Researchers seek to revolutionize catalyst design with machine learning Penn State University

Researchers from Penn State and Carnegie Mellon University (CMU) have received a $1.2 million grant from the United States Department of Energy (DOE) to use machine learning -- a form of artificial intelligence -- and data science to design more effective catalysts for chemical processing. The grant is part of a new initiative by the DOE to provide $27.6 million in grants for data science research in chemical and materials sciences. A catalyst is a stable chemical substance that, when added to a chemical reaction, increases the rate of reaction without becoming part of the reaction. "It is important to recognize how widespread the use of catalysts is," said Michael Janik, Penn State professor of chemical engineering and principal investigator for the study. "About 90% of chemical products people are using every day, like gasoline and fine chemicals that are in shampoo, are going through some sort of catalytic process before they're used."