Christian S Ahart1, Kevin M Rosso2, Jochen Blumberger1. 1. Department of Physics and Astronomy and Thomas Young Centre, University College London, London WC1E 6BT, United Kingdom. 2. Pacific Northwest National Laboratory, Richland, Washington 99354, United States.
Abstract
Constrained density functional theory (CDFT) is a powerful tool for the prediction of electron transfer parameters in condensed phase simulations at a reasonable computational cost. In this work we present an extension to CDFT in the popular mixed Gaussian/plane wave electronic structure package CP2K, implementing the additional force terms arising from a constraint based on Hirshfeld charge partitioning. This improves upon the existing Becke partitioning scheme, which is prone to give unphysical atomic charges. We verify this implementation for a variety of systems: electron transfer in (H2O)2+ in a vacuum, electron tunnelling between oxygen vacancy centers in solid MgO, and electron self-exchange in aqueous Ru2+-Ru3+. We find good agreement with previous plane-wave CDFT results for the same systems, but at a significantly lower computational cost, and we discuss the general reliability of condensed phase CDFT calculations.
Constrained density functional theory (CDFT) is a powerful tool for the prediction of electron transfer parameters in condensed phase simulations at a reasonable computational cost. In this work we present an extension to CDFT in the popular mixed Gaussian/plane wave electronic structure package CP2K, implementing the additional force terms arising from a constraint based on Hirshfeld charge partitioning. This improves upon the existing Becke partitioning scheme, which is prone to give unphysical atomic charges. We verify this implementation for a variety of systems: electron transfer in (H2O)2+ in a vacuum, electron tunnelling between oxygen vacancy centers in solid MgO, and electron self-exchange in aqueous Ru2+-Ru3+. We find good agreement with previous plane-wave CDFT results for the same systems, but at a significantly lower computational cost, and we discuss the general reliability of condensed phase CDFT calculations.
The electron self-interaction error is one of the major shortcomings
of standard density functionals.[1−3] While this long-standing problem
has been addressed at a fundamental level through development of 1-electron
self-interaction error free functionals[4,5] and, very recently,
through neural network machine learning,[6] several correction schemes for standard functionals have also been
developed, including Perdew–Zunger self-interaction correction,[1] DFT+U,[7] optimal tuning
of range-separated hybrid functionals,[8] constrained density functional theory (CDFT),[9,10] its
multideterminant extension CDFT configuration interaction (CDFT-CI),[11] and the localized orbital scaling correction
approach (LOSC).[12]CDFT, on which
we focus in the current work, is particularly attractive
in the context of electron transfer (ET) calculations. An external
potential is added to the Kohn–Sham (KS) Hamiltonian to enforce
localization of the excess electron on the electron donor or acceptor,
thereby creating a set of charge localized diabatic states that can
be used to obtain the basic quantities of ET theories (reorganization
energy, driving force, and electronic coupling). The rationale behind
CDFT is that the charge localized diabatic states suffer less from
the electron delocalization error than the adiabatic electronic states
in time-dependent (TD)DFT calculations. This is particularly true
at ET transition states where the exact adiabatic ground state is
delocalized over donor and acceptor and its energy is strongly underestimated
by standard density functionals due to the wrong scaling of these
functionals with fractional electron number, resulting in too low
ET barriers and strongly overestimated ET rates.[10,11]In recent years there have been several new implementations
of
CDFT in popular DFT packages,[13−22] which generally follow the seminal work by Wu and Van Voorhis.[9] A Lagrangian multiplier is introduced to search
for an external potential applied to the Kohn–Sham Hamiltonian,
performed self-consistently with a second iteration loop in addition
to that of a standard DFT calculation. The definition of this external
potential introduces a weight function, describing the partitioning
of electron density (or charge). In their earlier work,[9] Wu and Van Voorhis utilized the Lowdin atomic
population scheme,[23] later recommending
real space partitioning schemes of the electron density, in particular
Becke partitioning.[24] As a purely geometric
approach that divides space equally among all atoms, Becke partitioning
of the electron density avoids any issues with basis set convergence
found for Lowdin or Mulliken atomic charge partitioning.[25] An alternative real space partitioning scheme
is the one according to Hirshfeld[26] where
molecular electron density is assigned to atoms in proportion to their
promolecular density, thus accounting for their different sizes.Table demonstrates
the problem of equally dividing space among all atoms as done in Becke
partitioning, that for a water molecule the oxygen atom becomes positively
charged and the hydrogen atoms become negatively charged. This is
in direct contrast to Hirshfeld charge partitioning, which predicts
a qualitatively correct charge distribution. The qualitative failure
resulting from equal division of space for charge partitioning in
heteronuclear systems is well-known,[24] where
it is common to define atomic size adjustments based on either covalent
or ionic radii.[18] Such introduction of
empirical parameters is undesirable, with significant ambiguity in
their choices.
Table 1
Atomic Charges for a Neutral Water
Molecule According to Different Partitioning Schemes
atom
Becke
Hirshfeld
O
0.84
–0.30
H
–0.42
0.15
Recently CDFT has been
implemented in the CP2K simulation package;[18] however, the CDFT forces required for CDFT geometry
optimization and molecular dynamics simulation are currently only
available for Becke partitioning of the electron density. In this
work we report the implementation of CDFT forces arising from the
more robust Hirshfeld partitioning scheme of the electron density.
We benchmark our implementation against previous plane-wave CDFT calculations[13] also performed using Hirshfeld partitioning,
finding good agreement for both geometry optimization and molecular
dynamics for electron tunnelling between oxygen defects in MgO[27] and electron self-exchange in aqueous Ru2+–Ru3+.[13]Through considering a wider selection of systems than previous
work, we are also able to discuss the general reliability of condensed
phase CDFT calculations. With the example of charge transfer in two
organic crystals where fully localized polarons do not exist, we demonstrate
that a useful diagnostic tool to identify symmetry splitting and the
transfer of fractional electrons resulting from unphysical diabatic
states is the integrated absolute spin density (IASD)where ρα(r) and ρβ(r) are the electron
densities of the alpha and beta spin channels.The remainder
of the paper is organized as follows. Section summarizes briefly the theory
of CDFT and the implementation of the required force terms, followed
by results for both CDFT geometry optimization (Section ) and CDFT molecular dynamics
(Section ). An
example of systems for which CDFT calculations can be problematic
is shown in Section , and a discussion of the general reliability of condensed phase
CDFT calculations is presented in Section . Concluding remarks are made in Section .
Theory and Implementation
CDFT is a well established method,
with many recent implementations
in popular DFT packages.[15,16,18,19,22] As such, we choose to only briefly summarize the theory relevant
to this work.Charge or spin localized states are constructed
by minimizing the
energy functional E[ρ] under the condition
that the constraintis satisfied. Here w(r) is a weight
function that defines how electron density
is assigned to atoms or molecules in the constraint region, e.g.,
electron donor and electron acceptor, and Nc is the constraint value, e.g., the charge or spin of the atoms or
molecules, or their charge or spin difference. Both remain fixed during
CDFT minimization.The constrained minimization is performed
by introducing a Lagrangian
multiplier V and a new energy functionalW[ρ, V] is minimized
with
respect to ρ for a given V, and V is iteratively adjusted so that the minimized electron density obeys
the constraint eq .In CDFT the total force on an atom i is given
bywhere F is the usual force arising from the
unmodified DFT functional E[ρ] and Fc is the additional force arising from
the constraint. The latter
is given byThe Hirshfeld weight function is constructed
from the promolecular
atomic densities ρ(r –
R) = ρ(r) where r = |r –
R|. For a system with N total atoms and a charge difference constraint defined
between donor atoms D and acceptor atoms A, the weight function has the formThe derivative of the weight function can be shown to be[13]whereThe derivative of the density is given by[13]In CP2K the atomic densities ρ are calculated by performing a DFT calculation on the isolated atoms,
and fitting a minimal Gaussian basis set to this density. As such,
the radial derivatives are known analytically. The calculation of
the atomic densities and their derivatives is performed only once
per atomic species, and therefore the computational cost is negligible.To both ensure numerical stability and to further reduce the computational
cost, an adjustable cutoff is introduced for the denominator of eq . When the total promolecular
density is smaller than 1e–12e the weight function is set to
zero. Similar numerical cutoffs can be found in other implementations
of CDFT based on Hirshfeld partitioning of the electron density.[22] We have verified that the total energy and forces
are insensitive to this choice of cutoff.A simple test of the
implementation of the constraint force (eq ) and Hirshfeld partitioning
(eqs –9) can be performed by checking that the total force
(eq ) is equal to the
force calculated from finite differences of the minimized energy functional W[ρ, V] (eq ) subject to the density constraint eq . Such a comparison is
performed for the helium dimer He2+, shown in Supporting Information Figure 1. The difference in the force obtained
from eq and the finite
difference calculation is 4.70 × 10–5 H/Bohr,
similar to that obtained from other CDFT implementations.[22]
Results
We present
validation and benchmarking of the CDFT force implementation
for both geometry optimization (Section ) and molecular dynamics (Section ), for a variety of systems.
Through considering a wider selection of systems than previous work,
we are also able to discuss the general reliability of condensed phase
CDFT calculations (Section ).
CDFT Geometry Optimization
(H2O)2+ in a Vacuum
Charged dimers
or molecular clusters are a well-known problem for standard DFT functionals.[3] The electron delocalization error tends to favor
charge delocalization over charge localization, in particular for
situations where both these states are energy degenerate in exact
theory, e.g., in a charged molecular dimer at the dissociation limit.
CDFT can be used to correct this error. In the following we consider
the water dimer cation, creating the charge localized state H2O+–H2O by imposing a charge difference
constraint of Nc = 1e between the donor
(H2O) and acceptor (H2O+) regions
using the Hirshfeld weight function eq . The constraint is converged until the residual error
is less than 1 × 10–4e, with a wave function
gradient of 1 × 10–6 H. Calculations are performed
in a vacuum for a center of mass distance of 10 Å, with the PBE-D3
functional.[28,29] Geometry optimization is converged
until the residual forces are smaller than 0.02 eV/Å. Unless
specified otherwise these values were used for all systems studied
in this work.Table shows the DFT optimized geometries of the isolated H2O+ and H2O molecules, confirming that
CDFT geometry optimization of the charge localized state H2O+–H2O reproduces these geometries for
the large water–water separation of 10 Å, as it should
do. Not surprisingly, DFT predicts that the excess hole is equally
delocalized over both molecules and the geometry of the two molecules
is the same, between the one for neutral water and the water radical
cation, i.e. H2O0.5+–H2O0.5+. Similar results are found for CDFT-MD performed at 300
K (see the Supporting Information).
Table 2
Geometry Optimization of a Water Dimer
(H2O)2+ in a Vacuum at a Distance of 10 Åa
DFT (isolated)
DFT
CDFT
(O1–H1)+/Å
1.017
0.988
1.017
(O1–H2)+/Å
1.017
0.989
1.017
θHOH+
108.51
105.91
108.50
(O2–H3)/Å
0.970
0.988
0.971
(O2–H4)/Å
0.970
0.985
0.971
θHOH
104.17
105.95
103.94
With the use
of CDFT to form
the charge localized state H2O+–H2O, the bond lengths and angles of the isolated H2O+ and H2O molecules are reproduced. In comparison,
standard DFT predicts that the excess hole is equally delocalized
over both molecules and the geometry of the two molecules is the same.
With the use
of CDFT to form
the charge localized state H2O+–H2O, the bond lengths and angles of the isolated H2O+ and H2O molecules are reproduced. In comparison,
standard DFT predicts that the excess hole is equally delocalized
over both molecules and the geometry of the two molecules is the same.
Electron
Transfer in Solid MgO
While CDFT is an established method
for calculating electron transfer
(ET) parameters in molecular systems,[25,27,30−32] applications to condensed phase/periodic
systems remain rare to date. A notable example, however, is the electron
tunnelling between between charged oxygen vacancies (termed F-center
defects) in MgO, previously calculated with a plane-wave implementation
of CDFT in CPMD.[27,31] Oxygen vacancies have been shown
to exist in MgO in three possible charge states: F0, F+, and F2+, corresponding to the localization of two, one, or
zero electrons at the defect site.[31] The
electron tunnelling process between defect sites i and ii is therefore written asThe ET process is modeled by removing
two oxygen atoms at a separation d from a MgO rocksalt
structure, while removing only one electron. With a total charge of
+1 and a multiplicity of 2, a charge difference of Nc = 1e defined between the defect sites is used to form
the diabatic states. The Hirshfeld weight function (eq ) is defined as the 6 Mg atoms nearest
to the respective defect site. The reorganization energy for this
reaction is defined aswhere RA and RB are the optimized geometries in the diabatic
states A and B. As the initial and final states are the same, the
reorganization energy can be calculated as the vertical energy gap
at the minimum of a diabatic stateCDFT geometry optimizations of the diabatic
states are performed
using the PBE functional,[28] with single
point calculations of the reorganization energy also performed using
the PBE0 functional[28,33,34] with an optimally tuned truncated Coulomb potential.[35] The latter functional was shown to reproduce
the experimental MgO band gap of 7.2 eV.[27,36] For Mg, the 2s, 2p, and 3s electrons and for O the 2s and 2p electrons
are treated explicitly. Because of the very hard pseudopotential of
Mg, a multigrid cutoff of 3000 Ry was used.Figure shows an
isosurface of excess spin density for the DFT adiabatic ground state,
showing delocalization of the excess charge over both defect sites,
and the CDFT diabatic state calculated for the same geometry with
a charge difference of Nc = 1e defined
between the defect sites. The results of geometry optimizing the diabatic
state and calculating the vertical energy gap λ are shown in Figure . The corresponding
reorganization energies (dashed lines) are very similar (MRUE = 4%)
to the ones obtained from CP2K CDFT single point calculations on the
CPMD CDFT optimized geometries (solid lines) giving reassurance to
the present CDFT force implementation. The reorganization energies
obtained from CP2K CDFT tend to be somewhat larger than they were
reported for CPMD CDFT (MRUE = 22%), even if they are calculated on
the same geometries. This difference is most likely related to the
different functional form of the weight function w (eq ) in the two implementations,
Gaussian functions in CP2K and Slater functions in CPMD.[27,31] Other differences, like the basis used for electronic structure
calculations, could also contribute to the difference.
Figure 1
Oxygen defects in MgO.
Excess spin density for (A) DFT adiabatic
ground state and (B) CDFT diabatic state on the adiabatic ground state
optimized geometry with a defect separation of 12.76 Å. The increase
in spin density (yellow) is composed of a s-like function at the defect
site and the p-orbitals of the surrounding oxygen atoms.
Figure 2
(A) Reorganization energies λ and (B) electronic couplings obtained for tunnelling between
oxygen
defects in MgO. The black markers represent the CPMD reference values,[27] red markers the CP2K values calculated using
the CPMD structures, and pink markers the CP2K values from reoptimized
structures. Results are shown for different percentages of Hartree–Fock
exchange and for different defect separations. Circles represent PBE
calculations, while squares represent PBE0 calculations. Best fits
are indicated by solid and dashed lines.
Oxygen defects in MgO.
Excess spin density for (A) DFT adiabatic
ground state and (B) CDFT diabatic state on the adiabatic ground state
optimized geometry with a defect separation of 12.76 Å. The increase
in spin density (yellow) is composed of a s-like function at the defect
site and the p-orbitals of the surrounding oxygen atoms.(A) Reorganization energies λ and (B) electronic couplings obtained for tunnelling between
oxygen
defects in MgO. The black markers represent the CPMD reference values,[27] red markers the CP2K values calculated using
the CPMD structures, and pink markers the CP2K values from reoptimized
structures. Results are shown for different percentages of Hartree–Fock
exchange and for different defect separations. Circles represent PBE
calculations, while squares represent PBE0 calculations. Best fits
are indicated by solid and dashed lines.In addition to reorganization energies, we can also compare with
the CPMD electronic couplings. The electronic coupling matrix elements
between the initial and final ET states are calculated with CDFT[10] on the transition state structures, approximated
by the DFT adiabatic ground state where the electron hole is delocalized
over both defects. The supercell size and defect separation were chosen
such that in one direction the distance between the defects is equal
to the distance to the periodic image of the defects, while the other
directions are sufficiently large that periodic images in these directions
have only a small effect.[27,31] The finite size corrected
electronic coupling Hab is therefore equal
to half of the coupling obtained in periodic boundary conditions Habpbc minus a correction term that accounts for the artificial contribution
from the remaining periodic imageswhere in this work the latter
correction term
is neglected to enable a direct comparison to the CPMD electronic
couplings.Figure compares
the electronic couplings calculated with CPMD and CP2K on the CPMD
optimized geometries as a function of defect distance, with good agreement
for defect distances of up to 10 Å (MRUE = 26%). At larger distances,
both the PBE and PBE0 CP2K couplings are somewhat larger than reported
for CPMD, resulting in a smaller exponential decay value for PBE0
of β = 0.47 ± 0.06 Å–1, compared
to the one reported for CPMD couplings, 0.73 ± 0.10 Å–1.[27,31] The overall MRUE error is reasonably
small, 58%. For PBE, we find a smaller exponential decay value of
β = 0.28 ± 0.10 consistent with CPMD β = 0.40 ±
0.22.
CDFT Molecular Dynamics
H2+ in a Vacuum
An important consideration
in any molecular dynamics calculation is total energy conservation.
For CDFT-MD this can be particularly challenging as the constraint
is introduced through an additional self-consistent field (SCF) loop,
and as such both the DFT and CDFT SCF loops must be well converged
in order to ensure total energy conservation.The hydrogen dimer
H2+ presents
one of the simplest benchmarks for examining energy convergence, performed
in a vacuum for a temperature of 300 K in the NVE ensemble with the
PBE functional. Figure shows the average drift of the conserved energy for both DFT-MD
as a function of the SCF convergence criterion, and CDFT-MD as a function
of the constraint convergence. The constraint is defined as a charge
difference of Nc = 0.5e between the two
hydrogen atoms. The resultant energy drift is less than 1e–6
H/atom/ps for a constraint convergence of 1 × 10–6e, the same as found in CPMD calculations for this system.[13] For unconstrained DFT-MD of H2+, the energy
drift is negligible for the chosen DFT convergence of 1 × 10–5, less than 1 × 10–8 H/atom/ps,
and therefore the observed energy drift is introduced through the
use of CDFT.
Figure 3
(A) Total energy conservation in DFT-MD of the hydrogen
dimer H2+ as a function
of the SCF convergence criterion, the largest gradient of the energy
with respect to a change in molecular orbital coefficients. (B) Total
energy conservation in CDFT-MD as a function of the constraint convergence.
Solid markers for BiVO4, lepidocrocite and hematite denote
systems where the energy drift for 1 ps has been extrapolated from
100 fs CDFT-MD. See Supporting Information Figure 8 for corresponding plots of energy drift against time.
(A) Total energy conservation in DFT-MD of the hydrogen
dimer H2+ as a function
of the SCF convergence criterion, the largest gradient of the energy
with respect to a change in molecular orbital coefficients. (B) Total
energy conservation in CDFT-MD as a function of the constraint convergence.
Solid markers for BiVO4, lepidocrocite and hematite denote
systems where the energy drift for 1 ps has been extrapolated from
100 fs CDFT-MD. See Supporting Information Figure 8 for corresponding plots of energy drift against time.On average, the CDFT-MD calculations presented
in this work are
a factor of 3 times more expensive than corresponding DFT-MD calculations,
consistent with other CDFT implementations.[13] This additional cost is introduced by the CDFT SCF loop, with around
2–3 additional SCF cycles per MD step. See Supporting Information Figure 15 for the cost of CDFT-MD as
a function of the constraint convergence.
Excess
Electrons and Holes in Oxide Materials
Also included in Figure is the energy drift
for CDFT-MD of MgO with a defect separation
of 6 Å, constraining the charge difference over the defects sites
as described in Section . Likely as a result of the well-defined oxygen defects
with large reorganization energies, even for a loose constraint convergence
of 1 × 10–3e total energy conservation below
1 × 10–6 H/atom/ps is achieved for both PBE
and PBE0 CDFT-MD.Energy drifts for CDFT-MD calculations for
three further systems are shown in Figure : an excess electron in bismuth vanadate
(BiVO4),[37] an electron hole
in lepidocrocite (γ-FeOOH),[38] and
an electron hole in hematite (α-Fe2O3).[38,39] For each system, the starting structure is the geometry optimized
charged ground state DFT structure of the excess electron or electron
hole. A spin constraint is then used to constrain the spin moment
of either the vanadium atom (bismuth vanadate) or the iron atom (lepidocrocite
and hematite) where the polaron is localized to the spin moment of
the geometry optimized structure. As such, the Lagrange multiplier
(eq ) is initially zero,
and becomes finite during the CDFT-MD. Importantly, the use of CDFT-MD
introduces a minimal additional energy drift in comparison with that
for the use of DFT-MD. See Supporting Information Section 1.8 for additional information for these systems.
Ru2+–Ru3+ in
Aqueous Solution
For an example of condensed phase CDFT MD,
we choose the previously studied Ru2+–Ru3+ electron self-exchange in aqueous solution.[13] This is arguably one of the simplest electron self-exchange reactions
in an aqueous solution. Both Ru ions are low-spin and coordinated
by 6 water molecules in an octahedral geometry. The most significant
difference between aqueous Ru2+ and Ru3+ is
the Ru–O bond lengths, around 0.08 Å shorter in the oxidized
state.[40]Starting from the same initial
structure from classical MD as the reference CPMD calculations,[13] with 2 Ru ions and 63 water molecules, 1 ps
of DFT-MD equilibration is performed with a time step of 0.96 fs in
the NVT ensemble with a Nose–Hoover thermostat at 300 K, and
a fixed Ru–Ru distance of 5.5 Å. Where possible, we use
the same computational setup as the calculations in CPMD,[41,42] including use of the BLYP functional.[43,44] A charge difference
constraint of Nc = 1e is defined between
the electron donating and accepting groups, chosen as the Ru ion and
the 6 water molecules in the first solvation shell: Ru2+(H2O)6 for the electron donating group and
Ru3+(H2O)6 for the electron accepting
group. The constraint is converged until the residual error is less
than 5 × 10–4e. An isosurface of the weight
function (eq ) is shown
in Figure .
Figure 4
CDFT-MD of
Ru2+–Ru3+ in aqueous solution.
An isosurface of the weight function (eq ) is shown, where the electron donating group Ru2+(H2O)6 is shown color coded yellow
and the electron accepting group Ru3+(H2O)6 is shown color coded blue. The bonds between the 2 Ru ions
and the 6 water molecules in their first solvation shell are shown
explicitly.
CDFT-MD of
Ru2+–Ru3+ in aqueous solution.
An isosurface of the weight function (eq ) is shown, where the electron donating group Ru2+(H2O)6 is shown color coded yellow
and the electron accepting group Ru3+(H2O)6 is shown color coded blue. The bonds between the 2 Ru ions
and the 6 water molecules in their first solvation shell are shown
explicitly.The total linear drift of the
conserved energy is shown in Figure , for both DFT-MD
and CDFT-MD. The use of CDFT introduces minimal additional energy
drift, with only a small increase from 4.0 × 10–5 H/atom/ps to 4.5 × 10–5 H/atom/ps. While
this energy drift is reasonably large, it is smaller than that found
in CPMD calculations of 9.7 × 10–5 H/atom/ps.[13] See Supporting Information Figure 8 for a plot of the energy drift against time.Following 1 ps of CDFT-MD equilibration, we find that the average
absolute charge for the electron donating group Ru2+(H2O)6 is 0.47e and the electron accepting group Ru3+(H2O)6 is 1.47e. Only the charge difference
between the two groups is constrained to 1, and as such the absolute
charges are free to vary during the dynamics. These average charges
are similar to those found from CPMD calculations, 0.52e and 1.52e.[13] The remaining charge of 3.06e (2.96e from CPMD)
is delocalized over the solvent.While the average charges of
the electron donating and accepting
groups are similar between the CP2K and CPMD calculations, the geometries
are different. For CP2K CDFT-MD the Ru–O bond lengths are on
average 0.086 Å shorter in the oxidized state Ru3+(H2O)6 than Ru2+(H2O)6, in comparison to only 0.02 Å shorter for CPMD CDFT-MD.[13] X-ray diffraction experiments performed on isolated
ions in solution found that the average Ru–O bond lengths were
0.08 Å shorter in the oxidized state,[40] consistent with unconstrained calculations performed in CPMD.[41,45] However, without any experimental data available for an ion–ion
distance of 5.5 Å it is not possible to determine which of the
CPMD or CP2K CDFT-MD geometries are more accurate.The CDFT
simulation can be used to calculate the reorganization
free energy for electron transfer between the two Ru ions. For self-exchange
and assuming a linear response, it is simply equal to the thermal
average of the vertical energy gapwhere ΔE = EB – EA, and
the average is taken along a CDFT trajectory in diabatic state A.
The vertical energy gap was sampled with 100 equally spaced single
point calculations, shown in Figure , with an average ⟨ΔE⟩A = 1.30 ± 0.03 eV, slightly smaller than
the CPMD calculated value of 1.53 ± 0.06 eV.[13] The error of the average due to the finite length of the
trajectory is calculated from the difference of the vertical energy
gap obtained from the first and second half of the trajectory.
Figure 5
Vertical energy
gap for the electron self-exchange reaction of
Ru2+–Ru3+ in aqueous solution. Single
point calculations are performed on 100 equally spaced structures
sampled from 1 ps of CDFT-MD. The green dotted line shows the BLYP
average of 1.30 ± 0.03 eV, the blue line the ωB97X average
of 1.48 ± 0.08 and the red dotted line the CPMD value from Oberhofer
et al. of 1.53 ± 0.06 eV.[13]
Vertical energy
gap for the electron self-exchange reaction of
Ru2+–Ru3+ in aqueous solution. Single
point calculations are performed on 100 equally spaced structures
sampled from 1 ps of CDFT-MD. The green dotted line shows the BLYP
average of 1.30 ± 0.03 eV, the blue line the ωB97X average
of 1.48 ± 0.08 and the red dotted line the CPMD value from Oberhofer
et al. of 1.53 ± 0.06 eV.[13]With the increasing efficiency of computer codes
and platforms,
it is now possible to perform hybrid CDFT calculations on system sizes
that would have been out of reach of the earlier CPMD work.[13] In particular, we are able to perform CDFT-MD
with B3LYP[46] and the long-range corrected
hybrid functional ωB97X.[47] Following
CDFT-MD equilibration, we find only a small increase in the average
absolute charges of the Ru3+(H2O)6 and Ru2+(H2O)6 compared to charges
obtained from BLYP CDFT-MD: +0.08e for B3LYP and +0.13e for ωB97X.
The remaining charge of 2.92e and 2.82e remains delocalized over the
solvent. Therefore, even these hybrid functionals are unable to prevent
spurious charge delocalization across the solvent. Table shows the average Ru–O
bond lengths and vertical energy gap for BLYP, B3LYP and ωB97X.
Similar to the charge, the reorganization energy increases only slightly:
+0.12 eV for B3LYP and +0.18 eV for ωB97X.
Table 3
Average Ru–O Bond Lengths and
Vertical Energy Gap (eq ) for the Electron Self Exchange Reaction of Ru2+–Ru3+ in Aqueous Solutiona
functional
average Ru–O
(Å)
energy gap
(eV)
BLYP
2.18, 2.10
1.30 ± 0.03
B3LYP
2.18, 2.08
1.42 ± 0.18
ωB97X
2.17, 2.07
1.48 ± 0.08
BLYP[13]
2.15, 2.13
1.53 ± 0.06
The average
of the 6 Ru2+–O and Ru3+–O bond
lengths are calculated
following 1 ps of CDFT-MD equilibration. The error of the vertical
energy gap (eq ) is
calculated from the difference of the vertical energy gap obtained
from the first and second half of the trajectory.
The average
of the 6 Ru2+–O and Ru3+–O bond
lengths are calculated
following 1 ps of CDFT-MD equilibration. The error of the vertical
energy gap (eq ) is
calculated from the difference of the vertical energy gap obtained
from the first and second half of the trajectory.The reorganization energy calculated
for the electron self-exchange
reaction accounts for the 2 Ru-hexahydrates and the 51 water molecules
solvating the electron transfer complex, neglecting the effects of
higher solvation shells and the bulk solvent. Blumberger et al.[48] calculated a finite size correction from classical
MD with extrapolation to the limit of infinite dilution, resulting
in a correction term of 0.09 eV.[13] As such,
the reorganization free energy of the infinitely diluted system for
the BLYP, B3LYP, and ωB97X functionals is 1.30 + 0.09 = 1.39
eV, 1.42 + 0.09 = 1.51 eV, and 1.48 + 0.09 = 1.57 eV. Comparison to
the experiment is challenging as a direct experimental measurement
of the reorganization free energy is not available, and the experimental
Ru–O bond lengths for the electron transfer complex at a distance
of 5.5 Å are not known. A continuum study[49] with a Ru–Ru distance of 6.5 Å reported a reorganization
free energy of 1.95 eV, which fits well the experimental rate constant,[50] and is expected to decrease to 1.75 eV for a
Ru–Ru distance of 5.5 Å.[13] In
addition, under a number of assumptions, an experimental value of
2.0 eV has been reported.[50]
Charge Transfer in Organic Crystals
A useful application
of CDFT in organic semiconductor research would
be to calculate reorganization energies for charge transfer in organic
semiconductors, including the full outer-sphere contribution from
the periodic crystal which is usually presumed to be small and therefore
neglected. However, it would be useful to check this assumption from
case to case. Refined values for reorganization free energy would
improve the accuracy of the parametrization of charge transport simulations,
including, e.g., charge hopping and nonadiabatic molecular dynamics.[51−53]Figure shows
the weight functions (eq ) for hole transfer in two organic semiconductors: a 3 × 3 supercell
of a pyrene 2D covalent organic framework (pyrene-COF),[54] and a 3 × 2 × 1 supercell of pentacene.
For both systems, the electron donating and accepting regions are
defined as adjacent units or molecules. The reorganization energy
for hole transfer in these systems should be calculated using eq , as the vertical energy
gap at the minimum of a diabatic state. Geometry optimizing the diabatic
state with PBE or HSE06 for either system results in unphysical distortions
and even bond breaking during CDFT geometry optimization of the donor
and acceptor groups. This shows that the localization of a full charge
on a single COF unit or pentacene molecule within a crystalline environment
does not correspond to a stable local minimum on the potential energy
surface. Thus, we conclude that fully localized polarons do not exist
in these materials and cannot be enforced using CDFT. In this respect,
we note that previous nonadiabatic molecular dynamics simulations
showed that polarons in crystalline pentacene are delocalized over
18 molecules on average at room temperature.[53] At 0 K, corresponding to the present CDFT optimizations, the charge
will occupy the fully delocalized state at the top of the valence
band. The physical reason for the nonexistence of fully localized
polaronic states is that reorganization energy is not sufficiently
large in these materials compared to electronic couplings to support
fully localized states, in stark contrast to, e.g., the F centers
in the MgO system (Section ) and the Ru2+–Ru3+ self-exchange
reaction (Section ).
Figure 6
Weight function (eq ) for hole transfer in two organic semiconductors: (A) 3 × 3
supercell of a pyrene 2D covalent organic framework (pyrene-COF) and
(B) 3 × 2 × 1 supercell of pentacene.
Weight function (eq ) for hole transfer in two organic semiconductors: (A) 3 × 3
supercell of a pyrene 2D covalent organic framework (pyrene-COF) and
(B) 3 × 2 × 1 supercell of pentacene.
Reliability of CDFT
CDFT is a powerful
method for calculation of ET parameters, but as we have discussed
in Section , no
arbitrary charge constrained state can be constructed this way. A
useful diagnostic tool to identify states that the DFT functional
is not able to adequately describe is the IASD, eq . For a system with a single excess charge,
the IASD should have a value of 1. Small deviations are to be expected.
For example, the CDFT geometry optimizations of MgO in Section have an
average IASD of 1.05, and the CDFT-MD of Ru2+–Ru3+ in Section have an average IASD of 1.09.While neutral DFT calculations
for the pyrene-COF and pentacene crystal in Section have an IASD of 0.00 as expected, with
the addition of an electron hole this increases to 1.18 for the pyrene-COF
and 1.33 for the pentacene crystal. Using CDFT to localize the electron
hole fully on a single unit or molecule raises the IASD to 1.46 (+0.28)
and 1.55 (+0.22), with further increases during CDFT geometry optimization.
See Supporting Information Figures 3 and 4 for the energy and IASD as a function of CDFT geometry optimization
step. These large values of IASD indicate the breaking of electron
pairs, as the DFT functional is not able to adequately describe the
charged states. This is particularly problematic for CDFT, where the
transfer of fractions of electrons from donor to acceptor can lead
to electronic couplings that do not decay exponentially with distance.[55] In the context of this work, we attribute symmetry
breaking and the transfer of fractional electrons to the formation
of an unphysical diabatic state that the DFT functional is not able
to adequately describe.
Conclusion
In this
work, we have provided an extension to CDFT in a popular
DFT package CP2K, implementing the necessary force terms that arise
from a constraint based on Hirshfeld partitioning of the electron
density. The previously used Becke partitioning is prone to predict
qualitatively incorrect atomic charges, as a result of dividing space
equally among all atoms.We have verified and benchmarked this
new implementation against
systems previously studied in a plane-wave implementation of CDFT,
showing good agreement for both geometry optimization and molecular
dynamics for electron tunnelling between oxygen defects in MgO[27] and electron self-exchange in aqueous Ru2+–Ru3+.[13] With
the increasing efficiency of computer codes and platforms it is now
possible to perform hybrid CDFT calculations on system sizes that
would have been out of reach of the earlier CPMD work.[13] In particular, we are able to perform CDFT-MD
for electron transfer reactions in the condensed phase where both
solute and solvent are treated at the hybrid or long-range corrected
hybrid DFT level.Consistent with previous work,[55] we
find that an IASD markedly larger than 1 is an indicator of systems
for which CDFT calculations can be unreliable. With the exception
of these pathological cases, we find that CDFT is a powerful tool
for the calculation of electron transfer parameters at a reasonable
computational cost. We expect the method to become valuable also for
the simulation of electron transfer reactions across interfaces between
different semiconductors or between semiconductors (e.g., oxides)
and liquid solutions (e.g., water), thus becoming part of the toolbox
for first-principles electrochemistry.[56]