Strieth-Kalthoff Felix, Hao Han, Rathore Vandana, Derasp Joshua, Gaudin Théophile, Angello Nicholas H, Seifrid Martin, Trushina Ekaterina, Guy Mason, Liu Junliang, Tang Xun, Mamada Masashi, Wang Wesley, Tsagaantsooj Tuul, Lavigne Cyrille, Pollice Robert, Wu Tony C, Hotta Kazuhiro, Bodo Leticia, Li Shangyu, Haddadnia Mohammad, Wołos Agnieszka, Roszak Rafał, Ser Cher Tian, Bozal-Ginesta Carlota, Hickman Riley J, Vestfrid Jenya, Aguilar-Granda Andrés, Klimareva Elena L, Sigerson Ralph C, Hou Wenduan, Gahler Daniel, Lach Slawomir, Warzybok Adrian, Borodin Oleg, Rohrbach Simon, Sanchez-Lengeling Benjamin, Adachi Chihaya, Grzybowski Bartosz A, Cronin Leroy, Hein Jason E, Burke Martin D, Aspuru-Guzik Alán
Department of Chemistry, University of Toronto, Toronto, ON, Canada.
Department of Computer Science, University of Toronto, Toronto, ON, Canada.
Science. 2024 May 17;384(6697):eadk9227. doi: 10.1126/science.adk9227.
Contemporary materials discovery requires intricate sequences of synthesis, formulation, and characterization that often span multiple locations with specialized expertise or instrumentation. To accelerate these workflows, we present a cloud-based strategy that enabled delocalized and asynchronous design-make-test-analyze cycles. We showcased this approach through the exploration of molecular gain materials for organic solid-state lasers as a frontier application in molecular optoelectronics. Distributed robotic synthesis and in-line property characterization, orchestrated by a cloud-based artificial intelligence experiment planner, resulted in the discovery of 21 new state-of-the-art materials. Gram-scale synthesis ultimately allowed for the verification of best-in-class stimulated emission in a thin-film device. Demonstrating the asynchronous integration of five laboratories across the globe, this workflow provides a blueprint for delocalizing-and democratizing-scientific discovery.
当代材料发现需要复杂的合成、配方和表征序列，这些序列通常跨越多个拥有专业知识或仪器的地点。为了加速这些工作流程，我们提出了一种基于云的策略，该策略能够实现分散式和异步的设计-制造-测试-分析循环。我们通过探索用于有机固态激光器的分子增益材料作为分子光电子学的前沿应用来展示这种方法。由基于云的人工智能实验规划器精心安排的分布式机器人合成和在线性能表征，导致发现了21种新的先进材料。克级合成最终使得在薄膜器件中验证一流的受激发射成为可能。该工作流程展示了全球五个实验室的异步整合，为科学发现的本地化和民主化提供了蓝图。
