nce and Modelling
Mapping the Materials Chain through data science
Krishna Rajan, Department of Materials Design and Innovation, University at Buffalo, Buffalo, USA
This presentation discusses how Material Informatics can transform the existing paradigm of accelerated materials discovery and multiscale design , namely from one that involves the generation of, and searching among, massive data libraries via high throughput computation and/or experiments, to one of targeted materials discovery based on discovering the best pathways for that and for future discoveries. It is shown that these pathways help to bridge the gap between fundamental materials properties and structure and materials performance. This presentation will focus on data science methods that include the analysis of the structure of high dimensional data through the tools of manifold learning and topological data analysis.