Scientists have uncovered thousands of previously overlooked chemical reactions that could help improve the conversion of carbon dioxide (CO2) into valuable fuels and industrial chemicals. By combining machine learning with advanced computer simulations, researchers at the Indian Institute of Science (IISc) identified 9,389 individual reactions occurring on a copper catalyst, revealing unexpected chemical pathways that conventional models had missed. The findings, published in Nature Communications, could help scientists develop more effective catalysts for transforming CO2 into useful products such as methanol.
The research also uncovered a surprising way hydrogen can participate in these reactions, challenging established assumptions about how the process works. One promising approach to recycling carbon dioxide is hydrogenation, which uses a catalyst to help CO2 react with hydrogen and form chemicals such as methanol. However, the process involves an enormous number of individual reactions taking place across the catalyst's surface.
Simulating every possible step using quantum mechanics would require immense computing power, so researchers typically focus on a limited selection of reactions believed to be the most important. This simplification can leave hundreds of potentially critical reactions out of the picture. "We began with a worry familiar to anyone who does mechanistic modeling: How do you know that your reaction network has not omitted the one step that matters?" says first author Anand Mohan Verma, who conducted the research as a CV Raman Postdoctoral Fellow at IISc and is now an Assistant Professor at the Motilal Nehru National Institute of Technology Allahabad (MNNIT Allahabad).
AI Reveals Thousands of Overlooked Chemical Reactions To overcome this limitation, the research team began by using quantum mechanics simulations to build a detailed database containing 152 chemical reactions. They then trained machine learning models to quickly estimate the energy barriers that additional reactions would need to overcome. Using automated computational tools, the scientists examined the possible reactions involving 105 chemical species present on the catalyst surface.
They also determined which transformations could take place in a single reaction step. This approach expanded their original network from just 152 reactions to 9,389. The difference was significant.
When the researchers relied on the smaller network, their model incorrectly identified formic acid as the main product rather than methanol. It also predicted substantially less CO2 conversion than experiments indicated. "When we modeled the process using the 152 reactions considered initially, the network wrongly predicted formic acid, not methanol, as the major product, and underestimated how much CO2 gets converted.
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