Computational Approaches to Material Design
Comp. Mater. Lab. @ Westlake University
About Us
Our research group focuses on computational materials science, aiming to understand, discover, design, and modify novel inorganic solid materials through computation. By combining artificial intelligence algorithms with various materials computation methods, we can establish an in-depth fundamental understanding of the core structure-property relationships in materials science from the microscopic atomic scale, and discover and design new materials that meet practical application requirements through high-throughput computation and data mining.
Research
Solid-state Battery Materials
Understanding and designing novel materials for next-generation batteries through computational approaches and AI-driven discovery.
Strategic Solid-state Synthesis
Exploring reaction pathways and mechanisms in materials synthesis using advanced computational methods.
AI for Materials Discovery
Developing and applying machine learning models for accelerated materials discovery and property prediction.
Our Team
Yizhou Zhu
Assistant Professor
School of Engineering, Westlake University
Yizhou Zhu obtained her B.S. degree in Physics (2011) and M.S. degree in Nuclear Technology (2014) both from Peking University. She earned her Ph.D. degree in Materials Science and Engineering at the University of Maryland, College Park in 2018. She worked as a postdoctoral research associate at Northwestern University from 2018 to 2021. Zhu joined the Westlake University as a tenure-track Assistant Professor since September 2021.
Her research works on solid electrolytes have been published in renowned journals such as Nature, Sci. Adv., Adv. Mater., Adv. Energy Mater., Angew. Chem. Int. Ed., Joule, J. Mater. Chem. A, etc.