Self-Driving Chemistry Laboratories: Chemical Discoveries Powered by Robotics

Analytical/Physical Chemistry, Applied Physics, Materials Science

This stream will leverage robotics and machine learning to explore the properties of next-generation materials for clean energy technologies, such as solar cells, light emitters, and energy storage devices. Organic and hybrid semiconductors, which are created from a precursor ink solution, have the potential to revolutionize the semiconductor industry due to their low-cost fabrication, chemical tunability, and compatibility with mechanically flexible devices. However, challenges remain because of the extensive range of parameters in materials design and processing. Students in this program will develop high-throughput methods for fabricating these materials and use machine learning to optimize their properties.

Stream Leaders

Connor Bishack, Ph.D.
Assistant Professor, Department of Chemistry