A Materials Acceleration Platform for Organic Laser Discovery

Tony C. Wu*, Andrés Aguilar-Granda, Kazuhiro Hotta, Sahar Alasvand Yazdani, Robert Pollice, Jenya Vestfrid, Han Hao, Cyrille Lavigne, Martin Seifrid, Nicholas Angello, Fatima Bencheikh, Jason E. Hein, Martin Burke, Chihaya Adachi, Alán Aspuru-Guzik*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

15 Citations (Scopus)

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.

Original languageEnglish
Article number2207070
Number of pages9
JournalAdvanced materials
Volume35
Issue number6
DOIs
Publication statusPublished - 9-Feb-2023
Externally publishedYes

Keywords

  • accelerated materials discovery
  • automated synthesis and analysis
  • autonomous laboratory
  • organic laser

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