Current state-of-the-art Na-ion battery cathodes are selected from the broad chemical space of layered first-row transition-metal (TM) oxides. Unlike their lithium-ion counterparts, seven first-row layered TM oxides can intercalate Na ions reversibly. Their voltage curves indicate significant and numerous reversible phase transformations during electrochemical cycling. These transformations are not yet fully understood but arise from Na-ion vacancy ordering and metal oxide slab glide. In this study, we investigate the nature of vacancy ordering within the O3 host lattice framework. We generate predicted electrochemical voltage curves for each of the Na-ion intercalating layered TM oxides by using a high-throughput framework of density-functional-theory calculations. We determine a set of vacancy-ordered phases appearing as ground states in all NaxMO2 systems and investigate the energy effect of the stacking of adjacent layers.

All-solid-state Na-ion batteries that operate at or close to room temperature are a promising next-generation battery technology with enhanced safety and reduced manufacturing cost. An indispensable component of this technology is the solid-state electrolyte that allows rapid shuttling of the mobile cation (i.e., Na+) between the cathode and anode. However, there are very few fast Na-ion conductors with ionic conductivity approaching that of the liquid counterparts (i.e., 1 mS cm-1). In this work, we present the synthesis and characterization of a fast Na-ion conductor, cubic Na3PSe4. This material possesses a room-temperature ionic conductivity exceeding 0.1 mS cm-1 and does not require high-temperature sintering to minimize grain boundary resistance, making it a promising solid-state electrolyte candidate for all-solid-state Na-ion battery applications. On the basis of density functional theory, nudged elastic band, and molecular dynamics investigations, we demonstrate that the framework of cubic Na3PSe4 only permits rapid Na+ diffusion with the presence of defects, and that the formation of the Na vacancy (charge-balanced by slight Se2- oxidation) is more energetically favorable among the various defects considered. This finding provides important guidelines to further improve Na-ion conductivity in this class of materials.

Accelerating the discovery of advanced materials is essential for human welfare and sustainable, clean energy. In this paper, we introduce the Materials Project (www.materialsproject.org), a core program of the Materials Genome Initiative that uses high-throughput computing to uncover the properties of all known inorganic materials. This open dataset can be accessed through multiple channels for both interactive exploration and data mining. The Materials Project also seeks to create open-source platforms for developing robust, sophisticated materials analyses. Future efforts will enable users to perform ''rapid-prototyping'' of new materials in silico, and provide researchers with new avenues for cost-effective, data-driven materials design. © 2013 Author(s).

We present the Python Materials Genomics (pymatgen) library, a robust, open-source Python library for materials analysis. A key enabler in high-throughput computational materials science efforts is a robust set of software tools to perform initial setup for the calculations (e.g., generation of structures and necessary input files) and post-calculation analysis to derive useful material properties from raw calculated data. The pymatgen library aims to meet these needs by (1) defining core Python objects for materials data representation, (2) providing a well-tested set of structure and thermodynamic analyses relevant to many applications, and (3) establishing an open platform for researchers to collaboratively develop sophisticated analyses of materials data obtained both from first principles calculations and experiments. The pymatgen library also provides convenient tools to obtain useful materials data via the Materials Project's REpresentational State Transfer (REST) Application Programming Interface (API). As an example, using pymatgen's interface to the Materials Project's RESTful API and phasediagram package, we demonstrate how the phase and electrochemical stability of a recently synthesized material, Li 4SnS4, can be analyzed using a minimum of computing resources. We find that Li4SnS4 is a stable phase in the Li-Sn-S phase diagram (consistent with the fact that it can be synthesized), but the narrow range of lithium chemical potentials for which it is predicted to be stable would suggest that it is not intrinsically stable against typical electrodes used in lithium-ion batteries. © 2012 Elsevier B.V. All rights reserved.