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Controlling Li ion transport in glasses at atomic and molecular levels is key to realizing all‐solid‐state batteries, a promising technology for electric vehicles. In this context, Li3PS4 glass, a promising solid electrolyte candidate, exhibits dynamic coupling between the Li+ cation mobility and the PS43− anion libration, which is commonly referred to as the paddlewheel effect. In addition, it exhibits a concerted cation diffusion effect (i.e., a cation–cation interaction), which is regarded as the essence of high Li ion transport. However, the correlation between the Li+ ions within the glass structure can only be vaguely determined, due to the limited experimental information that can be obtained. Here, this study reports that the Li ions present in glasses can be classified by evaluating their valence oscillations via Bader analysis to topologically analyze the chemical bonds. It is found that three types of Li ions are present in Li3PS4 glass, and that the more mobile Li ions (i.e., the Li3‐type ions) exhibit a characteristic correlation at relatively long distances of 4.0–5.0 Å. Furthermore, reverse Monte Carlo simulations combined with deep learning potentials that reproduce X‐ray, neutron, and electron diffraction pair distribution functions showed an increase in the number of Li3‐type ions for partially crystallized glass structures with improved Li ion transport properties. Our results show order within the disorder of the Li ion distribution in the glass by a topological analysis of their valences. Thus, considering the molecular vibrations in the glass during the evaluation of the Li ion valences is expected to lead to the development of new solid electrolytes. [ABSTRACT FROM AUTHOR]

Instead of conventional cation doping strategy, anion doping is a promising new strategy for advances of energy conversion and storage technologies such as batteries, catalysts, electrolysis, and fuel cells. To synthesize mixed‐anion compounds, novel synthesis techniques such as topochemical reaction, high‐pressure reaction, solvothermal reaction have been developed. Despite these excellent synthesis techniques, synthesizable mixed‐anion compounds are still limited. For further expansion of the material exploration of mixed‐anion compounds, herein, an electrochemical anion doping technique is developed, which can flexibly control a species of anion, the doping rate and the degree of anion doping. The concept of the new synthesis technique is verified by F doping to the perovskite oxide La0.5Sr0.5CoO3−δ. Quantitative control of F in the perovskite host material is succeeded by using an electrochemical reactor composed of La0.5Sr0.5CoO3−δ‐BaF2|BaF2|PbF2‐Pb, and phase‐pure F‐doped La0.5Sr0.5CoO3−δ powder is obtained. Moreover, nano‐size crystalline domains with amorphous phase are formed on the particle surface under the high‐rate F doping, suggesting that tuning the anion doping rate enables the control of the formation of metastable phase. As demonstrated, the electrochemical anion doping technique opens up new possibilities for advances of energy materials by utilizing function of anionic species. [ABSTRACT FROM AUTHOR]

For devices encountering long‐term stability challenges, a precise evaluation of degradation is of paramount importance. However, methods for comprehensively elucidating the degradation mechanisms in devices, particularly those undergoing dynamic chemical and mechanical changes during operation, such as batteries, are limited. Here, a method is presented using operando computed tomography combined with X‐ray absorption near‐edge structure spectroscopy (CT‐XANES) that can directly track the evolution of the 3D distribution of the local capacity loss in battery electrodes during (dis)charge cycles, thereby enabling a five‐dimensional (the 3D spatial coordinates, time, and chemical state) analysis of the degradation. This paper demonstrates that the method can quantify the spatiotemporal dynamics of the local capacity degradation within an electrode during cycling, which has been truncated by existing bulk techniques, and correlate it with the overall electrode performance degradation. Furthermore, the method demonstrates its capability to uncover the correlation among observed local capacity degradation within electrodes, reaction history during past (dis)charge cycles, and electrode microstructure. The method thus provides critical insights into the identification of degradation factors that are not available through existing methods, and therefore, will contribute to the development of batteries with long‐term stability. [ABSTRACT FROM AUTHOR]