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Organic-inorganic hybrid materials (OIHMs), such as methylammonium lead triiodide (MAPbI3), have a wide composition space because of the various potential combinations of organic molecules and inorganic cages. However, for unknown OHIMs, it is difficult to predict what kind of crystal structure will be stable without any experimental data. In this work, we report an efficient scheme for predicting crystal structures and phase diagrams of MA-Pb-I systems from first-principles calculations and genetic algorithms. In our scheme, OIHMs are divided into organic molecules and inorganic clusters. A pseudobinary phase diagram of MAI-PbI2 was obtained by predicting structures at each composition. These results indicated that only MAPbI3 and MA2PbI4 are stable phases, consistent with the experiments. In addition, the electronic and optical properties of the predicted structures were calculated and the solar cell performance was evaluated. Thus, our method allowed us to search for unknown OIHMs without any experimental data.

Lithium-ion transport in cathodes, anodes, solid electrolytes, and through their interfaces plays a crucial role in the electrochemical performance of solid-state lithium-ion batteries. Direct visualization of the lithium-ion dynamics at the nanoscale provides valuable insight for understanding the fundamental ion behaviour in batteries. Here, we report the dynamic changes of lithium-ion movement in a solid-state battery under charge and discharge reactions by time-resolved operando electron energy-loss spectroscopy with scanning transmission electron microscopy. Applying image denoising and super-resolution via sparse coding drastically improves the temporal and spatial resolution of lithium imaging. Dynamic observation reveals that the lithium ions in the lithium cobaltite cathode are complicatedly extracted with diffusion through the lithium cobaltite domain boundaries during charging. Even in the open-circuit state, they move inside the cathode. Operando electron energy-loss spectroscopy with sparse coding is a promising combination to visualize the ion dynamics and clarify the fundamentals of solid-state electrochemistry., Understanding lithium ion dynamics holds the key to unlocking better battery materials and devices. Here, by combining electron energy-loss spectroscopy and machine learning, the authors reveal how lithium is extracted from LiCoO2 cathode used in a solid-state battery.

When two different materials come into contact, mobile carriers redistribute at the interface according to their potential difference. Such a charge redistribution is also expected at the interface between electrodes and solid electrolytes. The redistributed ions significantly affect the ion conduction through the interface. Thus, it is essential to determine the actual distribution of the ionic carriers and their potential to improve ion conduction. We succeeded in visualizing the ionic and potential profiles in the charge redistribution layer, or space-charge layer (SCL), formed at the interface between a Cu electrode and Li-conductive solid electrolyte using phase-shifting electron holography and spatially resolved electron energy-loss spectroscopy. These electron microscopy techniques clearly showed the Li-ionic SCL, which dropped by 1.3 V within a distance of 10 nm from the interface. These techniques could contribute to the development of next-generation electrochemical devices.

All-solid-state lithium-ion batteries (LIBs) are one of the promising candidates to overcome some issues of conventional LIBs with liquid electrolytes. However, high interfacial resistance of Li-ion transfer at the electrode/solid electrolyte limits their performance. Thus, it is important to clarify interfacial phenomena in a nanometer scale. Here, we present a new method to dynamically observe the Li-ion distribution and Co-ion electronic states in a LiCoO2 cathode of the all-solid-state LIB during charge and discharge reactions using operando scanning transmission electron microscopy (STEM) and electron energy-loss spectroscopy (EELS). By applying a hyperspectral image analysis of non-negative matrix factorization (NMF) to the STEM-EELS, we succeeded in clearly observing the quantitative Li-ion distribution in the operando condition. We found from the operando observation with NMF that the Li ions did not uniformly extract/insert during the charge/discharge reactions, and the activity of the electroche...