Concerted efforts continue to be made in the search for superior lithium-ion conducting solids to replace the highly reactive liquid electrolytes typically used in rechargeable batteries. LISICON-type materials have been studied extensively over the last few decades, providing abundant experimental data, but to date no overall design principle for achieving high conductivity has been forthcoming. In this communication we present results of systematic sets of fi rst-principles calculations based on the cluster expansion method, as well as fi rst-principles molecular dynamics (FPMD) simulations carried out to calculate Li-ion conductivities at high temperature, for a diverse range of compositions. A machine-learning technique is used to combine theoretical and experimental datasets to predict the conductivity of each composition at 373 K. The insights obtained show that an iterative combination of fi rst-principles calculations and focused experiments can greatly accelerate the materials design process by enabling a wide compositional and structural phase space to be examined effi ciently.Lithium-conducting oxides in the system LiO 1/2 -A O m /2 -B O n /2 (where m and n denote the formal valences of cations A and B , respectively), known as LISICONs and corresponding to general formula Li 8 − c A a B b O 4 (where c = ma + n b ), [ 1 ] have been intensively studied since the 1970s. The original LISICON composition, Li 3.5 Zn 0.25 GeO 4 , was reported to exhibit an ionic conductivity of over 10 − 1 S cm − 1 at 673 K, [ 2 ] and stimulated a fl urry of new research. Although the conducting properties of many different LISICONs have since been reported by various groups, there are still many compositions that have yet to be synthesized, let alone characterized. In some cases, results from different groups also vary considerably. [2][3][4][5][6] An Arrhenius plot of Li-ion conductivity summarizing previous experimental data is provided as Figure S1 in Supporting Information. Given the urgent need for improved energy storage and power devices, a more effi cient means of designing ionic conductors based on a reproducible and systematic methodology is an imperative for future progress in this fi eld.Thanks to astonishing improvements in computer performance and computational techniques, fi rst-principles calculations based on density functional theory (DFT) are now used routinely for quantitative analysis of ionic conduction in crystals. Combination of DFT calculations with high-throughput and machine-learning techniques is now also considered a viable means of searching for novel lithium battery materials. [7][8][9] For compounds with simple chemistry and structure, the saddle point associated with an ionic jump, from which the activation barrier energy can be extracted in a straightforward manner, is readily calculated. Such methods have already been applied to several Li-battery materials, e.g., LiCoO 2 , [ 10 ] LiFePO 4 , [ 11 ] TiO 2 -B, [ 12 ] and graphite. [ 13 ] The nudged elastic band (NEB) method is popular for su...

Migration of Li+ ions via the vacancy mechanism in LiX (X = F, Cl, Br, and I) with the rocksalt and hypothetical zinc blende structures and Li2X (X = O, S, Se, and Te) with the antifluorite structure has been investigated using first-principles projector augmented wave calculations with the generalized gradient approximation. The migration paths and energies, determined by the nudged-elastic-band method, are discussed on the basis of two idealized models: the rigid-sphere and charged-sphere models. The trajectories and energy profiles of the migration in these lithium compounds vary between these two models, depending on the anion species and crystal structure. The migration energies in LiX with both the rocksalt and hypothetical zinc blende structures show a tendency to decrease with increasing periodic number of the anion species in the periodic table. This is consistent with the widely accepted view that anion species with large ionic radii and high polarizabilities are favorable for good ionic conduction. In contrast, Li2O exhibits the lowest migration energy among Li2X compounds, although O is the smallest among the chalcogens, indicating that electrostatic attractive interactions play the dominant role in the inter-ion interactions in Li2O and, therefore, in the ion migration.

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