De‐Liang Long
Papers
12
Total Citations
1,122
H-Index
8
About
De-Liang Long is a pioneering chemist at the forefront of autonomous chemical discovery, combining robotics, machine learning, and inorganic chemistry to revolutionize how new molecules and materials are found. His research focuses primarily on polyoxometalates (POMs) — complex metal-oxide clusters with remarkable structural diversity — and the application of intelligent robotic systems to navigate vast, otherwise intractable chemical spaces. Long's most celebrated contribution, a 2018 paper on controlling an organic synthesis robot with machine learning to search for new reactivity, has garnered over 770 citations, establishing him as a key figure in the emerging field of self-driving laboratories. His influential work comparing human versus robotic discovery of gigantic polyoxometalates demonstrated that automated workflows could match or surpass human researchers in efficiency and reproducibility. Subsequent publications introduced fully autonomous chemical robots capable of exploring billions of reaction combinations without prior knowledge, uncovering hidden rules of inorganic coordination chemistry from scratch. More recently, Long has extended these approaches to metal-organic frameworks and even hybrid peptide-metal oxide systems, demonstrating remarkable breadth. His body of work represents a transformative shift toward algorithm-driven, robot-assisted science that is reshaping the pace and scope of chemical discovery.
Research Focus
Key Achievements
Top Papers
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- 6Robotic synthesis of peptides containing metal-oxide-based amino acids26 citations · 2022
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