Timothy Flack1, Samuel A Jobbins2, Salah Eddine Boulfelfel3, Stefano Leoni1. 1. Materials Discovery Group, School of Chemistry, Cardiff University, C10 3AT Cardiff, U.K. 2. School of Medicine, Cardiff University, C10 3AT Cardiff, U.K. 3. School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0100, United States.
Abstract
LiMPO4 (M = Mn, Fe) olivine phosphates are important materials for battery applications due to their stability, safety, and reliable recharge cycle. Despite continuous experimental and computational investigations, several aspects of these materials remain challenging, including conductivity dimensionality and how it maps onto Li pathways. In this work, we use a refined version of our finite temperature molecular dynamics "shooting" approach, originally designed to enhance Li hopping probability. We perform a comparative analysis of ion mobility in both materials, focused on many-particle effects. Therein, we identify main [010] diffusion channels, as well as means of interchannel couplings, in the form of Li lateral [001] hopping, which markedly impact the overall mobility efficiency as measured by self-diffusion coefficients. This clearly supports the need of many-particle approaches for reliable mechanistic investigations and for battery materials benchmarking due to the complex nature of the diffusion and transport mechanisms.
LiMPO4 (M = Mn, Fe) olivine phosphates are important materials for battery applications due to their stability, safety, and reliable recharge cycle. Despite continuous experimental and computational investigations, several aspects of these materials remain challenging, including conductivity dimensionality and how it maps onto Li pathways. In this work, we use a refined version of our finite temperature molecular dynamics "shooting" approach, originally designed to enhance Li hopping probability. We perform a comparative analysis of ion mobility in both materials, focused on many-particle effects. Therein, we identify main [010] diffusion channels, as well as means of interchannel couplings, in the form of Li lateral [001] hopping, which markedly impact the overall mobility efficiency as measured by self-diffusion coefficients. This clearly supports the need of many-particle approaches for reliable mechanistic investigations and for battery materials benchmarking due to the complex nature of the diffusion and transport mechanisms.
The need for clean, efficient,
and fast energy storage has grown
exponentially over the past few decades and has been driven predominantly
by global warming, the concurrent diminishing fossil fuel resources,
and the mounting demand for portable electronics and grid storage
systems.[1,2] A significant quantity of research has been
directed toward polyanion compounds with the general formula LiMXO4, where M = Fe, Co, Mn, or Ni and X = P, Mo, W, or S. One
polyanion compound that has garnered a substantial amount of attention
is triphylite or lithium ferrophosphate, LiFePO4 (LFP).
LFP belongs to the olivine family of lithium orthophosphates, whose
orthorhombic crystal structure involves corner-sharing FeO6 octahedra and edge-sharing LiO6 octahedra, which are
linked together by PO4 tetrahedra. LFP exhibits a discharge
potential of ∼3.4 V versus lithium, a theoretical capacity
of 170 mAh g–1, and no obvious capacity fading after
several hundreds of cycles.[3] The excellent
thermal stability of the O–P bond means there is no significant
structural rearrangement upon intercalation/deintercalation of Li+ ions and no structural degradation upon overcharging. This
is typified by its commercialization in 2006 and by the fact that
it is now commonplace among battery devices. Much research has been
directed toward improving the electrochemical performance on LFP[3−7] by using a combination of synthesis methods, including nanoparticulate
coating with electronically conductive phase such as carbon,[8] to enhance on LFP’s intrinsic poor electronic
and ionic conductivity. Fundamental knowledge of the Li+ ion diffusion process on the atomic scale is critical to determining
the governing factors of the electrochemical behavior, including diffusion
pathways and, importantly, their coupling to electronic degrees of
freedom.Experimental studies by Franger et al.[9] estimated Li+ ion diffusion
in LiFePO4 at 10–14–10–13 cm2 s–1. The low figure of experimental
diffusion coefficients has been attributed to a series of material
properties including two phase coexistence (LiFePO4–Li1–FePO4) during charge/discharge, a large miscibility gap
between the end-members at room temperature,[10,11] the unidimensional nature of Li+ ion diffusion,[12,13] and phase transformation during lithiation.[14,15] Puzzlingly, theoretical values predict relatively fast bulk Li+ ion diffusion in the range of 10–9–10–8 cm2 s–1.[13,16] Muon spectroscopy[17] places self-diffusion
in the range (1.8–2.3) × 10–10 cm2 s–1, closer to computed values, pinpointing
the role of the experimental techniques in determining the range of
diffusion coefficients. The understanding of the Li+ ion
diffusion mechanism and relevant pathways within such materials is
therefore a top priority to the development of high-performance battery
materials.Early DFT studies[13] indicated
Li ions
diffuse in one-dimensional channels along [010] and predicted very
low activation barriers (∼0.1–0.2 eV) in comparison
to experiment. Later studies based on interatomic potentials[18] calculated activation barriers (∼0.5
eV) closer to the experimental values[19] (0.54–0.63 eV) while also suggesting lithium ions follow
a nonlinear trajectory along [010], further supported by DFT[13,20] and neutron diffraction[12] studies.Because of the larger distance between adjacent channels (>4.5
Å) and the higher activation barrier of [001] translocations
in comparison to [010], theoretical studies support one-dimensional
[010] Li+ ion diffusion in the ordered structure of LiFePO4.[13,20] However, measurements by Amin et
al.[21] on single crystals indicated
that Li+ conductivity is effectively two-dimensional. Furthermore,
antisite defects generated by swapping Li+ and Fe2+ ions markedly affect the diffusion mechanism and dimensionality
in LiFePO4. First-principles calculations[22] and bond valence methods[23] show
that the formation of Li+/Fe2+ antisite defects
enables diffusion across [010] channels already at low defects concentration
(1–3%), corresponding to as-synthesized LiFePO4.[24,25]Static calculations typically map mechanisms onto minimum-energy
paths over a double-well potential barrier separating adjacent Li
sites. By use of ab initio molecular dynamics simulations,
cross-channel migration was observed[26] upon
formation of Li+/Fe2+ antisite defects. The
activation energy for cross-channel migration Li+ ion moving
along a [010] channel with an antisite Fe2+ ion was calculated
to be 0.491 eV, which was lower than and therefore competitive with
in-channel jumps (0.70–0.74 eV). Although Li/Fe antisite defects
can negatively impact ion mobility by blocking diffusion along [010]
channels, they also open pathways across channels.[19] In a scenario of competitive pathways, molecular dynamics
(MD) simulations allow in principle for a detailed mechanistic analysis
of Li pathways characterized by multiple and complex particle translocation
events, including particle–particle correlations and long sequences
of intersite Li+ jumps.[26] However,
simulating diffusion using straightforward MD requires overdriving
temperature to overcome activation barriers, a factor that can be
expected to reduce the simulation efficiency and blur mechanistic
details.To extend investigation beyond single particle translocation,[27] we proposed the “shooter” method
in conjunction with finite temperature MD, targeting many-particle
Li+ ion diffusion dynamics under consideration of all degrees
of freedom. This approach was able to yield enhanced atomistic details
of Li+ diffusion mechanisms within LiFePO4.
Frenkel defect formation was critical to the mechanism of particle
diffusion, including [010] channel activation via cross-channel [001]
jumps as an important part of the reaction coordinate of Li+ diffusion, while Li+/Fe2+ antisite defects
introduced additional pathways for Li+ ion migration.In this work we present a complete mechanistic analysis of ionic
translocation within two benchmark materials, LiFePO4 and
LiMnPO4 (LMP) based on finite temperature many-particle
“shooter” molecular dynamics. Although advantageous
in terms of redox potential, LMP bears inferior electrochemical performances
compared to LiFePO4, exhibiting poorer Li ion diffusion
and low electronic and ionic conductivities.[19,28] This is attributed to Jahn–Teller instability of d4 Mn3+ ions, which entails MnO6 octahedra distortion
as well as localization of the hole polaron.[29−32] Static Li migration calculations
predicted an even higher barrier for LiMnPO4 (0.62 eV)
compared to LiFePO4 (0.55 eV).[27] Also, [010] channels are indicated as only viable pathways for ionic
translocation. Understanding the mechanism of diffusion, including
relevant pathways and what are major hindrances to ion mobility is
therefore key toward better energy storage materials.The computational
methodology presented in this work is an improved
version of the simulation scheme presented in our previous work.[33] To increase the efficiency of sampling Li+ hopping events during simulations, we introduced systematic
changes to control the shooting regime. This allowed to reduce the
temperature used for a shooting event or momenta redistribution and
helped in increasing the stability of simulations by shortening the
time needed to equilibrate the system after each shooting event. These
important modifications were implemented and tested for LiFePO4 as discussed below and then applied to study Li ions diffusion
mechanism in pristine LiMnPO4 and in the presence of antisite
defects.
Methods and Models
A simulation box
consisting of 1120 atoms (2 × 4 × 5
supercell) was used for both LiFePO4 and LiMnPO4. All molecular dynamics simulations were performed by using CP2K
package[34] in NPT ensemble with periodic
boundary conditions. Newton’s equations of motion were integrated by using a velocity-Verlet
algorithm with a time step of 0.2 fs. Nonbonded van der Waals interactions
were modeled with a Buckingham potential based on a shell model for
M2+ and O2– ions, allowing for polarization
effects.[27,33] Interatomic potentials for LiFePO4 and LiMnPO4 from Fisher et al.[27] were used in this work as they have been shown
to accurately reproduce the experimentally observed equilibrium orthorhombic
structure and defect energetics.To enhance the frequency of
Li+ ions hopping without
exceedingly warming up the nondiffusing part of the system, we used
a modified version of the simulation scheme utilized for Li+ mobility in LiFePO4.[33] The
acceleration of Li+ ions dynamics is achieved by applying
momenta redistribution, so-called “shooting” moves to
all mobile particles in the system, while keeping their positions
unchanged, as discussed in section S1 of the Supporting Information. These perturbations were applied under conservation
of total linear, angular momentum, and kinetic energy. The relaxation
time from velocity autocorrelation function of Li+ ions
(see Figure S3) based on independent standard
molecular dynamics simulation was used to determine the optimal time
interval between successive shooting events. At least 0.5 ps was required
to allow Li+ ions equilibration after a shooting move and
to ensure dynamical decorrelation. Another parameter controlling the
magnitude of shooting moves was the half-width of the Gaussian smearing
function applied to Li+ atoms momenta. Values within the
interval 10–5–10–2 Å/fs,
delimiting weak and strong momenta
perturbations (low and high shooting
regimes), were tested. In all our simulations, a time interval of
2 ps between shooting moves and a half-width equal to 10–4 Å/fs were used, unless otherwise specified.For Li/M
antisites defect creation, randomly selected Li+ ions were
swapped with their nearest metal atom, M. MD simulations
were run for at least 0.8 ns and shooter moves applied every 0.5 ps,
applying a Gaussian half-width of 10–4 Å2/fs.These settings represented a good compromise in
allowing the whole
system to equilibrate after shooting moves while maintaining a good
sampling of Li+ hopping events during the molecular dynamics
simulations. We emphasize that the general mechanistic features are
not affected by a specific choice the shooting moves frequency and
magnitude of momenta perturbations. A detailed description of the
shooter method algorithm is presented in section S1.3 of the Supporting Information.For each system,
self-diffusion coefficients were computed from
a linear fit of time evolution of mean-squared displacement (MSD)
to the Einstein equation ⟨r2 ⟩
= 2dDst (r is displacement of the mobile Li ions, d is dimensionality
of the system, and Ds is the self-diffusion
constant). MSD values were averaged over multiple time origins as
described in section S1.4 of the Supporting Information. Each self-diffusion constant was averaged over data from five independent
runs with different initial velocity distributions.
Results
Li+ ion diffusion
in LiFePO4 and LiMnPO4 is an activated process
biased by energy barriers larger
than kBT, even at room
conditions. By use of standard molecular dynamics simulations, the
frequency of Li+ ions hopping is therefore too low at normal
conditions even for very long running times. Consequently, the derivation
of a self-diffusion constant from mean-squared displacements of Li+ ions is not possible as shown in Figures S4 and S5. A common approach to tackle the time scale problem
in similar processes is trying to increase the frequency of Li+ ions hopping by using high-temperature molecular dynamics
simulations. However, tests for LiFePO4 and LiMnPO4 at 700 and 1000 K did not lead to a noticeable increase in
hopping frequency as evidenced by the flat root mean-squared displacements
curves of Li+ ions shown in Figures S6–S9.To enhance the sampling of hopping events
during the diffusion
process using molecular dynamics methods, we selectively coupled Li+ ions to a heat bath using a method comparable to the stochastic
scheme of an Andersen thermostat. While the temperature of the whole
system is still controlled through the thermostat of the NPT ensemble
at 700 K, Li+ ions are systematically “warmed up”
by transferring kinetic energy from the nondiffusing part of the system
as described in sections and S1. The trajectories generated
by using this simulation methodology were used for diffusion mechanism
analysis in pristine materials and in the presence of defects, for
both LFP and LMP.
Many-Particle Diffusion Mechanism in Ordered
LiFePO4 and LiMnPO4
The overall mechanism
entails sequences of ion translocations taking place principally along
[010] for both LiFePO4 and LiMnPO4. Ionic mobility
is initiated by Frenkel defects creations followed by Li cations migration
as illustrated in Figures and S10 for LiMnPO4 and LiFePO4, respectively. An interstitial double occupancy
and a corresponding vacancy formed an initial Frenkel pair prompted
either by a single jump (Figure a) or as a result of multiple, consecutive Li+ ion hopping events (Figure S10a). In Figure , an interstitial
Li+ ion drifted away from the vacancy via single jumps
along [010] (Figure a–f), while the vacancy was still at the initial position
after 42 ps in LiMnPO4. In LiFePO4, Frenkel
defects were created in the same [010] channel, and the corresponding
vacancies propagated along with Li+ ions as shown in Figure S10b–d. The atomistic details of
ionic mobility in LiFePO4 and LiMnPO4 revealed
from trajectories illustrated in Figures and S10 clearly
highlighted a complex diffusion mechanism involving multiple interacting
particles—one that cannot be reduced to single Li+ ion hopping between adjacent empty sites.
Figure 1
LiMnPO4 (low
shooting regime). Snapshots of a representative
diffusion mechanism within a single [010] channel (vertically). Li+ ions are individually colored (same color for periodic images).
(a) After Frenkel defect creation, double Li occupancy begins to migrate
down the channel and away from the vacancy, minimizing the chance
of recombining (a). The column of Li+ atom remain activated
by this separated Frenkel pair, with single hopping events occurring
sporadically (b, c, d, e). After 42 ps, the Frenkel pair remains separated
(f).
LiMnPO4 (low
shooting regime). Snapshots of a representative
diffusion mechanism within a single [010] channel (vertically). Li+ ions are individually colored (same color for periodic images).
(a) After Frenkel defect creation, double Li occupancy begins to migrate
down the channel and away from the vacancy, minimizing the chance
of recombining (a). The column of Li+ atom remain activated
by this separated Frenkel pair, with single hopping events occurring
sporadically (b, c, d, e). After 42 ps, the Frenkel pair remains separated
(f).Another important aspect of ionic mobility in LiFePO4 and LiMnPO4 is Li+ ion jumps along
[001].
On the basis of single particle activation energies (LiMPO4: M = Fe 2.89 eV, M = Mn 2.83 eV1), Li+ hopping along the c-axis
was considered unlikely. Using our shooter method, we identified sequences
involving cross-channel jumps along [001] as shown in Figures and S12 for LiMnPO4 and LiFePO4, respectively. A single
Li+ ion hop between adjacent channels resulted in the formation
of a Frenkel defect. This created an excess charge around the double-occupancy
site (yellow and pink Li+ ions in Figure b) and a corresponding charge deficiency
was introduced around the vacancy left beyond (empty square in Figure b). Once created,
the double occupancy is rapidly relocated within the [010] channel
(Figure b,c, from
pink/yellow to yellow/light blue Li pairs), without recrossing events.
Particle and vacancy migration mostly occurred as the result of elementary
single-particle migration steps (see Figure (LMP) and Figure S12 (LFP)).
Figure 2
LiMnPO4 (low shooting regime). Snapshots of a [001]
cross-jump (horizontal) and subsequent events. Coloring distinguishes
Li+ ions within [010] channels (vertical), except for periodic
images. Colors in adjacent channels are unrelated. After an initial
cross-jump (a), the channels are activated in their Li mobility, enabling
diffusion due to the presence of a vacancy in one channel and a double
occupancy in another (b–h), which are unlikely to recombine
due to infrequent recrossings (none was observed).
LiMnPO4 (low shooting regime). Snapshots of a [001]
cross-jump (horizontal) and subsequent events. Coloring distinguishes
Li+ ions within [010] channels (vertical), except for periodic
images. Colors in adjacent channels are unrelated. After an initial
cross-jump (a), the channels are activated in their Li mobility, enabling
diffusion due to the presence of a vacancy in one channel and a double
occupancy in another (b–h), which are unlikely to recombine
due to infrequent recrossings (none was observed).MSD curves were obtained for defect-free LiFePO4 and
LiMnPO4 systems as shown in Figure . Our simulation scheme allowed to reduce
the amplitude of momenta modifications without altering either the
diffusion mechanism or the derived self-diffusion coefficients as
demonstrated by comparison between low and high shooting regimes in Figures S13 and S15 for LiFePO4 (Dslow/Dshigh = 1.06). The computed Li-ion self-diffusion coefficient
in LiFePO4 was (3.87 ± 0.19) × 10–8 cm2 s–1, 1 order of magnitude slower
in comparison to our previous results[2] and
in better agreement with predictions in the range of 10–9–10–8 cm2 s–1 from other theoretical studies.[13,16] In comparison
to experimental studies values in the range of 10–17–10–11 cm2 s–1,[35−37] our results are overestimating self-diffusivity of Li+ ions, partially due to the bias introduced by the shooter method
to speed up ionic mobility. The computed Li-ion self-diffusion coefficient
in LiMnPO4 was (1.19 ± 0.05) × 10–8 cm2 s–1, ∼3 times slower in
comparison to LiFePO4 and few orders of magnitude faster
than theoretical predictions of Shi et al. (∼10–14 cm2 s–1).[38] Experimental measurements of Kwon et
al.(39) on LiMnPO4 nanoparticles
reported larger diffusion coefficients in the order of 10–12–10–10 cm2 s–1.
Figure 3
Li+ ions MSD vs time in LiFePO4 (black line, Ds = (3.87 ± 0.19) × 10–8 cm2 s–1) with ωf =
0 ns, ωt = 3.7 ns, and ωs = 75 ps,
and in LiMnPO4 (gray line, Ds = Ds = (1.19 ± 0.05) × 10–8 cm2 s–1) with ωf = 0 ns, ωt = 3.25 ns, and ωs = 75 ps. Both curves were averaged over multiple time origins.
Li+ ions MSD vs time in LiFePO4 (black line, Ds = (3.87 ± 0.19) × 10–8 cm2 s–1) with ωf =
0 ns, ωt = 3.7 ns, and ωs = 75 ps,
and in LiMnPO4 (gray line, Ds = Ds = (1.19 ± 0.05) × 10–8 cm2 s–1) with ωf = 0 ns, ωt = 3.25 ns, and ωs = 75 ps. Both curves were averaged over multiple time origins.The cross-channel hopping along [001], although
less frequent,
helped increase ionic mobility by promoting the creation of Frenkel
defects. Figure illustrates
an increase in Li+ ions MSD for LiMnPO4 by a
factor ∼5 following cross-channel jumps, suggesting an important
role of many-particle charge dynamics in a 2-dimensional conductivity
mechanism, despite ion mobility being dominated by diffusion along
the [010] direction. The same effect on diffusion constants caused
by cross-channel jumps along [100] was observed in LiFePO4, as shown in Figure S14 and LiMnPO4 in Figure S16. The two figures
represent the time evolution of MSD of Li+ ions before
and after a cross-channel jump from the same trajectory.
Figure 4
Li+ ions MSD vs time in LiMnPO4 before (black
line, Ds = (6.42 ± 0.81) × 10–9 cm2 s–1) and after (gray
line, Ds = (1.22 ± 0.42) × 10–8 cm2 s–1) the creation
of double occupancy and vacancy in adjacent [010] channels.
Li+ ions MSD vs time in LiMnPO4 before (black
line, Ds = (6.42 ± 0.81) × 10–9 cm2 s–1) and after (gray
line, Ds = (1.22 ± 0.42) × 10–8 cm2 s–1) the creation
of double occupancy and vacancy in adjacent [010] channels.
Effect of Li/M Antisite Defects (M = Fe/Mn)
on Li Diffusion Mechanism in LiMPO4
To investigate
the effect of Li+/M2+ (M = Fe/Mn) antisites
on the migration along the [001] direction and the underlying mechanism,
simulations were performed on both LiFePO4 and LiMnPO4. In accordance with experimental values,[24,25] four Li+/M2+ defects were introduced into
the simulation system, corresponding to a 2.5% of Li+ ions
on antisites (4 out of 160 Li atoms in total).Li ion migration
from channel to channel via interstitial Li+ ion occurred
in two possible ways as shown in Figure . The first involved the replacement of the
antisite Li+ ion by a pristine channel Li+ ion,
while the second entailed a direct bypassing of the antisite Li+ ion by a channel Li+ ion. The sequence of hopping
events was initiated as the result of the combination of two correlated
Li+ ion jumps (blue and orange Li+ ions in Figure a). Local disorder
within the channel was created by an interstitial double occupancy
and a vacancy as shown in Figure b (white square). This was followed by simultaneous
migration of a Li+ ion (green) into antisite positions
and an antisite Li+ ion (red) into the main channel (Figure b,c). The vacancy
and double occupancy pair are now separated in adjacent channels (Figure c). Rearrangement
of the double-occupied site caused further ionic migration within
the left channel (Figure c,d). Antisite recrossing was realized via a direct bypassing
of the antisite Li+ ion (green) by the migrating Li+ ion (red, Figure e), before entering the adjacent channel (Figure f).
Figure 5
LiMnPO4. Snapshots
illustrating two mechanisms of [001]
cross-jump migration. Li+ are individually colored; initial
antisite Li+ is represented as a large red atom. The sequence
is initiated by (a) the combination of two single Li+ jumps.
The [001] migration is realized through the swapping of a channel
Li+ ion (green) and the antisite Li+ (red) (b).
The double-occupied site migrates as the result of single particle
jumps (c, d). A second mechanism of [001] migration involves a Li+ ion revolving past the antisite Li+ ion (green)
(e). This second [001] migration terminates into a different channel
compared to the original migration (f).
LiMnPO4. Snapshots
illustrating two mechanisms of [001]
cross-jump migration. Li+ are individually colored; initial
antisite Li+ is represented as a large red atom. The sequence
is initiated by (a) the combination of two single Li+ jumps.
The [001] migration is realized through the swapping of a channel
Li+ ion (green) and the antisite Li+ (red) (b).
The double-occupied site migrates as the result of single particle
jumps (c, d). A second mechanism of [001] migration involves a Li+ ion revolving past the antisite Li+ ion (green)
(e). This second [001] migration terminates into a different channel
compared to the original migration (f).This sequence of events illustrates significant
correlation between
mobile ions in adjacent channels and supports a two-dimensional diffusion
scenario promoted by the inclusion of Li+/Mn2+ antisites. The overall effect of the antisite defects was assessed
by quantifying variations in Li+ ions diffusivity in LiFePO4 and LiMnPO4. By use of MSD data in Figures and S19, the derived Li+ ions self-diffusion coefficients were
(8.76 ± 0.16) × 10–8 and (2.01 ±
0.08) × 10–7 cm2 s–1 in LiMnPO4 and LiFePO4, respectively. Compared
to (1.19 ± 0.05) × 10–8 and (3.87 ±
0.19) × 10–8 cm2 s–1 for pristine LiMnPO4 and LiFePO4, respectively,
it corresponds to an ∼7 and ∼5 times increase in Li+ ions diffusivity. As for LiFePO4, coupling between
channels is enhanced upon the inclusion of Li+/Mn2+ antisites. A channel-resolved comparison of MSD in LiMnPO4 with antisite defects proves the activation of the [001] direction
(Figure ).
Figure 6
MSD vs time
for all Li+ ions in all five simulations.
MSDs are averaged over multiple time origins. ωf =
0, ωt = 1 ns, and ωs = 50 ps.
Figure 7
MSD vs time of Li+ ions for LiMnPO4 with
antisite defects. Total MSD is shown in red, along [010] in green,
and [001] in blue. Self-diffusion coefficient values are (8.76 ±
0.16) × 10–8 cm2 s–1 (total), (5.78 ± 0.14) × 10–8 cm2 s–1 ([010]), and (1.30 ± 0.12) ×
10–8 cm2 s–1 ([001]).
MSD vs time
for all Li+ ions in all five simulations.
MSDs are averaged over multiple time origins. ωf =
0, ωt = 1 ns, and ωs = 50 ps.MSD vs time of Li+ ions for LiMnPO4 with
antisite defects. Total MSD is shown in red, along [010] in green,
and [001] in blue. Self-diffusion coefficient values are (8.76 ±
0.16) × 10–8 cm2 s–1 (total), (5.78 ± 0.14) × 10–8 cm2 s–1 ([010]), and (1.30 ± 0.12) ×
10–8 cm2 s–1 ([001]).
Discussion
Using the shooter enhanced
sampling technique in combination with
shooter molecular dynamics simulations, for both LiFePO4 and LiMnPO4 the main diffusion pathways are in the [010]
direction (easy axis). Migrations along the [001] axis for both materials
were also observed, albeit as minority component in the overall diffusive
process, indicating a coupling between adjacent [010] channels, which
markedly enhances the measured diffusion constant. This coupling is
a result of many-particle dynamics and remains elusive to static calculations
based on defect energies.General mechanistic features of [010]
diffusion for both LiFePO4 and LiMnPO4 are the
following:Diffusion is initiated by the formation of a Frenkel
defect within easy [010] channels.Frenkel
defects introduce disorder within channels in
the form of Li+ double-occupied cages and a corresponding
vacancy localized at some distance, which was found to be larger for
LiFePO4.Frenkel pairs are
mobile species that can migrate due
to single particle events (hopping into adjacent channel sites) or
a combination of events (extended hopping).Single-particle potential energy calculations[27] have shown diffusion between channels/across
channel boundaries
to have a significantly higher activation energy in comparison to
diffusion within “easy” channels. The shooter method
has shown that in a many-particle system collective dynamics is more
than the sum of isolated intersite hopping events. Although migration
along [001] represents a small fraction of the reaction coordinate,
it has significant implications. There is indeed experimental evidence
that also suggests the [001] direction to be an active direction of
diffusion within LiFePO4.[21] No
corresponding experiments suggest that [001] migration is part of
the reaction coordinate of Li+ diffusion within LiMnPO4, which we demonstrate here computationally. Accordingly,
LiMPO4 diffusion should be better characterized as 2D rather
than restricted to easy channels only.Migration along [001]
also implies Frenkel pair mobility within
[010] channels, but with a subtle difference. The result of a cross-channel
jump (along [001]) is the formation of Frenkel pairs across channels, effectively introducing an additional diffusive dimension.
One channel possesses an excess charge, manifested a double-occupied
site, while an adjacent one hosts a corresponding vacancy. It has
already been established that Frenkel pairs are more mobile and rapidly
migrate within channels. Once they begin to migrate within separate
channels, the Frenkel pair has a vanishing recombination probability.
In fact, no recombination was observed during our MD simulations.
This way, diffusion is permanently affected.Self-diffusion
coefficients were estimated for both materials by
calculating multiple-reference Li+ ions MSD via the Einstein
equation. Calculated values are consistent with other theoretical
studies[13,16,33] for LiFePO4. Values calculated for LiMnPO4 were lower than
for LiFePO4, which trendwise agrees with the literature.[38,39]The overestimation of self-diffusion coefficients calculated
from
the shooter method may be in part explained by the necessary bias
introduced into the system, despite low shooting regimes. However,
the mechanism of Li+ ion diffusion has been shown to be
robust even for larger perturbations. The shooter method appears therefore
suitable for mechanistic investigations as it correctly predicts diffusion
trends.Previous theoretical studies[2,19,23] have shown Li+/M2+ (M = Fe2+/Mn2+) antisite defects to provide
alternative routes for diffusion
between channels due to additional diffusion pathways between channels
in both LiFePO4 and LiMnPO4. The shooter method
indicates two distinct mechanisms for cross-channel [001] diffusion:
(1) Diffusion across the channels may occur via the replacement of
the antisite Li+ ion with a pristine channel Li+ ion. (2) Diffusion across the channels also occurs via direct crossover
of a channel Li+ ion past and antisite
Li+ ion, without displacement of the latter. The calculated
self-diffusion coefficients reveal an overall increase in diffusion
for both the [010] and [001] direction. The increase in the [001]
direction can be attributed to additional pathways for diffusion introduced
by the antisites. The increase in the [010] direction is interesting
as antisite Fe2+ ions could be expected to inhibit diffusion
within channels. An overall increase in the [010] direction is a consequence
of increased interchannel couplings that reduces Frenkel pair recombination
probability.Shooting trajectories can be used as basis for
free-energy sampling
approaches, like umbrella sampling. Therein, constrained MD is used
on trajectory slices, corresponding to intermediate points along the
reaction coordinate. In Figures S20–S22 snapshots from constrained NVT MD are presented (168 atoms box),
where force calculations are based on the GFN-xTB transferrable potential[40] (see the Supporting Information for details). Sequences of Li+ ion displacements correspond
to force-field simulations, including the role of Frenkel pair recombination
and the role of many-particle dynamics. While the computation of an
accurate free energy profile is beyond the scope of this work, the
transferability of the mechanistic picture across potentials further
validates our findings.
Conclusions
In this work, the shooter
MD approach to collective ion dynamics
was further refined and extended to the investigation of Li diffusion
mechanisms in LiMnPO4 and LiFePO4. The parameter
space of the shooter method was investigated by allowing for a high and a low shooting regime, corresponding
to variable broadening of kinetic energy redistribution. As well as
providing a more reliable calculation of diffusion constants, the
mechanistic details of Li+ ion diffusion revealed by the
shooter method remain the same regardless of the severity of the shooter
perturbation. The mechanistic scenarios presented in this work support
a many-particle perspective on Li ion mobility, which we argue should
consistently replace any single-particle approach if a mechanistic
analysis is intended. In combination with better methods of defect
energy calculation,[41] many-particle assisted
hopping can provide a holistic account of ion mobility in relevant
materials. The coupling role of transversal jumps across channel boundaries
has a significant impact on diffusion constant moduli, on the understanding
of dimensionality of diffusion within materials, and on the design
of novel battery materials. While in this work we have used polarizable
force fields, which do not allow for electronic degrees of freedom,
the shooter method can be expected to be applicable in combination
with suitable potentials, based on tight-binding or ML potentials.
Additionally, force-field fitting on equilibrium properties only does
not guarantee control over hopping potential energy barriers. We expect
the problem of the general overestimation of diffusion constants,
common to most computational approaches, to be addressable in a scenario
that explicitly allows for coupling of ion dynamics with electrodynamics,
which is among the current challenges of battery simulations.
Authors: Thomas D Kühne; Marcella Iannuzzi; Mauro Del Ben; Vladimir V Rybkin; Patrick Seewald; Frederick Stein; Teodoro Laino; Rustam Z Khaliullin; Ole Schütt; Florian Schiffmann; Dorothea Golze; Jan Wilhelm; Sergey Chulkov; Mohammad Hossein Bani-Hashemian; Valéry Weber; Urban Borštnik; Mathieu Taillefumier; Alice Shoshana Jakobovits; Alfio Lazzaro; Hans Pabst; Tiziano Müller; Robert Schade; Manuel Guidon; Samuel Andermatt; Nico Holmberg; Gregory K Schenter; Anna Hehn; Augustin Bussy; Fabian Belleflamme; Gloria Tabacchi; Andreas Glöß; Michael Lass; Iain Bethune; Christopher J Mundy; Christian Plessl; Matt Watkins; Joost VandeVondele; Matthias Krack; Jürg Hutter Journal: J Chem Phys Date: 2020-05-21 Impact factor: 3.488
Authors: Ian D Johnson; Thomas E Ashton; Ekaterina Blagovidova; Glen J Smales; Mechthild Lübke; Peter J Baker; Serena A Corr; Jawwad A Darr Journal: Sci Rep Date: 2018-03-07 Impact factor: 4.379