W∞′ that preserve the accuracy for
energies and remove the limitations on the potential side. As a byproduct
of this work, we obtain useful strong-correlation generalized gradient
approximations that prove to be very robust for the description of
the Harmonium atom and the H2 dissociation.In the
following, we present the theory behind SCF implementation
of ACM functionals and the construction of new W∞ and W∞′ approximations. Afterward, we
present some interesting preliminary results obtained for model and
real systems.
Theory
To perform SCF ACM calculations
we need to deal with the potential
arising from the functional derivative of the energy of eq , that is[53]where D = ∂fACM/∂j with j = Ex, EcGL2, W∞, W∞′. As discussed in ref (53), the potential in eq requires a combination
of OEP (for Ex and EcGL2) and generalized
gradient approximation (GGA) approaches
(for W∞ and W∞′).
Thus, it resembles the OEP–SCF implementation of the DH functionals
reported in refs (57) and (58). In more
details, the and functional derivatives are obtained by
solving the OEP equation which reads[9,10,12,59−61]with A = X, C denoting the exchange
and correlation
parts, respectively. The inhomogeneity on the right hand side of eq is given byand the static
KS linear response function
isAll quantities are evaluated using
orbitals ϕ and eigenvalues
ε in a given cycle of KS
SCF procedure (further details
can be found in refs (17), (57), (58), (62), and (63)). We note, however, that
there is a significant difference between ACM and DH approaches: in
the former, the coefficients and are not fixed empirical parameters as in
DH, but are well-defined (non-linear) functions of Ex, EcGL2, W∞, W∞′.[53]
Approximations for the
Strong-Interaction Limit
Another
important issue to consider in the SCF implementation of the ACMs
is related to the treatment of W∞ and W∞′, which describe the λ →
∞ limit of the AC integrand. It can be proven that both W∞ and W∞′ display
a highly non-local density dependence.[64−68] This is accurately described by the strictly correlated
electron (SCE) formalism,[39,47] which is however computationally
very demanding and nontrivial to evaluate. Therefore, the λ
→ ∞ limit is usually approximated by simple semilocal
gradient expansions (GEA) derived within the point-charge-plus-continuum
(PC) model[38]where is the reduced gradient
of the density, A = −9(4π/3)1/3/10, C = 1/2(3π)1/2, μ = −31/3(2π)2/3/35 ≈ −0.1403,
and μ = −0.7222
(slightly different estimates are possible for μ, see, e.g., refs (36) and (39)). The GEAs of eqs and 9 yield, at least for small atoms,
energies that are quite close to the accurate SCE values. However,
when s is large, for example, in the tail of an exponentially
decaying density, they fail, giving functional derivatives that diverge.[53] This is a severe drawback that does not allow
these approximations to be used directly in an SCF implementation.To remedy this limitation we consider here a simple GGA approximation,
named, harmonium PC (hPC) model, based on the Perdew–Burke–Ernzerhof
(PBE) exchange enhancement factor[69] that
recovers the GEAs of eqs and 9 in the slowly varying regime, is well
behaved everywhere, and reproduces as close as possible the SCE values
for both W∞ and W∞′. Thus, we havewhere κ = −7.11 and κ =
−99.11 have been fixed such that W∞hPC and W∞′hPC recover exactly the corresponding SCE values for
the harmonium atom at ω = 0.5:[70] with
this value, the degree of correlation resembles that of the He atom
and a simple analytical density is obtained. We note that a previous
attempt to develop GGAs for W∞ and W∞′, the modified PC (mPC) model of ref (71), yields results that are
quite far from both the PC and the SCE values, in particular W∞′ does not even recover the PC model in the small s limit. In fact, the mPC GGAs have been derived for the
quasi-two-dimensional density regime[71] and
their application in three-dimensional systems, for example for the
total correlation of atoms, is highly based on an error cancellation
between the quite inaccurate values of W∞ and W∞′.[71] In particular, has been
designed to compensate the inaccuracies
of WmPC for the ISI functional, but
this error compensation cannot work for other ACMs (especially those,
as SPL, using only W∞).To
understand the performances of the different approximations
for the strong-interaction functionals, we report in Figure the differences between the
values of W∞ and W∞′ computed with the two GGAs and the PC model, for the Hooke atom
at different confinement strengths ω. The corresponding values
for those instances of ω for which exact SCE reference data
are available are also reported in Table .
Figure 1
Differences between the values of W∞ and W∞′ computed with hPC and mPC formulas
and the corresponding W∞PC and W∞′PC data (ΔW∞method = W∞method – W∞PC; ΔW∞′method = W∞′method – W∞′PC) for the harmonium atom at various
values of the confinement strength ω. For reference, some available
accurate SCE values are also reported.[70]
Table 1
W∞ and W∞′ Energies (in Ha) for Three Values
of
ω for Which Hooke’s Atom has Analytical Solutions[72] and Exact SCE Reference Data Are Available[70]a
ω
SCE
PC
hPC
mPC
W∞
0.0365373
–0.170
–0.156
–0.167
–0.191
0.1
–0.304
–0.284
–0.303
–0.344
0.5
–0.743
–0.702
–0.743
–0.841
MARE
6.78%
0.70%
12.90%
W∞′
0.0365373
0.022
0.021
0.021
0.060
0.1
0.054
0.054
0.053
0.146
0.5
0.208
0.215
0.208
0.562
MARE
2.64%
2.13%
171.10%
Hooke’s atom is usually considered
to be in the strong correlation regime when the density displays a
maximum away from the center of the harmonic trap, which happens[73] for ω ≲ 0.0401. The last line of
each panel reports the MARE.
Differences between the values of W∞ and W∞′ computed with hPC and mPC formulas
and the corresponding W∞PC and W∞′PC data (ΔW∞method = W∞method – W∞PC; ΔW∞′method = W∞′method – W∞′PC) for the harmonium atom at various
values of the confinement strength ω. For reference, some available
accurate SCE values are also reported.[70]Hooke’s atom is usually considered
to be in the strong correlation regime when the density displays a
maximum away from the center of the harmonic trap, which happens[73] for ω ≲ 0.0401. The last line of
each panel reports the MARE.We see that, unlike mPC, the hPC model reproduces
very well both
the W∞ and W∞′ accurate
SCE values,[70] being comparable to and even
superior to the original PC model. This performance is not trivial
because hPC was parameterized only on a single instance of the Hooke’s
atom (ω = 0.5) but turns out to be very accurate for the whole
range of confinement strengths. In particular, Figure shows that in the small ω range (strong
interaction limit of the Hooke’s atom) hPC yields the best
estimation of the XC energy Exc = W∞ + 2W∞′, being slightly
better than PC, while the mPC method fails completely.
Figure 2
Comparison of the leading
term of the XC energy in the strong interacting
regime of the
Hooke’s atom calculated using different models with FCI data.[52]
Comparison of the leading
term of the XC energy in the strong interacting
regime of the
Hooke’s atom calculated using different models with FCI data.[52]An additional assessment
is provided in Table and Figure where
real atoms are considered both for SCE energies
and SCE potentials. Also in this case the results of the hPC functional
are in line with or better than the PC model, that was originally
parametrized against the He atom, indicating once more the robustness
of the hPC method. As anticipated, the mPC is instead quite far from
the reference, especially for W∞′.
Table 2
Values of W∞ and W∞′ for the He, Be, and Ne Atoms Obtained
from Different Models and Using EXX Densities; We Use Atomic Unitsa
SCE
PC
hPC
mPC
W∞
H
–0.3125
–0.3128
–0.3293
–0.4000
He
–1.500
–1.463
–1.492
–1.671
Be
–4.021
–3.943
–3.976
–4.380
Ne
–20.035
–20.018
–20.079
–21.022
MARE
1.15%
1.81%
13.31%
W∞′
H
0
0.0426
0.0255
0.2918
He
0.621
0.729
0.646
1.728
Be
2.59
2.919
2.600
6.167
Ne
22
24.425
23.045
38.644
MARE
13.71%
3.05%
130.67%
The results which agree best with
SCE values[39,47] are highlighted in bold. The
last line of each panel reports the MARE [for W∞′ the
H results are excluded]. The W∞′SCE reference data
are reported with the same precision of as in ref (39).
Figure 3
Comparison between (a) vxc∞(r) = δW∞/δρ(r) and
(b) vxc′∞(r) = δW∞′/δρ(r) potentials computed from different
models for the Ne atom (using EXX densities).
Comparison between (a) vxc∞(r) = δW∞/δρ(r) and
(b) vxc′∞(r) = δW∞′/δρ(r) potentials computed from different
models for the Ne atom (using EXX densities).The results which agree best with
SCE values[39,47] are highlighted in bold. The
last line of each panel reports the MARE [for W∞′ the
H results are excluded]. The W∞′SCE reference data
are reported with the same precision of as in ref (39).
Computation Details
All calculations
have been performed with a locally modified ACESII[74] software package. As in our previous studies,[17,53,57,58,62,63,75,76] in order to solve OEP
equations, we have employed the finite-basis set procedure of refs (77) and (78). In calculations, we employed
the basis sets detailed below and tight convergence criteria (SCF:
10–8). In general, the convergence criteria were
met within several cycles of the SCF procedure.In order to
solve algebraic OEP equations, the truncated singular-value
decomposition (TSVD) of the response matrix was employed. The cutoff
criteria in the TSVD procedure were set to 10–6.
For technical details on this type of calculations, we refer the reader
to refs (17) and (63).As reference data,
we have considered the coupled-cluster single
double and perturbative triple [CCSD(T)][79] results obtained in the same basis set in order to make a comparison
on the same footing and to reduce basis set related errors. In particular,
we have considered a comparison with CCSD(T) relaxed densities, the
corresponding KS potentials obtained via KS inversion,[80] and the total CCSD(T) energies. In the assessment,
we have considered several properties, that is:total energies: the
total energies have
been calculated for the systems listed in Table in ref (63) using an identical computational setup as in
the same paper. A summary of the employed basis sets is also reported
in the Supporting Information. We remark
that, although total energies are not very important in practical
chemical applications, they are important observables and are especially
useful as indicators of the quality of the ACM interpolation.Dipole moments: for selected
systems (H2O, HF, HCl, H2S, and CO), we have
calculated the
dipole moments using SCF densities for various methods. This is a
direct test of the quality of self-consistent densities obtained within
all approaches. The uncontracted aug-cc-pVTZ basis set of Dunning[81] was used for all systems together with geometries
taken from ref (82).HOMO and HOMO–LUMO gap
energies: as in refs (63) and (83), we have computed the
HOMO and HOMO–LUMO gaps, respectively, for the same set of
systems as in the case of total energies. In the case of HOMO energies,
the reference data have been taken from ref (83), whereas the HOMO–LUMO
gap energies have been obtained from applying the KS inversion method[80] taking as a starting point the CCSD(T) relaxed
density matrix as in ref (63).correlation potentials
and densities: as
in our previous studies,[17,63,84,85] here we also investigate the
quality of correlation potentials and densities[17,86,87] looking at their spatial behavior. Both
quantities are obtained from fully SCF calculations. The densities
are analyzed in terms of correlation densities defined as Δρc = ρmethod – ρX,
where ρX is the density obtained from the exact exchange
only (X = EXX)[60] or Hartree-Fock (HF) (X
= HF) calculations for DFT and WFT methods, respectively. The Ne atom
OEP calculations have been performed in a fully uncontracted ROOS-ATZP[88] basis set, whereas for the CO molecule, the
uncontracted cc-pVTZ[89] basis sets were
employed.dissociation of H: fully self-consistent and
post-SCF calculations, using
OEP EXX orbitals, have been performed in the spin restricted formalism
using the uncontracted aug-cc-pVTZ basis set. For comparison, PBE,
MP2, GL2@EXX, and FCI data are also reported.correlation energies of Hooke’s atoms: as previously,[52,90,91] we have performed the calculation
for various values of ω
in the Hooke’s atom model[92] ranging
between 0.03 (strong interaction) and 1000 (weak interaction) using
a even-tempered Gaussian basis set from ref (93). For comparison, the ACM
correlation energies have been calculated at both @EXX and @SCF reference
orbitals.
Results
We have
performed a series of SCF ACM calculations to investigate
the performance of these methods in the KS framework. In particular,
we have considered the interaction–strength–interpolation
(ISI)[36] and Seidl–Perdew–Levy
(SPL)[40] ACMs. Unless explicitly stated,
the hPC model has been used to describe the strong-interaction limit
in all calculations. Moreover the bare GL2 (for SCF calculations OEP-GL2[12]) approach is also reported. The ISI model for Wλ has in general a larger deviation from
linearity than SPL (which does not depend on W∞′ too),
whereas GL2 corresponds to the linear approximation Wλ = 2EGL2 λ. Thus,
the comparison of ISI with SPL and GL2 gives information on the importance
of the shape of the ACM interpolation form.In Table , we show
the total energies computed with the various methods for a test set
of 16 closed-shell atoms and small molecules, namely, He, Be, Ne,
Mg, Ar, HF, CO, H2O, H2, He2, Cl2, N2, Ne2, HCl, NH3, and
C2H6.
Table 3
Total Energies (Ha)
Calculated with
Different Methods Self-Consistently (@SCF) or on top of EXX Orbitals
(@EXX), for Several Functionalsa
@SCF
@EXX
system
ISI
SPL
GL2
ISI
SPL
GL2
CCSD(T)
He
–2.90089
–2.90043
–2.90780
–2.90191
–2.90148
–2.90925
–2.90253
Be
–14.67318
–14.67551
not. conv.
–14.67102
–14.67278
–14.69013
–14.66234
Ne
–128.93274
–128.94313
–128.98863
–128.92733
–128.93628
–128.97770
–128.89996
Mg
–199.86915
–199.86937
–199.88275
–199.86560
–199.86569
–199.87826
–199.82815
Ar
–527.51661
–527.53309
–527.58461
–527.51478
–527.53095
–527.58181
–527.45748
H2
–1.17039
–1.16972
–1.18107
–1.17019
–1.16953
–1.18060
–1.17273
He2
–5.80177
–5.80086
–5.81560
–5.80167
–5.80075
–5.81539
–5.80506
N2
–109.58263
–109.61715
–109.75090
–109.56105
–109.58609
–109.68725
–109.47628
Ne2
–257.86564
–257.88644
–257.97751
–257.85475
–257.87266
–257.95552
–257.80003
HF
–100.43787
–100.45019
–100.50368
–100.43148
–100.44188
–100.48965
–100.39579
CO
–113.35397
–113.38496
–113.51191
–113.32766
–113.34760
–113.43484
–113.25738
H2O
–76.42686
–76.44091
–76.50285
–76.42076
–76.43270
–76.48790
–76.38692
HCl
–460.58531
–460.58876
–460.61411
–460.58227
–460.58550
–460.61020
–460.50933
Cl2
–919.93674
–919.94378
–919.99349
–919.92413
–919.93022
–919.97763
–919.77032
NH3
–56.55283
–56.56435
–56.62446
–56.54859
–56.55876
–56.61412
–56.52332
C2H6
–79.80517
–79.82045
–79.92279
–79.79876
–79.81239
–79.90830
–79.76414
ME
–50.00
–61.08b
–120.85
–43.14
–52.09
–99.17
MAE
50.91
62.25b
120.85
43.96
53.16
99.17
MARE
0.055%
0.071%b
0.162%
0.048%
0.062%
0.150%
CCSD(T) results
are given as a reference.
The last rows report the mean error (ME, in mHA), MAE (in mHA), and
the MARE (in percent). For OEP–GL2, all the averages exclude
the Be atom that for this functional has not converged. Not. conv.—not
converged.
Without Be.
CCSD(T) results
are given as a reference.
The last rows report the mean error (ME, in mHA), MAE (in mHA), and
the MARE (in percent). For OEP–GL2, all the averages exclude
the Be atom that for this functional has not converged. Not. conv.—not
converged.Without Be.We see that ISI@SCF and SPL@SCF
perform quite well, giving errors
roughly half that of OEP–GL2. For comparison, we acknowledge
that the PBE functional[69] yields a mean
absolute relative error (MARE) of 0.11%, which is twice as large as
that of ISI@SCF.Nevertheless, we have to acknowledge that the
performance has further
margins of improvement. For example the MAEs of MP2 and OEP2-sc (not
reported) for the same test are 20 and 17 mHa, respectively. We can
trace back most of this difference to the fact that the use of KS
eigenvalues, as in ISI, SPL, and OEP–GL2, requires a quite
large AC curvature (i.e., second derivative with respect to λ)
to yield accurate results, whereas this is not the case for MP2 and
OEP2-sc that employ HF-quality eigenvalues. Then, KS-based methods
need much more accurate ACMs to compete with HF-based ones. This is
also confirmed observing that in Table , ISI is generally better than SPL, as the former is
a more advanced ACM than the latter.A second, related observation
is that the ISI and SPL results suffer
from a small relaxation error that worsens slightly the performance
(with respect to using EXX orbitals). This effect might be related
to the fact that the considered ACMs were developed in the context
of post-SCF calculations and, as a result, may include some inherent
error cancellation which is lost when they are evaluated using a (more
accurate) SCF density. To better understand this trend, we define
the quantitywhich considers the absolute
error difference
[with respect the reference, i.e., CCSD(T)] going from EXX orbitals
to SCF orbitals (a negative value means that SCF orbitals give better
accuracy than EXX orbitals). The values of Δ[E] for ISI, SPL, and OEP–GL2/GL2 are 7.0, 9.1, and 16.9 mHa,
respectively. Despite the Δ[E] values all being
positive (i.e., calculations using EXX orbitals are more accurate)
they decrease going from GL2 to SPL and then from SPL to ISI, showing
again that increasing the complexity/accuracy of the ACM can yield
better SCF potentials and relaxed total energies.Interestingly,
an opposite effect of the density relaxation is
found in the harmonium atom, as shown in Figure , where if we look at small values of the
confinement strength, where the relaxation becomes more important,
the SCF results are better with respect to the ones obtained using
EXX orbitals and density (for both ISI and SPL). This depends on the
fact that at these regimes, the true density is very different from
the EXX one, and thus, the SCF procedure produces a significant improvement
on the density. This also traces back to the use of hPC which yields
accurate strong-correlation potentials; we note in fact that the accuracy
of both ACMs with the hPC model is very high (compare, e.g., with Figure of ref (52)). Conversely using the
mPC model only ISI results are rather accurate because of error compensation
effects between the W∞mPC and the terms, while SPL ones, where only W∞mPC is used, are rather poor (see Figure S2 in the Supporting Information). This is an important
indication of the importance of using proper strong-correlation approximations,
delivering both good energies and potentials.
Figure 4
Relative error on correlation
energies of harmonium atoms for various
values of ω computed at @SCF and @EXX orbitals for ISI and SPL
functionals using the hPC model for the strong-interaction functionals.
The errors have been computed with respect to FCI data obtained in
the same basis set.[93] The exact ISI and
SPL values are taken from ref (70) and are obtained by inserting exact densities into the
ISI and SPL functionals, including the exact treatment (SCE) of the
strong-interaction limit.
Relative error on correlation
energies of harmonium atoms for various
values of ω computed at @SCF and @EXX orbitals for ISI and SPL
functionals using the hPC model for the strong-interaction functionals.
The errors have been computed with respect to FCI data obtained in
the same basis set.[93] The exact ISI and
SPL values are taken from ref (70) and are obtained by inserting exact densities into the
ISI and SPL functionals, including the exact treatment (SCE) of the
strong-interaction limit.In Table , we report
the dipole moments of some selected systems, from the SCF density.
The results for CO are reported separately because they are qualitatively
different and deserve a distinct analysis.
Table 4
Dipole
Moments (in Debye) for Some
Selected Systems Calculated Using Self-Consistent Densitiesa
MAE
method
H2O
HF
HCl
H2S
CCSD(T)
exp.
CO
OEPx
2.043
1.954
1.279
1.171
0.121
0.180
–0.265
GL2
1.616
1.531
1.061
1.004
0.187
0.145
1.703
SPL
1.758
1.654
1.085
1.024
0.110
0.080
0.940
ISI
1.809
1.699
1.093
1.030
0.083
0.060
0.692
OEP2-sc
1.885
1.786
1.185
1.094
0.018
0.073
0.355
CCSD(T)
1.904
1.809
1.170
1.079
0.065
0.153
Exp.
1.855
1.820
1.080
0.970
0.122
Experimental data are taken from
ref (82). The MAE of
H2O, HF, HCl, and H2S with respect to CCSD(T)
and experimental results is also reported.
Experimental data are taken from
ref (82). The MAE of
H2O, HF, HCl, and H2S with respect to CCSD(T)
and experimental results is also reported.For H2O, HF, HCl, and H2S, a
comparison with
the CCSD(T) data shows that ISI is quite effective in predicting the
dipole moments being slightly better than SPL and twice as good as
GL2 [for comparison PBE gives in this case a mean absolute error (MAE)
of 0.092 Debye with respect CCSD(T)]. Anyway, as already observed for the total energies, there are important
margins of improvement as testified by the OEP2-sc performance that
is definitely better than the ISI one. As already discussed, we can
trace back the limitations of ISI and SPL not only in part to relaxation
effects but also on the fact that, working in a pure SCF KS framework,
it is very hard for the ACM to provide a proper curvature of the AC
integrand curve as to get accurate KS orbital energies; consequently,
the orbital-dependent energies are also negatively affected. For the
case of CO, these effects are even more evident. In this case, in
fact, OEPx predicts a qualitatively wrong dipole moment but GL2 largely
over-corrects it, indicating that the linear behavior of the AC integrand
needs to be significantly improved. Both ISI and SPL can partially
achieve this task, halving the error with respect to GL2, but still
they yield quite overestimated dipole moments.As a next step,
we consider in Table the highest occupied molecular orbital (HOMO)–lowest
unoccupied molecular orbital (LUMO) gaps obtained from different methods.
As it could be expected both ACMs correct the general overestimation
of gaps given by the OEPx but in doing so, they overestimate the correlation
effects yielding gaps that are too small in most cases. Thus, we obtain
MAEs of 0.68 and 0.52 eV for SPL and ISI, respectively, to be compared
with the OEP2-sc MAE of 0.21 eV. We note anyway that the ISI and SPL
results are clearly better than conventional semilocal functionals
(PBE gives a MAE of 0.97 eV). Moreover, we note that by improving
the quality of the ACM (GE2 → SPL → ISI) the description
of the HOMO–LUMO gap is also significantly improved. Similar
considerations apply as well for the HOMO energies (see Table ). At the ISI level, the HOMO
is shifted to higher energy with the almost the same MARE as OEPx
(which is shifted to lower energy). Again, the ISI approach is better
than SPL and much better than GL2 (as well as PBE with a MARE of 38.3%).
Table 5
HOMO–LUMO Energy Gap (eV) for
Different Systems as Obtained from Several Methodsa
@SCF
system
OEPx
GL2
OEP2-sc
SPL
ISI
KS[CCSD(T)]
He
21.60
20.95
21.32
21.23
21.23
21.21
Be
3.57
not. conv.
3.63
3.40
3.47
3.61
Ne
18.48
14.12
16.45
15.17
15.60
17.00
Mg
3.18
3.40
3.33
3.38
3.38
3.36
Ar
11.80
10.95
11.43
11.08
11.17
11.51
H2
12.09
12.03
12.13
12.12
12.12
12.14
He2
21.28
20.64
21.02
20.81
20.81
20.56
N2
9.21
6.73
8.37
7.68
7.99
8.55
Ne2
17.84
13.49
15.75
14.41
14.83
16.23
HF
11.36
7.80
9.84
8.70
9.08
10.30
CO
7.77
5.87
7.22
6.68
6.90
7.29
H2O
8.44
5.99
7.49
6.73
7.03
7.75
HCl
7.82
7.10
7.52
7.11
7.14
7.55
Cl2
3.90
2.65
3.35
2.74
2.78
3.29
NH3
6.97
5.30
6.35
5.78
5.98
6.54
C2H6
9.21
8.24
8.85
8.51
8.62
8.95
ME
+0.54
–1.13b
–0.11
–0.64
–0.48
MAE
0.52
1.15b
0.21
0.68
0.52
MARE
6.49%
12.16%b
1.86%
7.49%
5.71%
The last column
reports the reference
CCSD(T) data obtained from inverse method. The last lines report the
MAE, and the MARE with respect to the CCSD(T) results. Not. conv.—not
converged.
without Be.
Table 6
HOMO Orbital Energies
(eV) for Different
Systems as Obtained from Several Approachesa
@SCF
system
OEPx
GL2
OEP2-sc
SPL
ISI
CCSD(T)
He
–24.98
–24.23
–24.55
–24.46
–24.39
–24.48
Be
–8.41
not.
conv.
–8.89
–9.47
–9.32
–9.31
Ne
–23.38
–17.66
–20.14
–18.98
–19.48
–21.47
Mg
–6.88
–8.04
–7.33
–7.93
–7.91
–7.57
Ar
–16.08
–14.94
–15.34
–15.11
–15.20
–15.63
H2
–16.17
–16.34
–16.30
–16.25
–16.13
–16.41
He2
–24.92
–24.14
–24.47
–24.38
–24.30
–24.48
N2
–17.17
–11.32
–15.65
–13.09
–13.78
–15.51
Ne2
–23.05
–17.45
–19.98
–18.80
–19.31
–21.34
HF
–17.48
–12.16
–14.57
–13.52
–14.03
–15.96
CO
–15.02
–10.64
–13.21
–12.18
–12.70
–13.94
H2O
–13.69
–9.01
–11.27
–10.39
–10.87
–12.50
HCl
–12.92
–11.94
–12.28
–12.04
–12.08
–12.59
Cl2
–12.06
–9.92
–10.85
–10.14
–10.22
–11.45
NH3
–11.56
–8.37
–9.91
–9.34
–9.65
–10.78
C2H6
–13.21
–11.39
–12.20
–11.93
–12.07
–13.01
ME
–0.65
+1.97b
+0.59
+1.15
+0.93
MAE
0.89
2.49b
0.62
1.22
0.98
MARE
6.12%
13.68%b
4.36%
8.28%
6.67%
In the last column,
we report reference
HOMO energies from ref (62). The last lines report the MAE, and the MARE calculated with respect
to the CCSD(T) results. Not. conv.—not converged.
Without be.
The last column
reports the reference
CCSD(T) data obtained from inverse method. The last lines report the
MAE, and the MARE with respect to the CCSD(T) results. Not. conv.—not
converged.without Be.In the last column,
we report reference
HOMO energies from ref (62). The last lines report the MAE, and the MARE calculated with respect
to the CCSD(T) results. Not. conv.—not converged.Without be.Then, we consider the correlation potentials for two
typical systems,
the Ne atom and the CO molecule. In the top panels of Figure , we see that the ACMs provide
a quite good description of the correlation potential for the two
systems, improving significantly over GL2. Nevertheless, with respect
to reference data there are still some limitations, for example, a
moderate overestimation of the correlation potential in valence regions.
This characteristic corresponds to an overestimation of shell oscillations
in the SCF density, as indicated in the bottom panels of Figure , where we report
the correlation density ρc, that is, the difference
between the density obtained with a correlated method and its exchange-only
version.
Figure 5
Correlation potentials (top panels), Δ[vc] (middle), and correlation density (bottom) for the
Neon atom (left) and CO molecule (right) obtained using several ACM–SCF
methods. Reference means the CCSD(T) data using the method from ref (80).
Correlation potentials (top panels), Δ[vc] (middle), and correlation density (bottom) for the
Neon atom (left) and CO molecule (right) obtained using several ACM–SCF
methods. Reference means the CCSD(T) data using the method from ref (80).In the central panels of Figure , we report the values Δ[vc(r)], which is defined, in analogy to eq asThese show, point-by-point
whether or not the SCF procedure improves
the correlation potential with respect to EXX orbitals. As we found
for energies, the SCF correlation potentials are less accurate, but
the error reduces with more accurate ACM functionals. This feature
is also evident for the correlation density, see bottom panels. In
this context, we should however also point out that the ACM-SCF density
does not correspond to the exact linear response density.[94−96]As a final case, we consider in Figure the potential energy surface for the dissociation
of the H2 molecule, in a restricted formalism,[97] which is one of the main DFT challenges,[97,98] and was previously investigated in the ACM framework.[43,99,100] While both MP2 and GL2@EXX diverge
at large distances, ISI@SCF nicely reproduces the exact FCI curve,
much better than ISI@EXX, see also ref (48). Thus, the SCF procedure turns out to be quite
important showing that, despite some limitations discussed above,
it is crucial to include important correlation effects into the orbitals.
For SPL (see Figure S1 in the Supporting Information), similar trends are found; the SPL@SCF curve for R/R0 > 2.5 first increases and then
decreases
asymptotically, a behavior which is clearly incorrect and depends
on some drawbacks of the SPL functional to describe the limit for
large distances, which is more influenced by the strong correlation.
Figure 6
Total
energy of the H2 molecule as it is stretched calculated
with the various methods. The inset presents the same data around
the equilibrium distance.
Total
energy of the H2 molecule as it is stretched calculated
with the various methods. The inset presents the same data around
the equilibrium distance.The limit for very large distances, well beyond R/R0 > 5, is numerically
tricky, but
it
can be computed exactly using the hydrogen atom with fractional spins,
H(1/2,1/2), that is, with half spin up and half spin down.[101] For this system, we have EGL2 → −∞ so that the ISI XC energy
reduces to[36]with . The potential is
thus a simple linear
combination of the EXX potential and the GGA potential from W∞ and W∞′.
For the SPL approach, we have simply that ExcSPL → W∞ and thus the potential is just δW∞/δρ(r).The errors for different methods
and orbitals are reported in Table .
Table 7
Total Energy Error for H(1/2,1/2)
in kcal/mol for Different Methods and Orbitals, Using a Geometric
Series Basis-Set with 17 Uncontracted Gaussian Functions, 104 as the Maximum Exponent, and 2.5 as the Geometric Progression Factora
@EXACT
@SCF
IDD
PBE
54.7
51.5
0.103
EXX
196.1
178.6
0.260
SPL-PC
–0.4
SPL-mPC
–109.8
–114.9
0.125
SPL-hPC
–21.0
–21.4
0.024
ISI-PC
27.4
ISI-mPC
90.2
83.7
0.151
ISI-hPC
23.6
19.4
0.107
The last column
reports the IDD
error, that is, ∫dr4πr2|ρ(r) – ρexact(r)|. Note that self-consistent PC calculations
do not converge. The best two ACM results are reported in boldface.
The last column
reports the IDD
error, that is, ∫dr4πr2|ρ(r) – ρexact(r)|. Note that self-consistent PC calculations
do not converge. The best two ACM results are reported in boldface.At the exact density (ρ(r)
= exp(−2r)/π) SPL–PC
gives an extremely accurate total
energy but the same method fails for the SCF calculation. The SPL-mPC
approach strongly underestimates the total energy, while the SPL-hPC
gives a much lower error, both for the exact and the SCF densities.
At the ISI level, all the energies are higher and the ISI-hPC@SCF
is the most accurate approach. Note, however, that ISI-PC can be made
exact with a proper choice of the parameters.[38] Note also that EXX fails for this system and PBE is also quite inaccurate.When SCF effects are considered, PBE, EXX, ISI-mPC, and ISI-hPC
yield a slight improvement with respect to the case when the exact
density is used. Because the integrated density difference (IDD) is
not zero in all cases, this is a clear signature that all methods
display some error compensation effect. Moreover, some methods give
important convergence issues: the simple PC model does not converge,
as explained above; the mPC model converges but the errors are very
large, about twice the PBE ones. Instead, the ISI-hPC is very good
for both the considered densities, having the best accuracy among
all functionals and performing even better than all the functionals
considered in Table of ref (97). Note
that the good accuracy of the ISI-hPC with respect to ISI-mPC is not
related to the previously mentioned error cancellation between an
incorrect SCF density and an incorrect energy. In fact, the IDD error
is significantly smaller going from ISI-hPC to ISI-mPC. Interestingly,
the same arguments hold when comparing SPL-hPC to SPL-mPC, thus confirming
the high quality of the hPC functional. Note that the almost vanishing
IDD value for the SPL-hPC approach is a particular case, and all methods
with IDD ≲ 0.1 show a quite accurate density. The accuracy
of the ISI-hPC@SCF approach for the H2 dissociation limit
is thus quite significant, considering that it uses full exact exchange
and a combination of GL2 and a GGA functional without empirical parameters,
in contrast to other approaches that use more complex constructions
or extensive fitting on molecular data.[98,102]
Conclusions
In this paper, we have shown that it is
possible to use ACM-based
XC functionals in a full SCF procedure. This solves a long-standing
issue in DFT as all the previous calculations with ACM functionals
had been done in a post-SCF fashion using GGA or EXX orbitals. This
opens the way to new applications and even basic studies in this context,
removing the need for a post-SCF procedure and all the related sources
of inaccuracy. Of course, despite the ACM–SCF procedure presented
here is well defined, conceptually clean and fully capable of producing
important results, is it fair to state that the whole method is not
yet optimized and straightforward to apply especially because it is
strictly related to the OEP approach used for the treatment of the
GL2 component, which requires itself some expertise to be handled.
Nevertheless, several tricks and improvements can be used to make
the OEP calculations simpler and more reliable,[103] thus various upgrades can be easily seen from the practical
point of view for the SCF–ACM method. Anyway, these are left
for future works, as in this paper we wanted to focus only on the
core of problem without adding too many technical details.Having
been able to perform SCF ACM calculations on various systems,
we could perform a thorough assessment of the functionals, finding
important results. For strongly correlated systems, such as the harmonium
atom and the hydrogen molecule at the dissociation limit, the ACM
SCF calculations yield very accurate results taking advantage of the
incorporated strong-correlation limit and also thanks to the novel
hPC functional for W∞ and W∞′ that proved to be very accurate for these cases. For
molecular systems, we found that the overall accuracy using SCF orbitals
depends on the quality of the underlying ACM, in line with the refs (24) and (25). In any case, the ISI-hPC
yields already quite correct SCF potentials and total energies: nevertheless,
its accuracy needs to be further verified for reactions and atomization
energies.Thus, we can finally conclude that, despite some limitations,
the
overall accuracy of the ISI functional (and partially also of the
SPL one), when the full SCF solution is taken into account, is overall
satisfactory, especially considering the following: (i) it does not
employ any parameter obtained from molecular systems, and (ii) the
approach is within a pure KS formalism with a local potential. These
results and the availability of a working SCF procedure for general
ACM formulas now open to the application and testing on other systems
beyond the simple ones considered in this work. Moreover, it paves
the path toward the development of more accurate ACM functional forms
(see e.g. ref (46))
as well as to further development of W∞ and W∞′ approximations, with improved accuracy
for molecular systems.
Interpolation Formulas
In the following,
we report the ISI and SPL interpolation formulas.ISI formula[38]withwhich yields for the XC energySPL formula[40]withThe SPL
XC functional readsNote that this functional
does not make use of the information
from W∞′.
Authors: Hitler Louis; Destiny E Charlie; Ismail O Amodu; Innocent Benjamin; Terkumbur E Gber; Ernest C Agwamba; Adedapo S Adeyinka Journal: ACS Omega Date: 2022-09-19