Multi-ion Conduction in Li3OCl Glass Electrolytes - ACS Publications

Li3OCl, glass electrolyte, Li-ion batteries, diffusion, conductivity, concentration polarization, molecular dynamics simulations, MD, force field, ASS...
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Multi-Ion Conduction in LiOCl Glass Electrolytes Hendrik H. Heenen, Christoph Scheurer, Karsten Reuter, Johannes Voss, and Alan C. Luntz J. Phys. Chem. Lett., Just Accepted Manuscript • DOI: 10.1021/acs.jpclett.9b00500 • Publication Date (Web): 15 Apr 2019 Downloaded from http://pubs.acs.org on April 16, 2019

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Multi-ion Conduction in Li3OCl Glass Electrolytes Hendrik H. Heenen,†§ Christoph Scheurer,† Karsten Reuter,† Johannes Voss,‡ and Alan C. Luntz*‡ † Chair for Theoretical Chemistry and Catalysis Research Center, Technische Universität München, Lichtenbergstr. 4, D-85747 Garching, Germany ‡ SUNCAT Center for Interface Science and Catalysis, SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, California 94025, United States AUTHOR INFORMATION Corresponding Author *E-mail: [email protected].

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ABSTRACT Antiperovskite glasses such as Li3OCl and doped analogs have been proposed as excellent electrolytes for all solid-state Li ion batteries (ASSB). Incorporating these electrolytes in ASSBs results in puzzling properties. This paper describes a theoretical Li3OCl glass created by conventional melt-quench procedures. The ion conductivities are calculated using molecular dynamics based on a polarizable force field that is fitted to an extensive set of density functional theory based energies, forces, and stresses for a wide range of non-equilibrium structures encompassing crystal, glass, and melt. We find high Li+ ion conductivity in good agreement with experiments. However, we also find that the Cl- ion is mobile as well so that the Li3OCl glass is not a single ion conductor, with a transference number t+ ~ 0.84. This has important implications for its use as electrolyte for all solid-state batteries since the Cl could react irreversibly with the electrodes and/or produce glass decomposition during discharge/charge.

TOC GRAPHICS

KEYWORDS Li3OCl, glass electrolyte, Li-ion batteries, diffusion, conductivity, concentration polarization, molecular dynamics simulations, MD, force field, ASSB.

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There is now a large international research effort to develop practical all solid-state Li ion batteries (ASSBs), especially for use in electric vehicles. There are many potential advantages to all- solid-state batteries relative to the conventional liquid electrolyte Li+ ion technology; minimizing safety/fire hazards, enhancing energy density by potentially using Li metal anodes instead of Li+ intercalated graphite, higher power density by eliminating concentration polarization, longer cycle lifetimes and wider temperature ranges. Several solid-state electrolytes have now been discovered that have Li+ ion conductivities at 300 K comparable to or higher than the conventional liquid electrolytes used currently1. Of these, the family of antiperovskites Li3OCl, Li3OBr and mixed halides such as Li3OCl0.5Br0.5 have attracted considerable attention as Li+ superionic conductors that are electrochemically stable at the Li anode2. Although these electrolytes are not Li+ ion conducting as stoichiometric crystalline compounds, they become superionic by virtue of inducing Li+ vacancy defects via aliovalent doping, e. g. Li3-2xMgxOCl, or via mild hydration, yielding Li3-xOHxCl3-7. Typical Li+ ion conductivities of ~ 0.1 mS/cm are achieved. Extensive theoretical work on these systems is in excellent agreement with the measured crystalline conductivities8-19. Braga, et al.20 have shown that Li3OCl and derivates can also form glasses with over a hundred times higher Li+ conductivities ~ 10 mS/cm than the crystalline versions. Furthermore, these glasses are claimed to wet Li metal21 so that the interfacial impedance between the Li metal anode and electrolyte should be minimal22. They exhibit among the highest solid-state Li+ ion conductivities known, with a nominal glass transition at ~350 K by including a small amount of heavy atom aliovalent doping. Braga, et al.23 have also recently constructed ASSBs based on this glass electrolyte that exhibit extremely unusual behavior; an increasing discharge/charge capacity with cycle number that can even surpass the limit of the Li content of the cathode. They

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have suggested that this is caused by the glass electrolyte developing a slow ferroelectric polarization that causes a capacitance discharge/charge in addition to that from the battery process. In this work, we use theory to create a Li3OCl glass by conventional quenching of a Li3OCl melt and then use molecular dynamics (MD) to investigate its ion mobilities. Based on the amorphous nature of a glass, large simulation length and time scales become necessary and because there is no unique structure, ensemble averaging over many typical amorphous structures is required to describe average glass properties24-26. For computational tractability, we therefore utilize a polarizable force field description that is parameterized to describe the Li3OCl crystal, glass, and melt via fitting to an extensive data set of energies, forces and stresses defined by density-functional theory (DFT) (see Supporting Information, SI, sec. III). Using MD based on this polarizable force field as implemented in LAMMPS27, 28, we find that the high Li+ conductivities and activation energies measured by Braga, et al.20 are consistent with a conventional description of a Li3OCl glass. However, we also find that the Li3OCl glass is not a single ion conductor since Cl- ions are also mobile and the Li+ transference number 𝒕" is only ~ 0.84. This means that this glass electrolyte could suffer both from Cl- reaction at the anode and/or cathode, current-induced electrolyte decomposition, and modest concentration polarization. We suggest that the parasitic chemistry caused by the Cl- ion mobility may be one possible reason for the extra discharge capacity observed by Braga, et al.23 in their Li-ion batteries based on this electrolyte. The polarizable force field used to describe the Li3OCl glass is obtained by fitting to conventional DFT and ab initio MD (AIMD) simulations as implemented in VASP29, 30. Static calculations are performed for the crystal and AIMDs are conducted for 200 ps at 300 K in

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modest sized supercells of amorphous Li3OCl of 135 atoms or (Li3OCl)27 at densities close to that of the nominal equilibrium amorphous glass phase and at more expanded volumes at 900 K representing the melt (see Supporting Information (SI), Secs. IIa, IIb, IIIa). The fitting procedure yields a force field which describes well the volume expansion and migration barriers or diffusion coefficients in the crystal, glass, and melt when compared to experiment and both our static DFT and AIMD data (SI, sec. III). Using the fitted force field, ensembles of 20 random amorphous Li3OCl structures are created by subjecting large periodic supercells containing 1080 atoms, (Li3OCl)216, to a simulated meltquench procedure24, 31, 32. To create the members of each ensemble, 20 structurally uncorrelated seeds are extracted from NVT MD melt simulations at 1200 K and quenched to 300 K using an average quench rate of 0.26 K/ps (see SI, sec. Ic). All glass properties usually depend critically on their density or their excess volume relative to that of the crystal. An approximate Li3OCl glass density is estimated from the DFT-based AIMD simulations of the modest sized supercell (cf. SI IIa) which predicts a 13% expansion of the glass volume relative to the crystal (V/Vcrystal = 1.13). The ensemble averaged potential energy for varying densities around this reference density are obtained via NVT MD using the polarizable force field to yield a shallow minimum potential energy at a density corresponding to V/Vcrystal = 1.11 and we use this minimum for all final simulations. Both mechanical and thermodynamic properties typical for glasses are exhibited by the simulated glass (cf. SI section IVb). A glass transition temperature of Tg ~ 425 K is obtained as a change in slope of the specific volume against temperature from NPT MD simulations33 (see SI section IVb). This value of Tg is in very good agreement with the experimental value of 395 K20.

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Figure 1 Typical glass structure after the quench. Li+ is depicted in blue, O-Li and Cl- Li coordination polyhedra are depicted in red and green, respectively.

The instantaneous structure of the glass is defined by sub-nanoscale Li2O and LiCl regions, with an example shown in Figure 1. The predicted X-ray diffraction spectrum (XRD) based on sampling many instantaneous structures over an MD trajectory is in excellent agreement with the experimental one of Braga, et al.20 (see SI, sec IVb). Thus, although there is short-range order in the instantaneous sub-nanoscale regions, no long-range order is observed. The ionic diffusion is evaluated from the mean-square-displacement (MSD) sampled during a 4 ns MD simulation for every member in the ensemble at various temperatures between 300-500 K. As shown in Fig. 2, the MSDs indicate a rapid Li+ ion diffusion, with Cl- ions somewhat mobile as well. In contrast, the O2- ions exhibit negligible mobility. The Li+ and Cl- ions form global diffusion networks which spatially extend throughout the glass as visualized by probability density plots shown in the SI Fig. 11. The long-range transport is indicated by the long-time linear regime in the MSD and this is the basis for the quantitative extraction of ion mobilities (c.f. SI Va,Vb). The ion mobilities are in good agreement with AIMD simulations at the DFT level (c.f. SI IIb), although the length and time scales of the AIMD simulations are not sufficient to guarantee long range diffusion of the Cl ion. It should be noted that for the highest temperature MD at 500 K, the material would usually correspond to a supercooled liquid (see SI

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IVb). This phase-transition is however suppressed by the constrained volume in the NVT simulations. Thus, the 500 K results serve as accelerated glass dynamics to demonstrate the rapid ion mobility. 3.0

300 K

2.0 1.0 0.0

MSD (˚ A2 )

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400 K

20 10 0 200

500 K

100 0

0

1000

2000 3000 time (ps)

4000

Figure 2 Typical mean-square displacements (MSD) vs time from MD simulations for one member of the ensembles at 300, 400, and 500 K. The MSD of Li+ is shown in blue, O2- in red and Cl- in green. Note that 500 K likely represents a super-cooled liquid regime but shows a solid-like behavior (no O2- migration) due to the volume constraint in the NVT ensemble.

The ensemble averaged ionic diffusion for the 20 structurally-uncorrelated members is evaluated by separately averaging the MSDs at each temperature. As a measure for the longrange ion transport, we evaluate the tracer diffusion coefficients 𝐷$∗ (𝛼 = Li+, Cl-) from the Einstein relation as 𝐷$∗ =

1 〈|𝑟⃗. (𝑡) − 𝑟⃗. (0)|4 〉 3 2∆𝑡

where 𝑟⃗. (𝑡) is the position of particle i at time t, ∆𝑡 the sampling time and 〈 〉 refers to the ensemble average over all particles i belonging to species 𝛼34, 35. In addition to the 𝐷$∗ , the idealized ionic conductivity 𝜎 ∗ is determined via the Nernst-Einstein formulation based on the tracer diffusion coefficients as34

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AB

1 𝜎∗ = > 𝑞$4 𝑁$ 𝐷$∗ 3𝑉𝑘< 𝑇 $

where 𝑉 is the volume, 𝑘< the Boltzmann constant, 𝑇 the temperature, 𝑛$ the number of different species 𝛼, 𝑁$ the number of ions, 𝑞$ the charge, and 𝐷$∗ the tracer diffusion coefficient of species 𝛼. However, 𝜎 ∗ is generally not the true ionic conductivity at high ion concentrations due to ionic correlations. A more accurate estimate of the relevant conductivity 𝜎 is instead given by the Einstein formulation of the net charge migration36 as 4

I

1 1 〈F>[𝑞. 𝑟⃗. (𝑡) − 𝑞. 𝑟⃗. (0)]F 〉 𝜎𝒜 = 6𝑉𝑘< 𝑇 ∆𝑡 .

where N is the number of particles i of all species accounted for in set 𝒜. All these quantities are extracted for the individual (𝒜 = Li" or ClN ) and combined Li+ and Cl- (𝒜 = Li" ClN ) motion based on a subsampling-bootstrapping method including only the long-range mobility (c.f. SI Sec. Va,Vb). Spatial correlations between the different ion motions are included in the calculation of the single species conductivities 𝜎𝒜 (i.e. for 𝜎OP and 𝜎QR , see SI eqs. 5, 6) giving the effective single species contributions to the total conductivity 𝜎OPTQRU . The Haven ratio HR = ∗ 𝜎𝒜 /𝜎𝒜 reflects all correlations in the ion transport. Results for 𝜎 ∗, 𝜎 and HR for the ions at 300,

400, and 500 K are given in Table 1 and additional results at other temperatures are given in the SI, Table 5. Single-ion conducting glasses typically exhibit Haven ratios of ~ 0.1-0.537-39. ∗ Table 1 Ionic conductivities 𝜎𝒜 and 𝜎𝒜 and Haven ratios HRx with 𝒜 = 𝐿𝑖 " 𝐶𝑙N , 𝐿𝑖 " , and 𝐶𝑙N for the ensemble average at the equilibrium volume of 1.11 V/Vcrystal at 300, 400, and 500 K obtained from a bootstrapping procedure (c.f. SI Sec. Va, Vb).

𝛔(mS/cm) Li" ClN

T

HR

Li"

ClN

Li" ClN

Li"

ClN

300 𝜎 ∗

1.01

0.97

0.04

-

-

-

𝜎

1.44

1.19

0.25

0.73

0.84

0.18

400 𝜎 ∗

8.54

8.31

0.23

-

-

-

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𝜎 500 𝜎 ∗ 𝜎

23.3 45.2 112

19.8 43.3 94.4

3.47 1.89 17.4

0.37 0.41

0.43 0.47

0.07 0.11

Figure 3 shows an Arrhenius plot of the calculated total ion conductivity (red and yellow) compared to the experimental data (blue and violet) of Braga, et al.20. We find good agreement with the measurements of Braga, et al., both in the magnitudes of total ion conductivity (~ 1-10 mS/cm) and in the activation energy (0.42 eV). Although the activation energy for the glass is even higher than that for the aliovalently doped Li3OCl crystals, the glass exhibits more than an order of magnitude higher conductivity than the crystals. This is because Li+ ions are the mobile species in the glass due to its expanded volume, while in the aliovalently doped crystals only the low concentration vacancies are the mobile charge carriers.4 Similar calculations at other specific glass volumes (V/Vcrystal) demonstrate that the mobility of both Li ions and Cl ions is strongly dependent up on the excess volume (see SI, sec. Va). Similar to the glass, grain boundaries also show increased activation barriers as compared to the Li3OCl crystal40. From this analogy, a relation between increased activation barriers and irregular coordination polyhedra can be infered. 1.5 log(‡Li+ Cl≠ (mS/cm))

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1.0 0.5 0.0

0.42eV 0.54eV

NVT-MD NVT-MD fit exp. heating exp. cooling ‡exp

0.42eV

2.6

2.8 3.0 1000/T (K≠1 )

3.2

Figure 3 Temperature dependence of the total conductivity 𝜎[. T\] U (yellow, “NVT-MD”) in an Arrhenius representation as obtained from the combined Li+ and Cl- motion in comparison to the experimental data extracted for Li3OCl from Braga, et al.20:

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The violet and blue data represent Braga’s measured temperature dependent conductivity during the heating (“exp. heating”) and cooling (“exp. cooling”) of the pristine glass, respectively. The fit and magnitude of the apparent activation energies are indicated for the experimental data and for the simulated data in the same temperature range (red, “NVT-MD fit”). The filled blue marker (𝜎exp) represents the experimentally measured conductivity of 2.1 mS cm-1 at a fixed temperature of 62 °C.

As shown in Table 1, HR is in the expected range of glasses37, 38 and we note that it decreases with temperature for both Li+ and Cl- as the amorphous Li3OCl approaches its glass transition (see SI, Fig. 6). The low Haven’s ratios for Li+ and especially Cl- ion mobilities (c.f. Table 1) suggest a complex correlated transport for both types of ions. To obtain a detailed picture of the ion motion we investigate both the spatial and temporal correlations as discussed in the SI Sec. VIa and VIb. We find that while Cl ion mobility is confined to the interconnected LiCl nanophase regions, Li ion mobility occurs in both sub-nanoscale regions (see SI Sec. VIa and VIb). The mobility is not surprising based on the large excess volume of both phases (c.f. SI Sec. VIc). The Li+ and Cl- ions migrate in approximately opposite net-directions relative to each other due to local internal fields originating from dipoles created by the heterogeneous structure (c.f. SI Sec. Vc). In contrast to the periodic simulation cells, the orientation of the dipoles in space would be random in the macroscopic bulk glass. Nevertheless, in an external field, as present in a battery, the Li+ and Cl- ions would necessarily migrate in opposite spatial directions towards the electrodes. To investigate temporal correlations for the ion motion, we calculate the ensemble averaged 4bc ) as a probability for a second ion hop of species 𝛽 following an initial one by species 𝛼 (𝑝$a

function of the lag time between the two hops as described in detail in the SI, sec. VIb. The results at 300 K are shown in Figure 4 and additional results at 400 K are given in the SI, Fig. S17. The approximately constant ion hop probability at delays > 50 ps reflect the uncorrelated hopping motion of the relevant second ion. The increased probability at < 20 ps reflects the correlation to the first ion’s hop. We see that Li-Li and especially Cl-Cl ion motions are highly

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correlated, while the Li-Cl and Cl-Li motions are only modestly temporally correlated. The latter, however, rationalizes why in the MD and AIMD simulations, Cl- ion hops sometimes were coincident with the Li+ ion hops and sometimes occurred totally uncorrelated to Li- hops. Li-Cl

0.25

p2nd –— (%)

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0.00

0 Li-Li

50 0

Cl-Li 5

0

50

100

150

lag time

Cl-Cl

25 0

0

50

100

150

t (ps)

Figure 4 Ensemble averaged probabilities of a secondary hop 𝛽 to occur after an initial hop 𝛼 for the Li3OCl glass (V/Vcrystal = 1.11) at 300K. The probabilities are given for the ion relations (𝛼-𝛽): Li-Cl, Cl-Li, Li-Li and Cl-Cl as indicated. The x-axis represents the lag time after an initial hop and the y axis the probability of a second ion hop to occur within a time interval of 5 ps and within a radius of 4 Å from the first ion hop.

Because both Li+ and Cl- are mobile in the Li3OCl glass, the Li+ ion transference number significantly deviates from unity with 𝒕" = 𝝈𝑳𝒊T /𝝈𝐋𝐢T𝐂𝐥U ~ 0.83-0.88, depending upon temperature (see Table 1 and SI, sec Vb). Although 𝒕" is still relatively high, the fact that the Li3OCl glass is not strictly a single ion conductor has important implications for its use as a solid-state battery electrolyte. Because Cl- is also mobile, it will migrate to the electrodes (anode during discharge and cathode during charge) and could react with them irreversibly to cause increases in interfacial impedance and/or parasitic chemistry. At the very least, because 𝒕" < 1, concentration polarization resulting from the requirement for charge neutrality in the bulk of the electrolyte will occur. In order to estimate the magnitude of this effect, we use a simple onedimensional cell model that describes the system as a dilute binary electrolyte through a simplified Nernst-Planck equation41, 42, (cf. SI Sec. VId). For a cell length of 100 µm typical for practical applications22 and realized experimentally for this material21, this yields a limiting current density of 11.8 mA cm-2. In reality, the Li3OCl glass is not a dilute homogenous

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electrolyte that could accommodate large linear changes in Cl concentrations throughout the bulk without decomposing. Therefore, current-induced decomposition of the glass electrolyte is also possible. We have developed a theoretical Li3OCl glass electrolyte model by a melt-quench procedure using a polarizable force field fitted to DFT calculations of energies, forces, and stresses for a wide range of non-equilibrium structures of the crystal, glass, and melt. The theoretical model yields thermodynamic properties typical of a glass and reproduces the electrolyte’s reported experimental findings by Braga, et al. These findings include the glass transition temperature, Xray spectra, total ion conductivities, and apparent activation energies20. However, we also find that not only the Li+ ion is mobile in this glass, but also the Cl- ion, resulting in a lowered 𝒕" ~ 0.84. This has important implications for the use of this glass as a solid-state battery electrolyte; possible irreversible reactions at the electrodes, current-induced decomposition of the glass electrolyte, and, at a minimum, moderate concentration polarizations have to be expected. Although we have only studied the stoichiometric Li3OCl glass, we anticipate that 𝒕" may be even smaller for the aliovalently doped Li3OCl glasses. Doping lightly with heavy alkaline earths such as Ba decreases the glass transition temperature and increases the total ion conductivity20. We believe this occurs because the stress induced by doping causes larger excess volume in the glass that facilitates the higher ion mobilities and lower glass temperatures. In partial support of this, we have observed enhanced ion mobilities (especially Cl- ion) in ensembles that were quenched to lower densities. However, whether a conventional glass description is compatible with the extremely low activation energies of 0.06 eV observed by Braga, et al. for Ba doped Li3OCl is unclear.

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It is possible that the strange behavior observed by Braga, et al. for Li ion batteries using the Ba doped Li3OCl glass electrolyte could very well be due to either current-induced dissociation of the glass electrolyte or other parasitic chemistry. Our view on parasitic dissociative processes is also in line with recent discussions of Braga’s original characterization of the Ba doped solid electrolyte. These suggest, that the very low activation energy may originate from formed side products like LiCl∙ 𝑥H2O.7 We see no evidence for dipole alignment in the bulk of the glass in our simulations of 4 ns duration, even in presence of electric fields comparable to those present in a battery as suggested by Braga, et al. In fact, it is unclear to us whether long-range ferroelectric order is compatible with an amorphous phase.

ASSOCIATED CONTENT The Supporting Information is available free of charge on the ACS Publications website. Full details are presented of the computational methods, AIMD simulations, parameterization and validation of the employed force field, volume and quench rate dependence on the glass ensembles from MD simulations, the evaluation of diffusion, conductivity, ion mobility, mechanistic considerations and the one-dimensional binary electrolyte model. AUTHOR INFORMATION Notes The authors declare no competing financial interests. Present Addresses

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§ Hendrik H. Heenen: Catalysis Theory Center, Department of Physics, Technical University of Denmark, DK-2800 Lyngby, Denmark. ACKNOWLEDGMENT This work was partially supported by the U.S. Department of Energy, Chemical Sciences, Geosciences, and Biosciences (CSGB) Division of the Office of Basic Energy Sciences, via Grant DE-AC02-76SF00515 to the SUNCAT Center for Interface Science and Catalysis. H.H.H. gratefully acknowledges the kind hospitality of SUNCAT during his research stay. We also thank S. Rittmeyer and S. Stocker for discussions about the force field parametrization and J. Lawson and J. Haskins for discussions on ion conductivity. Computational resources have been provided by the Leibniz Rechenzentrum der Bayerischen Akademie der Wissenschaften within project pr92me and Tier-0 HPC resources of TGCC Curie have been granted within the Distributed European Computing Initiative by the PRACE-2IP, receiving funding from the European Community’s Seventh Framework Program (FP7/2007-2013) under grant agreement RI-283493. REFERENCES 1. Janek, J.; Zeier, W. G., A solid future for battery development. Nat. Energy 2016, 1, 16141. 2. Zhao, Y.; Daemen, L. L., Superionic Conductivity in Lithium-Rich Anti-Perovskites. J. Am. Chem. Soc. 2012, 134, 15042-15047. 3. Braga , M. H.; Stockhausen, V.; Oliveira, J. C. E.; Ferreira, J. A., The Role of Defects in Li3ClO Solid Electrolyte: Calculations and Experiments. MRS Proceedings 2013, 1526. 4. Stegmaier, S.; Voss, J.; Reuter, K.; Luntz, A. C., Li+ Defects in a Solid-State Li Ion Battery: Theoretical Insights with a Li3OCl Electrolyte. Chem. Mater. 2017, 29, 4330−4340. 5. Song, A.-Y.; Xiao, Y.; Turcheniuk, K.; Upadhya, P.; Ramanujapuram, A.; Benson, J.; Magasinski, A.; Olguin, M.; Meda, L.; Borodin, O.; Yushin, G., Protons Enhance Conductivities in Lithium Halide Hydroxide/Lithium Oxyhalide Solid Electrolytes by Forming Rotating Hydroxy Groups. Adv. Energy Mater. 2018, 8, 1700971. 6. Dawson, J. A.; Attari, T. S.; Chen, H.; Emge, S. P.; Johnston, K. E.; Islam, M. S., Elucidating lithium-ion and proton dynamics in anti-perovskite solid electrolytes. Energy Environ. Sci. 2018, 11, 2993-3002.

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