Zhengzhou University, China
Zhen Zhou completed his B.S. degree in Applied Chemistry in 1994, followed by his Ph.D. in Inorganic Chemistry in 1999, both from Nankai University, China. He commenced his academic career at Nankai University as a lecturer in 1999. After two years, he embarked on a postdoctoral fellowship at Nagoya University, Japan. In 2005, he returned to Nankai University, assuming the role of associate professor, and later attained the position of full professor in 2011. In 2021, he transitioned to Zhengzhou University, China, where he holds the position of Distinguished Professor and currently serves as the Dean of the School of Chemical Engineering. His primary research focus on the integration of high-throughput computations, experiments, and machine learning for energy storage and conversion. He serves as an Associate Editor for Journal of Materials Chemistry A, Green Energy & Enviroment and Journal of Power Sources.
As energy crisis and environmental issue become increasingly serious, energy conversion and storage has been receiving extensive attention. Previously we investigated and designed new energy materials via high-performance computations;1 however, instead of the design for a single material, high-throughput screening based on databases is a more efficient approach to achieve more excellent candidates. Among various photocatalysts, two-dimensional (2D) layered materials exhibit native advantages in photocatalytic reactions, such as high surface-volume ratio and short diffusion distance for photo-generated electrons and holes. Also, Na-containing layered materials have attracted extensive attention since the layered structure ensures the reversible intercalation/de-intercalation of Na+ without serious lattice changes, leading to good cyclic stability and excellent ionic conductivity. In this talk, I would introduce a screening algorithm2 to search promising layered materials for photohydrolytic catalysts,3 hydrogen evolution reaction electrocatalysts4 and Na ion batteries.5
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