Description:

Data-driven Accelerated Materials Discovery with High-throughput Computing and Statistical Learning

Presented by: Wei Chen

Abstract: Accelerating the discovery of advanced materials is essential for sustainable development and manufacturing innovation. In the talk, I will discuss how the integration of high-throughput computing and modern statistical learning can help uncover the missing piece for accelerated materials design. Overviews of high-throughput projects will be given to illustrate the power of autonomous computing workflows in mapping the tensor properties of inorganic materials. Specifically, I will talk about the development of a comprehensive database of elastic tensors and its contribution to the discovery of a new class of thermoelectric materials. In combination with a newly developed statistical learning framework, the elasticity database has been leveraged to design superhard materials and explore high-entropy alloys. The ability to quantify how microscale parameters affect the macroscale material properties marks an important step towards the ab initio prediction of material design rules. Moving beyond bulk phenomena of materials, the surface property is the new frontier for high-throughput materials research. I will introduce a recent effort in applying high-throughput surface calculations in the discovery of low-band-gap photoelectrocatalytic materials for direct fuel generation from sunlight. Twelve new water oxidation photoelectrocatalysts have been identified from computations and verified by experiments. 

Bio: Wei Chen obtained his BSc in Materials Science and Engineering from Shanghai Jiao Tong University and PhD in Materials from Northwestern University with Prof. Chris Wolverton. He was a postdoctoral fellow at Lawrence Berkeley National Laboratory working with Dr. Kristin Persson between 2012 and 2015. At LBNL, he was the primary contributor to the Materials Project, spearheading the development of major computational databases in elastic, piezoelectric, dielectric and transport properties of materials. He joined Illinois Institute of Technology in 2015 as an Assistant Professor in the Department of Mechanical, Materials and Aerospace Engineering. His work focuses on the integration of theory, computation and statistical learning to accelerate materials discovery and design.