High-performance organic energy storage has attracted much interest as a future battery. Organic anode has been developed as an alternate of graphite in the past decade. However, the design strategies are not fully studied for further development. The present work shows experiment-oriented materials informatics (MI) for efficient exploration of design strategy and new compounds for an active material of high-performance organic anode. A few important factors to achieve high specific capacity are extracted from training dataset containing experimentally measured specific capacity, calculation results, and literature data of the model compounds using sparse modeling, an informatics approach. Although the prediction model is not sufficiently accurate, the model assists in exploration of new compounds in combination with experience and intuition of experimental scientists. New compounds with high specific capacity, such as 227 mA h g -1 at 100 mA g -1 for benzo[1,2-b:4,5-b′]dithiophene (BdiTp), are efficiently discovered in a minimum number of experiments. Furthermore, polymerization of BdiTp exhibits the enhanced performances, such as 933 mA h g -1 at 20 mA g -1 and cycle stability, and rate performance. MI combined with experiment, calculation, and data accelerates design new materials and functions by experimental scientists having their small data, experience, and intuition.

Conducive polymers have a wide range of applications originating from their π-conjugated systems. The redox reactions of conductive polymers with doping and dedoping of anions have been applied to cathodes for charge storage. In contrast, the redox reactions with cations have not been fully studied in anodes for charge storage. Here, we found that the nanostructures of conductive polymers, such as polypyrrole (PPy) . The introduction of a carboxy group to the pyrrole and thiophene rings enhanced the specific capacities up to 730 and 963 mAh g -1 , respectively. The enhanced electrochemical properties were not observed in the bulk-size conductive polymers. The results suggest that conductive-polymer nanostructures have potential for developing metal-free, high-performance charge storage devices.

Development of high-performance organic energy storage is one of the important challenges in recent materials science. Molecular design and synthesis have potential for enhancement of the performances. Efficient exploration and design of the molecules are required in a wide search space. In the present work, a capacity prediction model for organic anodes was constructed on small experimental data by sparse modeling, a method of machine learning, combined with our chemical insights. The straightforward linear regression model facilitated discovery of a high-performance active material for organic anodes in a limited number of experiments. A recommended compound, 5-formylsalicylic acid (SA-CHO), showed one of the highest performances in recent works, i.e., a specific capacity of 873 mA h g −1 at 100 mA g −1 (sample number: n = 3) with rate performance and cycle stability. The model can be applied to explore organic anode active materials with higher specific capacity.

A new experiment‐oriented materials informatics facilitates finding of general design strategy and new compounds for high‐performance organic anodes as alternate of graphite for lithium‐ion battery. Polymerization of the discovered compound realizes the enhanced specific capacity, cycle stability, and rate performance. More details can be found in article number 1900130 by Hiromichi Numazawa, Yuya Oaki, and co‐workers.