Efficient Syntheses of 2D Materials from Soft Layered Composites Guided by Yield Prediction Model: Potential of Experiment‐Oriented Materials Informatics

Abstract

AbstractExfoliation is a common route to synthesize 2D materials such as monolayered and few‐layered nanosheets. However, it is not easy to control the breaking‐down process. This work shows a new exfoliation strategy for generation of nanosheets from soft layered composites in high yield. Soft layered composites of inorganic hosts and organic guests are exfoliated into nanosheets in organic dispersion media. A simple yield prediction model is constructed on small‐scale experimental data by sparse modeling, a data‐scientific approach, combined with chemical perspective. The prediction model indicates the guest–medium combinations enabling high‐ and low‐yield syntheses of the nanosheets. The high‐ and low‐yield syntheses are actually achieved on different types of layered transition metal oxides in a minimum number of experiments. The number of experiments is reduced by 94%. The experimental optimization realizes further improvement of the yield, namely, shortening the exfoliation time. The present strategies can be applied to obtain a variety of 2D materials through exfoliation. Moreover, the present work suggests that combination of small experimental data, data‐scientific approach, and chemical perspective, i.e., experiment‐oriented materials informatics, has potentials for acceleration of materials design.