Informatics for ab-initio Computational data in Materials Science

Presenter: Nobuto Oka

Author:Krishna Rajan
Department of Materials Science and Engineering &
NSF International Materials Institute: Combinatorial Sciences and Materials Informatics Collaboratory (CoSMIC-IMI)
Iowa State University, Ames , IA 50011, USA

In this presentation we discuss how informatics techniques of data dimensionality reduction and prediction using statistical learning can be used to identify critical correlations in the parameters used in ab-initio calculations. From such correlations of multivariate data, it is shown that one can identify clear dominant parameters influencing phase stability calculations. It is demonstrated that it is possible to make a quantitative assessment of the relative impact of different parameters on the final results of the calculations. The use of such informatics techniques to accelerate the computational approaches for first principle calculations is also discussed.