Effects of Sublattice Symmetry and Frustration on Ionic Transport in Garnet Solid Electrolytes

Kozinsky, Boris; Akhade, Sneha A.; Hirel, Pierre; Hashibon, Adham; Elsässer, Christian; Mehta, Prateek; Logéat, Alan; Eisele, U.

doi:10.1103/physrevlett.116.055901

Cited by 73 publications

(90 citation statements)

References 31 publications

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“…Lithium ordering coupled to symmetry breaking has also been predicted at other lithium stoichiometries by Kozinsky et al [79], who performed a group-theoretical analysis combined with first-principles energy calculations. Interestingly, this study predicted an ordered phase at x Li =6 with a lower symmetry than the parent cubic phase, with octahedra and tetrahedra occupied in a 3 : 1 ratio, as well as ordered phases at other lithium stoichiometries, again accompanied by spontaneous symmetry breaking and lattice distortion.…”

Section: Summary and Discussionmentioning

confidence: 97%

Lattice-geometry effects in garnet solid electrolytes: a lattice-gas Monte Carlo simulation study

Morgan

2017

R. Soc. open sci.

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Ionic transport in solid electrolytes can often be approximated as ions performing a sequence of hops between distinct lattice sites. If these hops are uncorrelated, quantitative relationships can be derived that connect microscopic hopping rates to macroscopic transport coefficients; i.e. tracer diffusion coefficients and ionic conductivities. In real materials, hops are uncorrelated only in the dilute limit. At non-dilute concentrations, the relationships between hopping frequency, diffusion coefficient and ionic conductivity deviate from the random walk case, with this deviation quantified by single-particle and collective correlation factors, f and fI, respectively. These factors vary between materials, and depend on the concentration of mobile particles, the nature of the interactions, and the host lattice geometry. Here, we study these correlation effects for the garnet lattice using lattice-gas Monte Carlo simulations. We find that, for non-interacting particles (volume exclusion only), single-particle correlation effects are more significant than for any previously studied three-dimensional lattice. This is attributed to the presence of two-coordinate lattice sites, which causes correlation effects intermediate between typical three-dimensional and one-dimensional lattices. Including nearest-neighbour repulsion and on-site energies produces more complex single-particle correlations and introduces collective correlations. We predict particularly strong correlation effects at xLi=3 (from site energies) and xLi=6 (from nearest-neighbour repulsion), where xLi=9 corresponds to a fully occupied lithium sublattice. Both effects are consequences of ordering of the mobile particles. Using these simulation data, we consider tuning the mobile-ion stoichiometry to maximize the ionic conductivity, and show that the ‘optimal’ composition is highly sensitive to the precise nature and strength of the microscopic interactions. Finally, we discuss the practical implications of these results in the context of lithium garnets and other solid electrolytes.

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Section: Summary and Discussionmentioning

confidence: 97%

Lattice-geometry effects in garnet solid electrolytes: a lattice-gas Monte Carlo simulation study

Morgan

2017

R. Soc. open sci.

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“…The dynamics can be driven by classical force fields, with parameters chosen to reproduce experiments or first-principles calculations, or using first-principles (on-the-fly) approaches based on accurate electronic-structure methods. Historically, the garnet family, due to its large unit cells, was studied extensively using classical force field [21,[49][50][51][52]. Force fields were also successfully applied to the LISICON family [31,34]; as an example, Adams and Rao [53] could show via classical simulations of Li 10 GeP 2 S 12 that Li ions (partially) occupy an additional site that was not observed in the first synthesis of the material by Kamaya et al [36], with experimental evidence for this site later provided by Kuhn et al [54] Classical force fields have also been used when studying grain-boundary diffusion, again due to inherently large system sizes, as is the case example in Li-rich antiperovkites [55].…”

Section: Introductionmentioning

confidence: 99%

“…However, the collective nature [21,67,74,75] of Li-ion diffusion in fast conductors makes the estimate of the dominant transitions paths complex. A large-scale screening via estimate of migration barriers would be cumbersome, since the definition of migration pathways remains at this stage humanintensive.…”

Section: Introductionmentioning

confidence: 99%

High-throughput computational screening for solid-state Li-ion conductors

Kahle

Marcolongo

Marzari

2020

Energy Environ. Sci.

124

106

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We present a computational screening of experimental structural repositories for fast Li-ion conductors, with the goal of finding new candidate materials for application as solid-state electrolytes in next-generation batteries. We start from ∼1400 unique Licontaining materials, of which ∼900 are insulators at the level of density-functional theory. For those, we calculate the diffusion coefficient in a highly automated fashion, using extensive molecular dynamics simulations on a potential energy surface (the recently published pinball model) fitted on first-principles forces. The ∼130 most promising candidates are studied with full first-principles molecular dynamics, first at high temperature and then more extensively for the 78 most promising candidates. The results of the first-principles simulations of the candidate solid-state electrolytes found are discussed in detail.of superionic conductors is the recent discovery of Li-argyrodites [22], with the general formula Li 7 PS 5 X (X=Cl, Br, I) or Li 7 PS 6 (sulphur can be replaced with oxygen, but this reduces the ionic conductivity [23]). Third, Li-containing NASICONs (sodium superionic conductors) are phosphates with the structural formula Li 1+6x X 4+2−x Y 3+x (PO

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“…Nevertheless, such methods rely on the crystallographic information they are given and also do not account for the varied or nonspherical geometry of sites [32]. Starting from a prior knowledge of the host structure and possible Li sites, mobile ions can also be automatically assigned to sites based on convex-hull analysis of site polyhedra [10,33]. This topology-based method deals with arbitrary site geometries, eliminates thermal noise and does not require arbitrary distance cutoffs, but does require the site polyhedra to be specified.…”

Section: Introductionmentioning

confidence: 99%

Unsupervised landmark analysis for jump detection in molecular dynamics simulations

Kahle

Musaelian

Marzari

et al. 2019

Phys. Rev. Materials

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Molecular dynamics is a versatile and powerful method to study diffusion in solid-state ionic conductors, requiring minimal prior knowledge of equilibrium or transition states of the system's free energy surface. However, the analysis of trajectories for relevant but rare events, such as a jump of the diffusing mobile ion, is still rather cumbersome, requiring prior knowledge of the diffusive process in order to get meaningful results. In this work, we present a novel approach to detect the relevant events in a diffusive system without assuming prior information regarding the underlying process. We start from a projection of the atomic coordinates into a landmark basis to identify the dominant features in a mobile ion's environment. Subsequent clustering in landmark space enables a discretization of any trajectory into a sequence of distinct states. As a final step, the use of the smooth overlap of atomic positions descriptor allows distinguishing between different environments in a straightforward way. We apply this algorithm to ten Li-ionic systems and perform in-depth analyses of cubic Li7La3Zr2O12, tetragonal Li10GeP2S12, and the β-eucryptite LiAlSiO4. We compare our results to existing methods, underscoring strong points, weaknesses, and insights into the diffusive behavior of the ionic conduction in the materials investigated.

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Effects of Sublattice Symmetry and Frustration on Ionic Transport in Garnet Solid Electrolytes

Cited by 73 publications

References 31 publications

Lattice-geometry effects in garnet solid electrolytes: a lattice-gas Monte Carlo simulation study

Lattice-geometry effects in garnet solid electrolytes: a lattice-gas Monte Carlo simulation study

High-throughput computational screening for solid-state Li-ion conductors

Unsupervised landmark analysis for jump detection in molecular dynamics simulations

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