Efficient recommendation tool of materials by an executable file based on machine learning

Abstract

To accelerate the discoveries of novel materials, an easy-to-use materials informatics tool is essential. We develop materials informatics applications, which can be executed on a Windows computer without any special settings. Our applications efficiently perform Bayesian optimization to optimize materials properties and uncertainty sampling to complete a new phase diagram. We introduce the usage of these applications and show the sampling results for a ternary phase diagram.