Data science and computer simulation driven design of materials and chemical reactions

Abstract

Materials informatics (MI) research predicting and designing materials chemical compositions for materials application functions that we want received enormous attention owing to rapid progresses in the machine learning and the artificial intelligence methods. National MI projects have been launched at worldwide. Especially with regard to the stress-strain problem for the mechanical functions of structural materials like metals and alloys, a reliable regression model has been proposed from the German projects for MI. On the other hand, MI for electro and optical functions in nanoelectronics and functional materials as well as MI for catalysis still remain to be “yet to come”. In this talk, I will discuss a scope for the MI toward these problems with a special emphasis on more intensive use of computer simulation, which may be indispensable if we think of inherent problems in experimental data. For this to happen, a large progress in computer simulations for direct predictions of materials functions out of the composition and structure information is highly desired, whose successful examples in nanoelectronics researches will be discussed with a short introduction to basic theories behind it.