Perovskite materials would be superior to silicon in PV cells, but manufacturing such cells at scale is a huge hurdle. Machine learning can help.
SMART breakthrough could help develop technologies that can identify materials according to desired properties for specific applications.
Read more about research performed by Prof. Buonassisi's team on LinkedIn
UNIVERSITY OF NOTRE DAME
B.S., Applied PhysicsUNIVERSITY OF CALIFORNIA-BERKELEY
Ph.D., Applied Science & Technology"Tonio Buonassisi is a Professor of Mechanical Engineering at the Massachusetts Institute of Technology (MIT). He is pioneering the application of artificial intelligence to develop new materials for societally beneficial applications. His research in solar photovoltaics and technoeconomic analysis assisted technology developments in dozens of companies, earning him a US Presidential Early Career Award for Scientists and Engineers (PECASE), a National Science Foundation CAREER Award, and a Google Faculty Award. He directs the ADDEPT Center, a DOE-funded national center devoted to making semi-transparent perovskite solar cells *durable* for terrestrial tandems. He is PI of the Accelerated Materials Lab for Sustainability (AMLS) at MIT, and served as founding director for the Accelerated Materials Development for Manufacturing Programme in Singapore. A recipient of the MIT Everett Moore Baker Memorial Award for Excellence in Undergraduate Teaching, his passion for education is evidenced by the ~1M views of his OpenCourseware/YouTube PV lectures series.
Materials Research Society, Institute of Electrical and Electronics Engineers, American Association for the Advancement of Science