Alán Aspuru-Guzik,
Professor of Chemistry and Computer Science
Director, Acceleration Consortium
University of Toronto

In this talk, Alan argues that for materials discovery, one needs to go beyond simple computational screening approaches followed by traditional experimentation. Alan has been working on the design and implementation of “materials acceleration platforms” (MAPs). MAPs are enabled by the confluence of three disparate fields, namely artificial intelligence (AI), high-throughput quantum chemistry (HTQC), and robotics. The integration of prediction, synthesis and characterization in an AI-driven closed-loop approach promises the acceleration of materials discovery by a factor of 10, or even a 100. Alan describes his efforts under the Mission Innovation umbrella platform around this topic.