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Delocalized, asynchronous, closed-loop discovery of organic laser emitters
Felix Strieth-Kalthoff1,2, Han Hao1,2,3, Vandana Rathore4,5
1Department of Chemistry, University of Toronto, Toronto, ON, Canada.
Science (New York, N.Y.)
|May 16, 2024
Summary
This study introduces a cloud-based AI system for distributed, asynchronous materials discovery. It successfully identified 21 new molecular gain materials for organic lasers, accelerating scientific workflows.
Area of Science:
- Materials Science
- Molecular Optoelectronics
- Organic Electronics
Background:
- Materials discovery involves complex, multi-location workflows.
- Current methods are often slow and geographically constrained.
- Specialized expertise and instrumentation are frequently required.
Purpose of the Study:
- To develop a cloud-based strategy for accelerating materials discovery.
- To enable delocalized and asynchronous design-make-test-analyze cycles.
- To explore molecular gain materials for organic solid-state lasers.
Main Methods:
- Implemented a cloud-based artificial intelligence experiment planner.
- Utilized distributed robotic synthesis and in-line property characterization.
- Integrated five international laboratories for asynchronous workflows.
Main Results:
- Discovered 21 new state-of-the-art molecular gain materials.
- Achieved gram-scale synthesis of promising candidates.
- Verified best-in-class stimulated emission in thin-film devices.
Conclusions:
- The cloud-based strategy successfully accelerates materials discovery.
- This approach democratizes scientific research by enabling global collaboration.
- The developed workflow serves as a blueprint for future distributed scientific endeavors.
