The present study sheds light on the long-standing challenges associated with high-voltage operation of LiNi x Mn x Co 1 À 2x O 2 cathode materials for lithium-ion batteries. Using correlated ensemble-averaged high-throughput X-ray absorption spectroscopy and spatially resolved electron microscopy and spectroscopy, here we report structural reconstruction (formation of a surface reduced layer, R 3m to Fm 3m transition) and chemical evolution (formation of a surface reaction layer) at the surface of LiNi x Mn x Co 1 À 2x O 2 particles. These are primarily responsible for the prevailing capacity fading and impedance buildup under high-voltage cycling conditions, as well as the first-cycle coulombic inefficiency. It was found that the surface reconstruction exhibits a strong anisotropic characteristic, which predominantly occurs along lithium diffusion channels. Furthermore, the surface reaction layer is composed of lithium fluoride embedded in a complex organic matrix. This work sets a refined example for the study of surface reconstruction and chemical evolution in battery materials using combined diagnostic tools at complementary length scales. C hemical evolution and structural transformations at the surface of a material directly influence characteristics relevant to a wide range of prominent applications including heterogeneous catalysis 1-3 and energy storage 4,5 . Structural and/or chemical rearrangements at surfaces determine the way a material interacts with its surrounding environment, thus controlling the functionalities of the material [6][7][8][9][10] . Specifically, the surfaces of lithium-ion battery electrodes evolve simultaneously with charge-discharge cycling (that is, in situ surface reconstruction and formation of a surface reaction layer (SRL)) that can lead to deterioration of performance 4,5,11 . An improved understanding of in situ surface reconstruction phenomena imparts knowledge not only for understanding degradation mechanisms for battery electrodes but also to provide insights into the surface functionalization for enhanced cyclability 12,13 .The investigation of in situ surface reconstruction of layered cathode materials, such as stoichiometric LiNi x Mn x Co 1 À 2x O 2 (that is, NMC), lithium-rich Li(Li y Ni x À y Mn x Co 1 À 2x )O 2 , lithium-rich/ manganese-rich (composite layered-layered) xLi 2 MnO 3 Á (1 À x) LiMO 2 (M ¼ Mn, Ni, Co, and so on) materials, is technologically significant as they represent a group of materials with the potential to improve energy densities and reduce costs for plug-in hybrid electric vehicles and electric vehicles [14][15][16][17] . Practical implementation of some of these materials is thwarted by their high first-cycle coulombic inefficiencies [17][18][19][20] , capacity fading 18,21 and voltage instability [20][21][22] , especially during high-voltage operation. Specifically, high-voltage charge capacities achieved in lithiumrich/manganese-rich layered cathodes are directly associated with various irreversible electrochemical processes including o...

Lead free perovskite solar cells based on a CsSnI3 light absorber with a spectral response from 950 nm is demonstrated. The high photocurrents noted in the system are a consequence of SnF2 addition which reduces defect concentrations and hence the background charge carrier density.

Abstract. Although the formalism that allows the calculation of alloy thermodynamic properties from first-principles has been known for decades, its practical implementation has so far remained a tedious process. The Alloy Theoretic Automated Toolkit (ATAT) drastically simplifies this procedure by implementing decision rules based on formal statistical analysis that frees the researchers from a constant monitoring during the calculation process and automatically "glues" together the input and the output of various codes, in order to provide a high-level interface to the calculation of alloy thermodynamic properties from first-principles. ATAT implements the Structure Inversion Method (SIM), also known as the Connolly-Williams method, in combination with semi-grand-canonical Monte Carlo simulations. In order to make this powerful toolkit available to the wide community of researchers who could benefit from it, this article present a concise user guide outlining the steps required to obtain thermodynamic information from ab initio calculations.

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We demonstrate strong potential of computational screening and germanium iodide perovskite compounds for photovoltaic applications.