The 26th Annual Dr. Shih-I Pai Lecture
Where Computational Science Meets Experiment: Self-Driving Laboratories for Materials Discovery
"To face the challenges of the 21st century, modern society requires the rapid discovery of better advanced and structural materials. These, in turn, can help alleviate needs of several sectors that range from health to energy to the environment. Scientific progress is relatively slow in comparison to the timescale of the problems at hand. It is widely recognized that we need to undertake massive immediate action in the timescale of a decade to enable a transition to a sustainable economy and energy systems to avoid catastrophic problems related to climate change. The current COVID19 crisis underscores the much-needed agility to solve problems that relate to molecules and materials in the area of health. Our laboratory's current research aims to accelerate scientific discovery by integrating several disciplines that used to collaborate with each other, but that in our opinion now should merge into a new field of accelerated science. These disciplines include traditional chemistry and materials science, artificial intelligence, data science, analytical and physical chemistry, and robotics. By concentrating on the workflow of scientific discovery and optimization, the concept of a materials acceleration platform or self-driving lab emerges. In this talk, I will describe the components of these platforms and our own efforts to either build them in our laboratory or collaborate with others. I will describe examples in the areas of organic materials and process optimization for the production of pharmaceuticals." - Alán Aspuru-Guzik.
Alán Aspuru-Guzik is a professor of Chemistry and Computer Science at the University of Toronto since July 1st, 2018. He is also the Research Chair of Canada 150 in Theoretical Chemistry and a Canada CIFAR AI Chair at the Vector Institute. Alán began his career at Harvard University in 2006 and was a Full Professor at Harvard University from 2013-2018.
He conducts research in the interfaces of quantum information, chemistry, and machine learning. He was a pioneer in the development of algorithms and experimental implementations of quantum computers and quantum simulators dedicated to chemical systems. He has studied the role of quantum coherence in the transfer of excitonic energy in photosynthetic complexes and has accelerated the discovery by calculating organic semi-conductors, organic photovoltaic energy, organic batteries and organic light-emitting diodes. He has worked on molecular representations and generative models for the automatic learning of molecular properties. Currently, Alán is interested in automation and "autonomous" chemical laboratories.
He is the recipient of the Google Focused Award for Quantum Computing, the Sloan Research Fellowship, the Camille and Henry Dreyfus Teacher-Scholar award and an Early Career Award in Theoretical Chemistry from the American Chemical Society. In 2010 the MIT Technology Review selected Alán as one of the best innovators under the age of 35. He is an elected member of the American Association for the Advancement of Science (AAAS).
Aspuru-Guzik received his B.Sc. from the National Autonomous University of Mexico (UNAM) in 1999 and obtained a Ph.D. from the University of California, Berkeley in 2004.
About the Dr. Shih-I Pai Lecture:
Dr. Shih-I Pai (1913-1996) served on the faculty of the University of Maryland at College Park beginning in 1949 and retired with Emeritus status in 1983. He was the recipient of a Centennial Medal from the A. James Clark School of Engineering and was a founding member of the Institute for Fluid Dynamics and Applied Mathematics (now the Institute for Physical Science and Technology). Dr. Pai authored 14 books and 130 articles in the field of aerodynamics, fluid dynamics and viscous flow, for which he received international recognition. The lecture series honors Dr. Pai's many accomplishments and contributions to UMCP and is supported by donations to the University of Maryland Foundation.