A first step towards Quantum Energy Potentials of
Electron Pairs
Julen Munárriz, Rubén Laplaza, A. Martín Pendás, Julia Contreras-García
To cite this version:
Julen Munárriz, Rubén Laplaza, A. Martín Pendás, Julia Contreras-García. A first step towards
Quantum Energy Potentials of Electron Pairs. Physical Chemistry Chemical Physics, 2019, 21 (8),
pp.4215-4223. �10.1039/C8CP07509C�. �hal-02181682�
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A first step towards Quantum Energy Potentials of Electron Pairs
Julen Munárriz,a,b,* Rubén Laplaza,a,b A. Martín Pendásc and Julia Contreras‐Garcíab,*
A first step towards the construction of a quantum force field for electron pairs in direct space is taken. Making use of
topological tools (Interacting Quantum Atoms and the Electron Localization Function), we have analyzed the dependency of
electron pairs electrostatic, kinetic and exchange‐correlation energies upon bond stretching. Simple correlations were
found, and can be explained with elementary models such as the homogeneous electron gas. The resulting energy model is
applicable to various bonding regimes: from homopolar to highly polarized and even to non‐conventional bonds. Overall,
this is a fresh approach for developing real space‐based force fields including an exchange‐correlation term. It provides the
relative weight of each of the contributions, showing that, in common Lewis structures, the exchange correlation
contribution between electron pairs is negligible. However, our results reveal that classical approximations progressively fail
for delocalized electrons, including lone pairs. This theoretical framework justifies the success of the classic Bond Charge
Model (BCM) approach in solid state systems and sets the basis of its limits. Finally, this approach opens the door towards
the development of quantitative rigorous energy models based on the ELF topology.
Introduction
The simulation of big systems requires the use of analytical
force fields (FFs) that enable the performance of molecular
dynamic simulations in reasonable computing times. This is
usually done by following simple atomic models. For example,
bond lengths are commonly analysed in terms of the Hooke’s
law, where potential and kinetic energy balances are
parametrized to adjust to experimental/computational
results.1,2 Nonetheless, in many cases, chemical behaviour is
determined by non‐classical terms (e.g. exchange or
correlation), which are not easily encoded in these potentials.
We propose hereby a change of paradigm that is able to easily
capture electron reorganization (towards building reactive FFs),
as well as quantum terms.
Atomic models usually require specific parametrization for
different coordination numbers. This stems from the fact that
electrons (i.e. bonds) are the ones being re‐allocated during a
reaction. Therefore, the static view of electrons belonging to
one atom, and hence, its oxidation state, can be avoided if the
electron pair is taken as the main unit. It should be noted that
this approach has been used for a long time in chemistry,
although not in a quantitative manner. Before the advent of
formal force fields, the use of mere electrostatic reasoning
among electron pairs allowed for the first time to predict
a. Departamento
de Química Física and Instituto de Biocomputación y Física de
Sistemas Complejos (BIFI), Universidad de Zaragoza, 50009, Zaragoza, Spain
b. Sorbonne Université, CNRS, Laboratoire de Chimie Théorique, LCT, F. 75005 Paris,
France.
c. Laboratorio de Química Física y Analítica, Universidad de Oviedo, 33006, Oviedo,
Spain.
†Electronic
Supplementary
Information
(ESI)
available.
See
DOI: 10.1039/x0xx00000x
molecular structures, in what is nowadays known as the
Valence Shell Electron Pair Repulsion (VSEPR) theory.3
Moreover the use of electron pairs also provides a simpler
link to quantum mechanics. The usefulness of electron pairs as
the basis of the representation lies on the fact that paired
electrons behave very much like bosons.4,5 This means that
Pauli correlation is minimized in a system composed by
perfectly localized electron pairs, so that the exchange‐
correlation term (more difficult to disentangle with simple
models) is minimal. These advantages have been exploited in
both, classical approaches, such as the Bond Charge Model
(BCM),6,7 where only potential and kinetic energy terms are
included; as well as in more updated formulations based on
quantum mechanical calculations.8
In order to provide robust and rigorous analytical
expressions for a quantum FF, it is necessary to count with a
recipe for the identification of electron pairs, and their
parametrization. For that, the Interacting Quantum Atoms (IQA)
energy decomposition scheme is very suitable, since it allows to
obtain and quantify the different energetic contributions from
the real space partitions of the system.9,10 The advantages of
the IQA scheme are showcased by its success in the study of
different chemical phenomena, such as halogen and hydrogen
bonding,11,12 and metal–ligand interactions,13 among many
others. However, these calculations are expensive and limited
to small systems. Therefore, by reconstructing models from this
scheme, the advantages of IQA could be transferred to bigger
systems.
For translating the IQA partition to electron pair energy
models, an electron‐pair real‐space partition is needed. The IQA
scheme is usually coupled to the Quantum Theory of Atoms in
Molecules (QTAIM) partition in order to associate the different
energy terms to atomic contributions. In this sense, it is worth
noting the previous work of Popelier et al., who developed the
first protein FF based on the QTAIM topology.14 This framework
also proved to be suitable for geometry optimizations when
combined with machine learning approaches.15,16 However,
since we want to focus on electron pairs, we will couple IQA to
the Electron Localization Function (ELF) topology.17 The ELF is
able to recover Lewis entities, as bonds and lone pairs, providing
the classical VSEPR picture, and is thus the perfect starting point
for our energy model, allowing to quantify (classic and
quantum) interactions between electron pairs.18
In this article we propose a first step in constructing a
stretching energy model based on the ELF topology. In order to
do so, we evaluate electron pair interactions through classical
(kinetic and electrostatic) and quantum energy terms (exchange
and correlation). The ease and chemical rigor with which the
model parameters can be obtained set the foundations of a
fresh approach to real space force fields. In addition, a careful
analysis of the relative weight of the classical and quantum
energy terms is presented. Valuable implications in general
force field development are also derived: we identify the
chemical bonds that require quantum terms among those that
can be studied under a purely classical perspective. The
resulting model is beautifully connected with previous
“intuitive” models (e.g. VSEPR, BCM). It also sets the basis for
connecting the ELF topology with the energy of the system,
leading to a simple chemical model that attempts to answer the
initial question: “how do electron pairs (bonds, lone pairs)
contribute to the energy of the system?”
Theoretical and Computational Methods
All energy scans and wavefunctions for ELF and IQA analyses
were obtained through DFT calculations, using the Gaussian 09
program package.19 The B3LYP exchange‐correlation
functional20,21 was used, in conjunction with the 6‐31G(d) basis
set.22,23 Stability checks were carried out with other functionals
(PBE and PBE0)24–26 and with Hartree‐Fock, in conjunction with
bigger basis sets (6‐311G(d,p), cc‐PVDZ and cc‐PVTZ).27 The
results obtained by varying the computational conditions led to
the same behaviour, yielding very similar fittings, while the
computational cost increased considerably with the increase in
the basis set size. These results are provided in the Supporting
Information (see Tables S1–S6). Hence, the small basis set was
favoured. Bonding descriptors were computed at the B3LYP/6‐
311G(d,p) level to further ensure basis set convergence of the
density at the bond critical points.
The partition into localized electron pairs was carried out
with the Electron Localization Function (ELF).17 The ELF kernel,
, can be interpreted as a measure of the excess of local kinetic
energy due to the Pauli Principle, relative to the homogeneous
electron gas kinetic energy density.28 The ELF, , is mapped
through a Lorentzian function (see eq. 1), to a scale ranging
from 0 (when → ∞), to 1 (when → 0).
(1)
The gradient of this function, , is used to induce a topological
partition which divides the space into non‐overlapping regions
(basins) whose properties can be determined by integrating the
appropriate densities over their associated volume. Hence, if
one is interested in, for example, lone pairs populations, it
suffices to integrate the electron density, , over the
corresponding region associated to the lone pair maximum.
The ELF studies were performed with a locally modified
version
of
the
TopMod
program,29
using
the
monodeterminantal
B3LYP/6‐31G(d)
wavefunctions
in
conjunction with a cubic tridimensional grid of 200 points in
each direction. ELF plots were made with Chimera software.30,31
The energies of the different topological basins can be
calculated with the Interacting Quantum Atoms (IQA) energy
decomposition scheme.32 This approach provides a set of
unique and rigorous energetic terms that additively recover the
exact energy of the system. Unlike many topological analyses,
this method is not only suitable for stationary points (e.g.
equilibrium geometries), such as with virial related energy
partitions, but also for non‐equilibrium geometries. This feature
was crucial for evaluating the energy terms along bond
elongations in geometry scans. The energy terms are calculated
by partitioning the first and second‐order density matrices with
respect to real space partitions, usually the QTAIM atomic
basins (see eq. 2).
∑
∑
∑
(2)
∑
This way, the total energy is divided into an intra‐atomic
contribution,
, and the inter‐atomic interaction between
each pair of atoms,
. The former is the sum of the kinetic
energy of electrons in atom A, , and the electron‐electron and
electron‐nucleus interactions,
and
, respectively.
is the sum of the interaction among the electrons in A
and the nucleus of B,
; the nucleus of A and the electrons
in B,
; and the nucleus‐nucleus and electron‐electron
interactions between A and B,
and
, respectively.
The Electron‐electron repulsion can be further divided into
a classical (electrostatic) contribution,
, and a non‐classical
one,
, which is the sum of exchange (X) and correlation
(Corr) terms (see eq. 3).
(3)
Following this scheme, each contribution to the total energy
(intra and interatomic) can be expressed just like in atomistic
approaches, that is, as a sum of kinetic and electrostatic terms,
plus a non‐classical interatomic term, as shown in eq. 4 and 5.
(4)
(5)
Where all electrostatic terms have been put under a
common “Coul” index:
and
.
IQA can also be applied to ELF partitions. When considering
bonding basins (and valence in general) within the IQA partition,
the nuclear terms presented in the previous equations become
null (
0,
0,
0). Therefore, for a bonding
basin, “Bond”, which interacts with a core basin that represents
an atom A, the different energy terms can be expressed as
shown in eq. 6 and 7.
(6)
(7)
Since we are interested in developing an energy model
accounting for interactions between electron pairs, this was the
selected approach. This way, it is possible to calculate
interactions between atoms and “bonds”, as well as interactions
between two “bonds” and “bonds” with “lone pairs”. For this
purpose, the original code was modified so as to perform
integration tasks over ELF basins.18 The IQA‐ELF approach
provides an accurate reference that can be used to analyse the
behaviour of the energy terms and to construct energy
potentials that take into account classical and non‐classical
terms. In the next sections, we will examine the dependency of
these terms with respect to bond elongation and compare them
with previous potentials.
The original IQA implementation could only deal with HF
wavefunctions; however, recent developments provide support
for DFT‐derived ones.10 IQA calculations were performed with
PROMOLDEN.9,33
Results and Discussion
1. The model
As a starting point, the ELF‐IQA approach was applied to a series
of simple yet representative molecules in the CH3–X (X = CH3,
NH2, OH, F) series. In order to analyse the variation of the
different terms that contribute to
and
(A‐Bond),
and attempt to rationalize the observed behaviour; the C–X
interatomic distance, R, was stretched around the equilibrium
position, Req, approximately in the range [0.90–1.10]∙Req. Since
we are resorting to small elongations, the use of a DFT approach
is justified. The following standard ELF notation is used: V(C,X)
represents the C–X bond, V(X) the lone pairs on X, C(Y) or simply
Y, designates the core of atom Y and so on. For the sake of
clarity, we will only analyse the results obtained for CH3–NH2 in
detail, as an illustrative example with bonds and lone pairs.
Similar results have been obtained for all the molecules in the
CH3–X test set, and are provided in the Supporting Information.
The CH3–NH2 ELF basins and their populations are shown in
Figure 1a. The evolution of the ELF populations of V(N) and
V(C,N) upon bond stretching follows the expected behaviour,
with a flux of electrons towards the lone pairs as the distance
increases (see Figure 1b). In order to develop working equations
along the stretching, we need to understand the evolution of
the main parameters during this process. Bond charges and
bonding basin sizes were found to change linearly with R (as
shown in Figures 1b and 1c). Similar results for the complete
CH3–X set are provided in Figures S1 and S2.
In the following sections, the interacting potentials for the
kinetic, electrostatic and exchange correlation terms involving
the C–X bond and valence lone pairs will be developed from the
ELF‐IQA partition. In all cases, the difference between the
calculated IQA energy and the DFT obtained one (∆E) was used
to evaluate the numerical integration accuracy. The error held
roughly constant and lower than 1% of the total energy, as
shown in Table S7.
Classical electrostatic interaction energy. Since the ELF basins are
non‐overlapping, the electrostatic interaction between them
can be reasonably well approximated by the Coulombic
interaction between point charges located at the barycenter of
the basin charge density. We have carried out a test of the
performance of such an approximation in the reference
molecule, CH3–NH2. The centre of charges for the C–N bond
only deviates 0.07 a.u. from the ELF attractor. This small
difference is clearly negligible when compared to the bond
length, 2.75 a.u. Hence, monopole electrostatics are expected
Figure 1. a) CH3–X ELF basins (isovalue = 0.8) and populations (at the equilibrium geometry). V(C,H) basins are shown in blue,
V(C,C) and V(C,N) in green, and V(N) in orange. b) V(C,N) and V(N) populations as a function of the C–N bond distance. Linear
regression coefficients: R2 = 0.982 for V(C,N) and 0.989 for V(N). c) V(C,N) and V(N) volumes as a function of the C–N bond distance.
Linear regression coefficients: R2 = 0.631 for V(C,N) and 0.988 for V(N).
to reproduce reasonably well the electrostatic interactions (see
eq. 8).
∝
(8)
Where qi refers to the electronic charge of basin i (be it core,
bond or lone pair). Hence, the overall electrostatic interaction
should follow the classical interacting potential Eelec = B/R + C,
where B and C are constants. For testing this hypothesis, we
used the ELF‐IQA approach to calculate the classical component
of
and
(see eq. 6 and 7) for the interactions
between the C–X basin (V(C,X)) and both the C and X (C(C) and
C(X)) ones. In addition, we computed the interactions between
the X lone pairs (V(X)) and X (C(X)). As previously explained,
these interaction between basins represents the interaction
between the C–X bond and C and X atoms, as well as the
interactions between the lone pair in X and the X core,
respectively. We represented these contributions against 1/R.
Results for the interaction between the pairs of valence basins
in methanamine are shown in Figure 2 (see Figure S4 for the
results involving all other molecules). As it can be seen, the
linear regression fittings present very good correlation
coefficients, with R2 being higher than 0.97 in all cases, for both
intra and inter‐basin contributions. The good agreement
confirms that the ELF maximum can be used to approximate a
point charge behavior. Remarkably, the linear correlation
between the electrostatic interactions and 1/R also holds for
intra‐basin interactions, where qA = qB (i.e. self‐interaction can
be neglected in the energy‐model). Note that repulsive
interactions are obtained for intra‐basin terms, since they
correspond to electron‐electron repulsions, whereas inter‐
basin terms are positive, due to the extra attractive contribution
from the nucleus. This agreement is also maintained when the
basin charges (i. e. the electron density integrated over the
basin volume) are taken into account (see Figure S5). Overall,
this indicates that zero‐th order electrostatics is a reasonably
accurate approach for ELF basins.
Kinetic energy. In order to analyse the evolution of the valence
electron pairs kinetic energy, we can assume that the electron
density in the low density region (i.e. bonds far from the core)
can be described by a zero‐th order expansion of the kinetic
/
energy density of a homogeneous electron gas,
.
Assuming now a linear behavior of charges upon stretching (as
shown in Figures 1b and S2), we obtain a simple expression
relating the kinetic energy of valence basins with distance (see
eq. 9). The development of eq. 9 is provided in the Supporting
Information.
/
(9)
The expression provided in eq. 9 depends on the bond basin
radius (RB). In order to verify whether we can relate it with the
C–X bond distance, we calculate RB as a function of R. For that,
we subtracted the core radii to the interatomic distance, as
proposed by Savin et al.34 The results show that RB (and RLP) are
proportional to R (see Figure S3). Therefore, we can develop a
working expression of the form: T ∝ R‐2. The validity of this
relation for the kinetic energy of the valence basins of CH3–NH2,
V(C,N) and V(N), is proven in Figure 3. The fittings for other
molecules are provided in the Supporting Information (Figure
S6). Overall, the agreement within the whole series of
Figure 2. ELF‐IQA computed classical electrostatic interaction
energy (intra and inter) against 1/R for a) V(C,N) and, b) V(N) in
CH3–NH2. Linear regression coefficients: R2 = 0.978 for Eintra
V(C,N); 0.995 for Einter V(C,N)‐C; 0.996 for Einter V(C,N)‐N; 0.989 for
Eintra V(N); and 0.994 for Einter V(N)‐N.
Figure 3. ELF‐IQA computed bond kinetic energy against 1/R2
for V(C,N) and V(N) basins in CH3–NH2. Linear regression
coefficients: R2 = 0.997 for V(C,N) and 0.984 for V(N).
molecules leads to regression coefficients, R2, ranging from
0.984 to 1.00 for both, bonds and lone pairs.
Exchange‐Correlation energy. Finally, let us examine the quantum
mechanical contributions. Exchange‐Correlation interactions have
been shown to follow a linear behavior with the delocalization index,
δAB, according to eq. 10.35
(10)
Delocalization indices between QTAIM atoms have been
shown to decay exponentially with the inter‐centre distance for
insulators,36 as they depend on orbital overlap. In the case of
ELF partitions, we have found that δAB has a clear hyperbolic
behavior (that is, δAB = k/R) for interactions between the bond
and core basins in the range of distances considered (as shown
in Figure S7). Accordingly, the effective expression for the
exchange‐correlation energy should follow eq. 11. Figure 4
shows how well this relation holds for the amine, the fittings for
all the other molecules being provided in Figure S8 of the
Supporting Information. Very good linear regression
coefficients, R2 > 0.99 in most cases, were obtained, confirming
the validity of the previous reasoning and the derived
dependencies.
(11)
Interplay of terms. The previous results have important
consequences that are highly relevant in both, force field
development, and quantum chemical topology. Firstly, they
confirm the ability of an electron pair force field (that includes
chemical bonds and lone pairs) derived from topology to
describe a system while using well‐behaved quantum
contributions. The latter are easy to parametrize and to be
added to available “classical” potentials.
Secondly, the quantum mechanical exchange‐correlation
energy term is found to be noticeably smaller than the classical
terms for all systems in the dataset (see Figure 5). As an
Figure 4. ELF‐IQA computed exchange‐correlation energies
against 1/R2 for V(C,N) and V(N) basins with C and N in CH3–NH2.
Linear regression coefficients: R2 = 0.998 for V(C,N)‐C; 0.997 for
V(C,N)‐N; and 0.988 for V(N)‐N.
example, we provide the different contributions for
methanamine in the equilibrium position. For the V(C,N) basins:
TV(C,N) = 2.207 a.u., Eelec‐intra V(C,N) = 0.825 a.u., Eelec‐inter V(C,N)‐C =
‐4.028 a.u., Eelec‐inter V(C,N)‐N = ‐5.723 a.u., Ex‐c V(C,N)‐C = ‐0.044
a.u., Ex‐c V(C,N)‐N = ‐0.058 a.u. For V(N): TV(N) = 3.281 a.u., Eelec‐
intra V(N) = 1.401 a.u., Eelec‐inter V(N)‐N = ‐9.379 a.u., Ex‐c V(N)‐N = ‐
0.138 a.u.
It is interesting to note that exchange‐correlation terms are
two orders of magnitude smaller than classical terms for bond
basins. Nonetheless, they are only one order of magnitude
smaller in the case of lone pairs. This reveals the greater
relevance of quantum effects in the description of lone pairs.
When building an electron pair force field they can be
neglected, in a first approximation, in the case of covalent
bonds, but should be taken into account when developing
accurate interacting potentials for lone pairs. Furthermore, this
prevalence of quantum effects further justifies the explicit
treatment of lone pairs in Force Fields, which are often simply
included in atomic contributions.
As a final check, Table S8 shows that intra‐basin core
energies (kinetic, electrostatic and exchange‐correlation)
remain constant upon elongation. Hence, they can be ignored
in the construction of the interacting potential.
2. Comparison with previous models
Up to now, we have coupled IQA with the ELF topology to obtain
the different interaction energy terms involving Lewis‐like
entities (atoms, bonds and lone pairs). According to the
previous discussion, the total bond energy would be the sum of
kinetic, electrostatic and exchange‐correlation contributions,
even though in most cases the latter will play a minor role.
Interestingly, this framework is formally equivalent to the one
provided by the Bond Charge Model (BCM).6 This approach is a
simple albeit chemically intuitive model for calculating the
energy of molecules (or solids). In particular, a homonuclear
diatomic molecule, say A2, is represented as two cores with +q/2
positive charge, each of them interacting through a bond
Figure 5. Figure 5. ELF‐IQA energy terms for C–N bond in CH3–
NH2.
holding a charge of –q electrons (see Figure 6 top). The bond
charge is allowed to move along the bond length (RB), which is
a fraction of the equilibrium interatomic distance (R), RB = υR.
The total energy, which depends on the charge and the bond
length, is the sum of three different contributions (see eq. 12,
in atomic units).
,
2
D′
(12)
Where E0 is the core energy (equal to 2EA for a homonuclear
molecule, with EA being the core energy of each atom); E1
accounts for the classical electrostatic interactions (core‐bond
and core‐core); and E2 represents the kinetic energy of the bond
electrons moving along the bond length, RB. The model can also
be expanded to heteronuclear systems, say AB, (see Figure 6
bottom) leading to eq. 13. This expression is formally equivalent
to the one obtained for homonuclear molecules.
,
′
D′
(13)
Originally, the model parameters were obtained by fitting to
experimental data.6,7 However, it is remarkable that the BCM
model has the same energy terms that have been analysed by
means of the ELF‐IQA approach (with the exception of the
exchange‐correlation term, which is non‐classical) and that they
present the same dependencies with the interatomic distance,
R. The parallelism with the terms derived from our ELF‐IQA
energy model is thus evident:
Figure 6. Bond Charge Model representation of a homonuclear
molecule (top) and a heteronuclear one (bottom).
order of magnitude smaller). The next section will be devoted
to the analysis of the limits of the IQA‐ELF potential.
3. Limits of the model
′
′
0
The first three equations have been shown to work for our
test set. As for the exchange‐correlation contribution, a
comparison of the scales of Figures 3 and 4 provides a first idea
of the error. As previously stated, bond exchange‐correlation
terms are typically two orders of magnitude smaller than the
other terms for bonds and one order of magnitude for lone pairs
(see Figure 5).
It is important to note that this framework explains the
previous success of the BCM model, as the energy terms with a
classical origin are the only ones that contribute significantly to
the scaling law of the total energy of molecules whenever
electrons are well‐localized. It also justifies the success of ELF‐
based parametrizations of the model. Moreover, it explains why
this model was successful for extended solids in material
science, while not so much applied for open structures (layers,
chains), where lone pairs are usually present.37 As we have seen,
neglecting the exchange‐correlation terms is straight forward
for bonds (two orders of magnitude smaller than kinetic and
electrostatic terms), but not so much for lone pairs (only one
Since the model is based on localized electron pairs, it is
perfectly compatible with the description of covalent bonds.
Accordingly, it may not suffice to capture other types of
interactions. Several examples pertaining to distinct bonding
regimes have been analysed as an attempt to estimate the
range of applicability of the model. On the basis of the extent of
electron pair localization, it should be possible to predict outlier
cases where the IQA‐ELF potential should fail. The following
systems have been addressed: BH3–NH3, BeH2–NH3, CH3–Li and
Li2, as paradigmatic examples of dative covalent bond, non‐
covalent beryllium bond, ionic and metallic systems (see Figure
7).38,39
It was found that both, dative and very polar bonds, still
follow the proposed dependencies for the IQA‐ELF potentials.
Specifically, the BH3–NH3 and BeH2–NH3 molecules lead to
linear regression coefficients, R2, for the electrostatic and bond
kinetic energies higher than 0.97 and 0.99, respectively (see
Table S9 and S10). The exchange‐correlation contribution was
also found to be negligible in comparison with the classical
energy terms, being two orders of magnitude lower, as in the
CH3–X series. Similar results are obtained for CH3–Li.
Interestingly, the Li‐V(C,Li) electrostatic term is smaller than the
C‐V(C,Li) counterpart by almost one order of magnitude. This
result suggests that this contribution is not energetically
meaningful, which can be related with the partially ionic
character of the bond, which leads to the bonding basin being
significantly closer to the carbon than to the lithium core (0.829
Å for C vs 1.169 Å for Li).
molecules, which were of the order of 101 a.u. (kinetic and
electrostatic terms) and 10‐1 a.u. (exchange‐correlation term).
We can thus consider that the model works properly for all the
molecules considered but Li2, for which it is not suitable.
Overall, the model is shown to be valid for covalent and
partially covalent links, while failing for metallic bonds (as the
case of Li2). It should be noted that these two categories can be
easily identified from properties derived from the electron
density. Over the years, numerous attempts have been made to
provide a distinct classification of the chemical bond from
topological characteristics,40,41 with special emphasis on the
metallic bond.42–44 Complex descriptors, as the metallicity index
(ξm) proposed by Ayers et al.44 have been used to further collect
the character of bonds through topological measurements. This
index is constructed to highlight regions of planar density, its
expression being provided in eq. 14.
⁄
/
(14)
Figure 7. ELF basins (isovalue = 0.8) and populations for a) BH3–
NH3, b) BeH2–NH3, c) CH3–Li, and d) Li2. Hydrogenoid, disynaptic
and core basins are shown in blue, green and purple
respectively.
Figure 8. Kinetic, classical (intra and inter) and exchange‐
correlation energy terms for Li–Li bond in Li2. For simplicity,
energy values are multiplied by 104.
The proposed scaling laws of the energy terms do not hold
for Li2. From the visual point of view, a rather remarkable
feature is already identifiable in Figure 7d. The volume of the
bond basin (where a non‐nuclear maximum of the density
appears) is much bigger than in previous cases (898.23 vs 17.91
Å3 in ethane). Moreover, the population in this basin also
follows a different behavior upon stretching. It remains rather
constant (between 1.81 and 1.83 e‐) independently of the Li–Li
interatomic distance. The resulting ELF‐IQA kinetic, electrostatic
and exchange‐correlation energy terms are shown in Figure 8.
It is noteworthy that all the terms are very small, of the order of
10‐4 a.u., very different from the ones obtained for CH3–X
High values of ξm are indicative of metallic character
(typically ξm > 25 in solids); while weak metallic bonds are
identified by ξm values between 1 and 5. When ξm is inferior to
1, the bond presents a non‐metallic character. Bonds of all the
previous molecules were characterized through their electron
density, ρ(r), its Laplacian, 2ρ(r), and the aforementioned
derivative descriptor at the bond critical point. Given that local
topological indices extrapolate the characteristics of a single
point to a large chemical entity, a larger basis set has been used
to guarantee converged densities and robustness. Results are
presented in Table 1.
First of all, it is clear that the limiting cases we chose lead
indeed to positive Laplacians and larger values of ξm. The
metallicity index for Li2 is much higher than for the rest of the
considered bonds, which correlates with the breakdown of our
model. Furthermore, the results do partially justify the lesser
degree of accuracy of the model for the B–N, Be–N and C–Li
bonds, as they exhibit greater ξm indices and positive Laplacian
values at their BCP. This feature can be related to their only‐
partial covalent nature. All this is compatible with the basic idea
encompassed here: localized pairs can be parametrized as point
charges, so that when electrons indistinctly delocalize over a
Table 1. Topological characteristics of the selected bonds.
Calculations were performed at the B3LYP/6‐311G(d,p) level of
theory.
2 BCP (a.u)
Bond
BCP (a.u)
ξm,BCP*
C–C
0.238
‐0.532
‐5.518
C–N
0.261
‐0.670
‐5.116
‐0.504
‐6.560
C–O
0.256
‐0.022
‐130.6
C–F
0.233
0.420
1.631
B–N
0.099
Be–N
0.057
0.337
0.801
C–Li
0.044
0.213
0.821
Li–Li
0.013
0.002
12.78
* ξm is not defined when 2ρ < 0, yet it can be calculated to
exemplify the significant difference between bonds.
larger part of the system, the model fails. Contrarily, highly
covalent bonds, with well localized pairs around their BCP can
be assumed to be properly described by the model hereby
presented.
Conflicts of interest
There are no conflicts to declare.
Acknowledgements
Conclusions and outlook
We have presented a simple energy model based on the ELF
topology for the stretching of bonds that explains the
interaction between electron pairs while retaining their
quantum mechanical character. Kinetic, electrostatic and
exchange‐correlation terms have been shown to follow
distance dependencies that are akin to straightforward scaling
laws. Electron pairs, as described by the Electron Localization
Function, can be modelled from the homogeneous electron gas
point of view. The proposed scaling behaviours have proven to
work reasonably well for different polarities (from homonuclear
to highly polar bonds, including non‐conventional bonds).
Whenever the electron pair fails to describe bonding, like in
metallic bonds, or when highly delocalized bonding regimes set
in, the model is expected to fail. We have also shown how
simple local measures can be introduced to identify these
situations.
Moreover, the energy model hereby introduced is able to
explain the success of simple previous proposals, such as the
Bond Charge Model, and its updated version, the ELF‐BCM
model.37 In both of them, the quantum nature of the electrons
was neglected. Our test set shows that, in general, the quantum
mechanical contribution (represented by the exchange‐
correlation term) is much smaller than the other terms for
bonds. On the contrary, quantum contributions become more
important as electron delocalization increases, as in the case of
lone pairs. Provided that lone pairs are of significant importance
in many chemical systems that are usually modelled with Force
Field approaches, we hereby justify the careful consideration of
their position and electrostatic behaviour. In this regard, the
definition of explicit lone pairs has already been considered in
molecular mechanics modelling, either mathematically or
conceptually.45,46
Notably, the development of a molecular energy model such
as the one here devised may have important implications in
other closely related fields, such as conceptual DFT (c‐DFT).47
The existence of a simple parametrization for the energy of a
system would allow to obtain molecular properties
(electronegativity, chemical hardness, etc.) in a simple manner
and starting from chemically meaningful concepts.48,49 As
previously stated, another field on which this energy model may
suppose a breakthrough is in Force Field development. In this
respect, our model provides useful insight on non‐classical
terms and further justifies the design of Force Fields
transcending the all‐atom paradigm. Such Force Fields have
already achieved remarkable success,50 and we expect to foster
these novel modelling methods. The work herein presented
also opens the doors towards the further development of
energy models based on Quantum Chemical Topology.
J.M. acknowledges financial support provided by the Spanish
Ministerio de Ciencia, Innovación y Universidades
(FPU14/06003 and EST17/00161), as well as from the
Universidad de Zaragoza, Fundación Bancaria Ibercaja and
Fundación CAI (CB 6/17). R.L. acknowledges ED388 for a PhD.
grant. A.M.P expresses its gratefulness for the financial support
provided by the Spanish Ministerio de Ciencia, Innovación y
Universidades (CTQ2015‐65790‐P). J.C.‐G. acknowledges
CALSIMLAB and the ANR within the Investissements d’Avenir
program under reference ANR‐11‐IDEX‐0004‐02. In addition,
the resources from the supercomputer “memento”, as well as
the technical expertise and assistance provided by BIFI‐ZCAM
(Universidad de Zaragoza) and the Laboratoire de Chimie
Théorique (Sorbonne Université) are gratefully appreciated.
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