Speaker

Ryoji Asahi

Department Manager, Sustainable Energy and Environment Dept. 1,

Laboratory Manager, Materials Design Lab., Toyota Central R&D Labs., Inc., Nagakute, Aichi 480-1192, Japan

Abstract

We are confronted with urgent needs for development of various kinds of functional materials with high performance and sufficiently low cost to keep competitiveness in industry and also to tackle inevitable global environmental issues such as sustainable resource and energy supply for society. In practice, it requires lots of trial-and-error experiments for many years to realize just one material substitution in a system.

Therefore, computational prediction based on ab-initio calculations, as it proves to be more efficient and sometimes even more ideal and accurate than experiment, becomes a major component in the development procedure of new materials. We show some examples of the functional materials which have been successfully developed in collaboration with computational materials design. In general, however, to perform the materials design based on ab-initio calculations we are faced with the following two major problems: (i) the conventional materials design requires representative materials that are known in advance for target properties, and (ii) realistic modelling to simulate experiment may often be difficult because of complexity and scale of the system. Here we develop a materials design platform that consists of integration of data mining and simulations. The search space of materials are first selected from database by specifying empirical/theoretical descriptors, and then expanded to new materials deductively. Optimizers for target properties including ab-initio calculations and large-scale molecular dynamics are then used to evaluate the target properties and propose candidates to experimentalists.

Full details can be found on the NSQI website.