Papers
3
Total Citations
105
H-Index
3
About
Zhenni Wu is a rising star in the field of advanced materials and photovoltaics, with a research focus on the automation and optimization of perovskite solar cells. Her work uniquely combines machine learning, robotics, and materials science to accelerate the discovery and engineering of high-performance thin films. Wu’s most notable contribution is the development of SPINBOT, a fully automated, machine-learning-guided robotic platform that efficiently navigates complex, multi-dimensional parameter spaces to optimize solution-processed perovskite thin films. This breakthrough, published in a 2023 paper that has already garnered 76 citations, dramatically speeds up the traditionally slow, trial-and-error process of materials optimization. In a related study, she used a robot-based platform to systematically investigate the crystallization and thermal stability of quasi-2D perovskites, synthesizing 28 different compositions to reveal key phase evolution mechanisms. By integrating high-throughput experimentation with intelligent data-driven guidance, Wu is pioneering a new paradigm for materials research. Her work not only pushes the boundaries of perovskite solar cell performance but also establishes a powerful, generalizable framework for autonomous materials discovery, marking her as a key innovator in the next generation of energy materials engineering.
Research Focus
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