Efficient material development using a combination of thin-film growth techniques and machine-learning approaches in energy applications

Abstract

Machine learning is increasingly attracting attention in the research field of novel material development. Among the various material preparation methods, thin-film technology is actively used in various fundamental researches, industries, and applications for preparing thin films of various types of materials and nanostructured materials. In this article, our recent researches concerning novel material development using a combination of thin-film technologies and machine-learning approaches are presented. Our material development methods with the use of machine-learning approaches achieved more efficient material development compared to previous methods and can be used for the exploration of novel thermoelectric materials.