Yibo Xie
Papers
1
Total Citations
86
H-Index
1
About
Yibo Xie is a rising leader at the intersection of artificial intelligence and catalysis, pioneering the use of large language models and automation to revolutionize catalyst discovery. His most-cited work, “Automation and machine learning augmented by large language models in a catalysis study” (2024, 86 citations), outlines a transformative shift from traditional trial-and-error methods to intelligent, high-throughput digital workflows. By integrating high-throughput information extraction, automated experimentation, and machine learning, Xie’s research accelerates the identification and design of novel catalysts with unprecedented efficiency. His contributions are helping to establish a new paradigm where AI-driven systems can autonomously navigate chemical space, reducing the time and cost of materials development. With a growing citation impact and a forward-looking approach, Xie is shaping the future of digital chemistry—making his work essential reading for students and researchers eager to understand how automation and language models are redefining experimental science.
Research Focus
Key Achievements
Top Papers
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