Professor Mohamad Moosavi (ChemE) is harnessing the power of AI to accelerate the discovery of new materials to combat climate change. New funding from the Joint EMHSeed and XSeed Funding Program will help him expand his research on the application of novel metal-organic frameworks (MOFs) in carbon capture and storage — specifically, identifying and developing materials that are most effective at absorbing CO2 within their chemical structure and separating it from molecules of other gases, such as those that flow through exhaust pipes and the smokestacks of industrial facilities.
MOFs are attractive because of their high chemical tunability. By adjusting the chemical composition, scientists can optimize the material’s ability to select for one molecule or another — but the number of potential combinations is breathtaking.
Since the first MOFs were synthesized in the early 2000s, the number of reported structures has surpassed 100,000, presenting a significant challenge in selecting the most suitable options for specific applications.
To address this challenge, Moosavi is incorporating the use of AI, including large language models, to compile and analyze vast amounts of MOF data into a database. He hopes that these tools will accelerate the discovery and design of MOFs for various applications, including carbon capture, conversion and storage.