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
We present the Python Materials Genomics (pymatgen) library, a robust, open-source Python library for materials analysis. A key enabler in highthroughput 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 REST API and phasediagram package, we demonstrate how the phase and electrochemical stability of a recently synthesized material, Li 4 SnS 4 , can be analyzed using a minimum of computing resources. We find that Li 4 SnS 4 is a stable phase in the LiSn-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.
To evaluate the potential of Na-ion batteries, we contrast in this work the difference between Na-ion and Li-ion based intercalation chemistries in terms of three key battery properties -voltage, phase stability and diffusion barriers. The compounds investigated comprise the layered AMO 2 and AMS 2 structures, the olivine and maricite AMPO 4 structures, and the NA-SICON A 3 V 2 (PO 4 ) 3 structures. The calculated Na voltages for the compounds investigated are 0.18-0.57 V lower than that of the corresponding Li voltages, in agreement with previous experimental data. We believe the observed lower voltages for Na compounds are predominantly a cathodic effect related to the much smaller energy gain from inserting Na into the host structure compared to inserting Li. We also found a relatively strong dependence of battery properties with structural features. In general, the difference between the Na and Li voltage of the same compound, ∆V Na-Li , is less negative for the maricite structures preferred by Na, and * To whom correspondence should be addressed 1 more negative for the olivine structures preferred by Li. The layered compounds have the most negative ∆V Na-Li . In terms of phase stability, we found that open structures, such as the layered and NASICON structures that are better able to accommodate the larger Na + ion generally have both Na and Li versions of the same compound. For the close-packed AMPO 4 structures, our results show that Na generally prefers the maricite structure, while Li prefers the olivine structure, in agreement with previous experimental work. We also found surprising evidence that the barriers for Na + migration can potentially be lower than that for Li + migration in the layered structures. Overall, our findings indicate that Na-ion systems can be competitive with Li-ion systems.
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