Organic cathodes for lithium-ion batteries are one of the most promising and significant materials toward a sustainable society. The molecular design is a key to achieve superior performances beyond inorganic cathodes. The present work shows predictors of the reaction potential, specific capacity, and ideal energy density for organic cathodes. Straightforward prediction models of the performance were constructed by a combination of machine learning and chemical insight, namely, sparse modeling for small data (SpM-S), on a small data set as training data found in the literature. The prediction accuracy was validated using different literature data. The predictors can be applied to explore high-performance organic cathodes in a wide search space efficiently. Moreover, SpM-S afforded straightforward, interpretable, and generalizable prediction models compared to other machine-learning algorithms. The small-data-driven methodology can be applied for further exploration of materials, enhancement of performances, and optimization of processes.

Lithium−oxygen batteries (LOBs) have received great attention as nextgeneration energy storage devices owing to their superior theoretical energy densities. Although there has been considerable technological progress in the field of LOBs, the development of gas diffusion layer materials at the positive oxygen electrode is limited despite their importance in providing an oxygen supply needed to achieve practical power densities. In the present study, we demonstrate the concept of a gas-diffusible current collector, which combines the functions of oxygen mass transport and electron transfer with minimal mass loading. To verify this concept, we fabricated a Ni-coated polymer fiber mesh and investigated its applicability in LOBs. LOB cells equipped with an ultralightweight gas-diffusible current collector exhibit a performance equivalent to that of cells equipped with conventional heavy components at 0.4 mA/cm 2 current density and 4.0 mAh/cm 2 areal capacity. We believe that the concept of an ultralightweight gasdiffusible current collector demonstrated in this study opens future directions in the search for metal−air batteries with high energy and power densities.

Lithium formed dense and smooth two-dimensional lithium clusters on the Al2O3 film, while needle-like lithium grew three-dimensionally on the bare Cu electrode. This leads to superior coulombic efficiency and cycling behaviour.

Li-metal rechargeable batteries are an attractive option for devices that require an extremely high specific energy density, high robustness, and long-term durability, such as high-altitude platform stations. However, Li dendrite growth during charge–discharge cycling causes short-circuit problems. One technical solution is to form an intermediate layer between the Li metal and electrolyte. This interfacial layer should possess mechanical strength, electrochemical stability in the presence of Li, and Li-ion conductivity. In this study, the Li-ion conductivity of spinel-type LiAl5O8 was investigated using first-principles density functional theory and force field molecular dynamics calculations. The calculation results confirmed that stoichiometric LiAl5O8 compounds do not exhibit Li-ion conductivity, whereas off-stoichiometric compounds with excess Li show long-range Li-ion diffusion. The evaluated activation energy was 0.28 eV, which is as low as that of well-known fast Li-ion conductors, such as garnet-type Li7La3Zr2O12. However, the extrapolated Li-ion conductivity at 298 K was relatively low (~ 10−6 S/cm) owing to the limited formation of migration pathways.