Speakers:
Dr. Nobuyuki N. Matsuzawa
Engineering Division, Industrial Solutions Company Panasonic Corporation

Abstract:
In addition to the boosting CPU power owing to the progresses of semiconductor technology, recent expansion of the cloud computing environment is inducing a huge impact on materials design based on computational chemistry by drastically increasing the number of candidate molecules that can be calculated within a reasonable timeframe. Furthermore, rapid progresses in the area of materials informatics (MI) are accelerating the speed of performing prediction of material properties; now a prediction can be made within milliseconds by MI, as compared to hours or even days by the conventional computational methods. These progresses have enabled performing massive screening of millions of materials that might show desired properties. Results of the progresses of recent AI-related technologies are further being introduced to the area of materials development in a form of various proposals to realize the inverse materials design. In this talk, results of our trials to introduce such progresses to the materials design in electronic industry will be presented for the case of the design of organic carrier transport materials such as heteroacenes. Results of quarter million screen of such materials by using the cloud computing environment will be discussed in combination with the results of benchmark studies of various methods of inverse materials design such as deep reinforcement learning.