A Materials Acceleration Platform for Organic Laser Discovery
Abstract
Conventional materials discovery is a laborious and time‐consuming process that can take decades from initial conception of the material to commercialization. Recent developments in materials acceleration platforms promise to accelerate materials discovery using automation of experiments coupled with machine learning. However, most of the automation efforts in chemistry focus on synthesis and compound identification, with integrated target property characterization receiving less attention. In this work, an automated platform is introduced for the discovery of molecules as gain mediums for organic semiconductor lasers, a problem that has been challenging for conventional approaches. This platform encompasses automated lego‐like synthesis, product identification, and optical characterization that can be executed in a fully integrated end‐to‐end fashion. Using this workflow to screen organic laser candidates, discovered eight potential candidates for organic lasers is discovered. The lasing threshold of four molecules in thin‐film devices and find two molecules with state‐of‐the‐art performance is tested. These promising results show the potential of automated synthesis and screening for accelerated materials development.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Dec 14, 2022
- Source ID
- 10.1002/adma.202207070
Entities
People
- Alán Aspuru‐guzik
- Andrés Aguilar‐granda
- Chihaya Adachi
- Cyrille Lavigne
- Fatima Bencheikh
- Han Hao
- Jason E Hein
- Jenya Vestfrid
- Kazuhiro Hotta
- Martin D. Burke
- Martin Seifrid
- Nicholas Angello
- Robert Pollice
- Sahar Alasvand Yazdani
- Tony C. Wu
Organizations
- Canada Foundation for Innovation
- Defense Advanced Research Projects Agency
- Kyushu University
- University of British Columbia
- University of Illinois Urbana–Champaign
- University of Toronto