Advanced Materials and Nanotechnology

Biography

Biography: Kai-Ming Ho

Abstract

Material informatics is a new initiative which has attracted a lot of attention in recent scientific research. The basic strategy is to construct comprehensive data sets and use machine learning to solve a wide variety of problems in material design and discovery. In pursuit of this goal, a key element is the quality and completeness of the databases used. Recent advance in the development of crystal structure prediction algorithms has made it a complementary and more efficient approach to explore the structure/phase space in materials using computers. In this talk, we discuss the importance of the structural motifs and motif-networks in crystal structure predictions. Correspondingly, powerful methods are developed to improve the sampling of the low-energy structure landscape. Applications to the Li/Na-ion battery cathode materials, in particular A_nFeSiO₄ (n=1 and 2; A = Li and Na) [1-5] and LiFePO₄ [6-7], will be presented.