Yuting Xu, a PhD student in Associate Professor Fanglin Che’s group in the Department of Chemical Engineering, has published new research in Nature Communications that uses artificial intelligence to speed up the discovery of low-carbon emission ways to produce acetate, a key ingredient in vinegar and an important chemical for making plastics, fabrics, coatings, and medicines.
Instead of using traditional energy-intensive methods based on fossil fuels, Che’s group explored how to produce acetate from carbon monoxide using renewable electricity. By combining advanced computational simulations with AI, they mapped how acetate forms on copper-based catalysts and discovered a simple design rule: The way methylidyne binds to the catalyst surface controls how efficiently acetate is produced from carbon monoxide electroreduction.
Using this rule, the researchers trained AI models to search thousands of possible catalyst combinations and identified new copper alloys that perform better and use energy more efficiently, a promising step toward reducing carbon emissions in chemical manufacturing.
Research collaborators on this publication include two other postdoctoral fellows in Che’s lab, Jiaqi Yang and Yilang Liu, along with Hefei Li, Wanyu Deng, and Ahryeon Lee from Feng Jiao’s group at Washington University in St. Louis.
