Papers
6
Total Citations
441
H-Index
5
About
Yicheng Zhao is a prominent materials scientist specializing in perovskite photovoltaics, with a particular focus on stability engineering, high-throughput experimentation, and machine learning-guided materials discovery. His research has significantly advanced the understanding of how cation engineering influences perovskite solar cell stability, most notably through his landmark 2021 study revealing temperature-induced stability reversals in perovskites — a finding that challenged conventional accelerated ageing methodologies and has since garnered 174 citations. Zhao has been a pioneer in coupling robotic automation with machine learning to accelerate materials optimization; his development of the SPINBOT platform exemplifies this approach, enabling efficient exploration of complex thin-film processing parameter spaces for high-performance solar cells. His investigation of quasi-2D Ruddlesden–Popper perovskites has shed critical light on how intercalating organic cations govern structural stability, contributing foundational knowledge to reduced-dimensional perovskite design. With over 440 citations across his key publications, Zhao's interdisciplinary methodology — merging robotics, data science, and perovskite chemistry — positions him as an influential voice in next-generation solar energy research, offering scalable and intelligent strategies for the rational design of stable, high-efficiency photovoltaic materials.
Research Focus
Key Achievements
Top Papers
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