Accelerating Discovery with AI: Self-Driving Laboratories

In the physical sciences, the pace of research has slowed, and in some cases plateaued, leading to more incremental breakthroughs rather than revolutionary discoveries. How can we overcome limitations in the lab that make it harder and harder to find new phenomena each year?

Artificial intelligence and robotics are transforming society at large, and these groundbreaking tools will also accelerate chemistry research to new heights. Join Alán Aspuru-Guzik, Professor of Chemistry and Computer Science at the University of Toronto as he discusses the rapidly growing field of self-driving laboratories. From automated chemical synthesis and characterization platforms to AI-aided experiment planning and optimization systems, register now to learn how these emerging technologies promise to reduce the time for discovery in chemistry and materials science.

This ACS Webinar is moderated by Angela K. Wilson, Associate Dean for Strategic Initiatives, College of Natural Sciences and John A. Hannah Distinguished Professor of Chemistry at Michigan State University. The webinar is organized by Young-Shin Jun, Washington University in St. Louis and the Chair of Science & Technology Subcommittee of the ACS Committee on Science, and is co-produced with the ACS Committee on Science.

What You Will Learn

• What are the components of a self-driving lab and how does it promise to accelerate research
• Recent applications of self-driving laboratories, specifically for the discovery of organic electrolytes and organic light-emitting diodes
• Current trends and directions in artificial intelligence and robotics that could accelerate the field of self-driving laboratories

Meet The Experts

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

Angela K. Wilson, Associate Dean for Strategic Initiatives, College of Natural Sciences and John A. Hannah Distinguished Professor of Chemistry, Michigan State University