MSE Seminar: “Navigating the Promises of Compositionally Complex Energy Materials with Data-driven Approaches”

Details

Abstract

Compositionally complex materials, represented by high-entropy alloys and ceramics, have primarily been used as structural materials since their initial discovery. Recently, interest in their potential for energy storage and conversion has surged. However, this excitement is often accompanied by confusion as researchers grapple with the need to complicate material composition beyond vague concepts like the “cocktail effect.”

This talk aims to clarify some fundamental pictures of compositionally complex energy materials (CCEM), illustrated through case studies on high-entropy battery materials and electrocatalysis. Inspired by the ongoing revolution of AI in science, this talk will also showcase our recent efforts in developing universally adaptable machine learning models for CCEMs. Our findings suggest that, in many cases, machine learning challenges in CCEM stem more from data limitations rather than the need for sophisticated neural network architectures. A well-designed dataset, enriched with the right domain knowledge, can deliver powerful insights even with simple models.

Bio

Bin Ouyang, Ph.D.

Assistant Professor
Florida State University

Dr. Bin Ouyang is a computational materials scientist specializing in the study of disordered and compositionally complex materials using high-throughput screening, data mining, and machine learning. He earned his Ph.D. in Materials Engineering from McGill University. After that, he worked as a postdoc at UIUC and UC Berkeley.

Dr. Ouyang started his college life as a metallurgical physicist and gradually evolved into a solid-state chemist. Currently, he is an assistant professor in the Department of Chemistry and Biochemistry at Florida State University, where his research group focuses on developing data-driven tools to investigate materials for energy storage and conversion, particularly those exhibiting complex compositional and structural disorder. He has published over 80 papers across diverse fields, including batteries, fuel cells, metal alloys, and low-dimensional nanomaterials. More information can be found at https://bin-ouyang.com/.