Title: The Electrolyte Molecular Universe: AI‑Empowered Discovery of Battery Materials

Speaker: Prof. Kang Xu (The Ohio State University)

Invited by: Professor Liang Zhenxing

Time: August 22, 2026 (Saturday), 15:00‑16:00

Venue: Room 902, Building B13, University Town Campus

Organizer: School of Chemistry and Chemical Engineering / Guangdong Provincial Key Laboratory of Fuel Cell Technology

Biography:

  Dr. Kang Xu is an MRS Fellow (Fellow of the Materials Research Society) and an ECS Fellow (Fellow of The Electrochemical Society). He currently serves as the Chair Professor in the Department of Mechanical and Aerospace Engineering at The Ohio State University and an Ohio Distinguished Scholar. He previously held the position of Chief Technology Officer at SES AI Corp. With nearly 40 years of dedicated research, his work centers on electrolyte chemistry as well as electrode‑interface and interphase chemistry. He has authored more than 350 academic publications, contributed 5 monographs and book chapters, and holds over 20 US patents. His publications have accumulated more than 90 000 total citations with an H‑index of 143. He has been continuously listed as a Clarivate Highly Cited Scientist since 2018 and featured in Stanford University’s Top 2 % Scientists Worldwide. His two review articles published in Chemical Reviews in 2004 and 2014, together with his 2023 monograph Electrolytes, Interfaces and Interphases, have become key references in the field of battery electrolytes. In recent years, he has devoted himself to AI‑empowered materials discovery. He leads the development of Molecular Universe, the world’s first end‑to‑end AI platform for battery materials. Integrating large‑scale molecular databases, machine‑learning algorithms and first‑principles calculations, this platform enables intelligent design and rapid screening of battery electrolytes and functional molecules, advancing the paradigm shift of battery‑materials R&D from traditional trial‑and‑error to AI‑driven innovation.

Abstract:

  Electrolytes represent one of the most distinctive components in electrochemical energy‑storage devices, maintaining direct interfacial contact with nearly all constituent materials within such systems. The chemical and electrochemical behaviours at these interfaces not only govern ion transport and electron‑transfer processes, but also determine whether devices can operate stably following the intended working mechanisms. For decades, R&D of electrolyte materials has largely relied on experience‑driven trial‑and‑error exploration, whose efficiency is constrained by both experimental costs and the vast molecular search space. Driven by the rapid advancement of artificial intelligence, materials discovery is undergoing a transition from experience‑oriented practice toward a new paradigm of data‑driven intelligent design. This presentation highlights state‑of‑the‑art advances in AI for Materials. Taking Molecular Universe as a showcase, it demonstrates how the world’s first large‑scale AI platform targeting the organic‑molecule chemical space accelerates the discovery and optimization of novel battery electrolytes and related functional materials by mapping the molecular universe and establishing structure‑property correlations.

Announced by School of Chemistry and Chemical Engineering