In a novel approach that could help reduce carbon emissions, a team of scientists led by Stony Brook's Anatoly Frenkel have described a way to use artificial intelligence (AI) to facilitate the conversion of carbon dioxide (CO2) into methane. By using this method to track the size, structure, and chemistry of catalytic particles under real reaction conditions, the scientists can identify which properties correspond to the best catalytic performance, and then use that information to guide the design of more efficient catalysts. "Improving our ability to convert CO2 to methane would'kill two birds with one stone' by making a sustainable non-fossil-fuel energy source that can be easily stored and transported while reducing carbon emissions," said Anatoly Frenkel, a chemist with a joint appointment at the U.S. Department of Energy's Brookhaven National Laboratory (BNL) and Stony Brook University. Frenkel is a professor of Materials Science in the College of Engineering and Applied Sciences. Frenkel's group has been developing a machine-learning approach to extract catalytic properties from x-ray signatures of catalysts collected as chemicals are transformed in reactions.

I. Memming Park, Stony Brook's 2019 Discovery Prize winner, built his first artificial neural network when he was in middle school. That long-held interest in how the brain works influenced his award-winning research titled, "Personalized Landscape of Unconsciousness." Park, an Assistant Professor in the Department of Neurobiology & Behavior and a faculty member of the Institute for AI-Driven Discovery and Innovation, says his research, to understand the brains of coma patients using machine learning methods and neurotechnologies, stems from a spontaneous discussion with Dr. Charles Mikell, Stony Brook Medicine faculty. Mikell was already recording signals, with his own data analysis software, from human brains during surgeries he performed. "We were interested in these brain implants for seizure treatments," said Park.