Abstract
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.
Original language | English (US) |
---|---|
Article number | eadk9227 |
Journal | Science |
Volume | 384 |
Issue number | 6697 |
DOIs | |
State | Published - May 17 2024 |
ASJC Scopus subject areas
- General
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In: Science, Vol. 384, No. 6697, eadk9227, 17.05.2024.
Research output: Contribution to journal › Article › peer-review
}
TY - JOUR
T1 - Delocalized, asynchronous, closed-loop discovery of organic laser emitters
AU - Strieth-Kalthoff, Felix
AU - Hao, Han
AU - Rathore, Vandana
AU - Derasp, Joshua
AU - Gaudin, Théophile
AU - Angello, Nicholas H.
AU - Seifrid, Martin
AU - Trushina, Ekaterina
AU - Guy, Mason
AU - Liu, Junliang
AU - Tang, Xun
AU - Mamada, Masashi
AU - Wang, Wesley
AU - Tsagaantsooj, Tuul
AU - Lavigne, Cyrille
AU - Pollice, Robert
AU - Wu, Tony C.
AU - Hotta, Kazuhiro
AU - Bodo, Leticia
AU - Li, Shangyu
AU - Haddadnia, Mohammad
AU - Wołos, Agnieszka
AU - Roszak, Rafał
AU - Ser, Cher Tian
AU - Bozal-Ginesta, Carlota
AU - Hickman, Riley J.
AU - Vestfrid, Jenya
AU - Aguilar-Granda, Andrés
AU - Klimareva, Elena L.
AU - Sigerson, Ralph C.
AU - Hou, Wenduan
AU - Gahler, Daniel
AU - Lach, Slawomir
AU - Warzybok, Adrian
AU - Borodin, Oleg
AU - Rohrbach, Simon
AU - Sanchez-Lengeling, Benjamin
AU - Adachi, Chihaya
AU - Grzybowski, Bartosz A.
AU - Cronin, Leroy
AU - Hein, Jason E.
AU - Burke, Martin D.
AU - Aspuru-Guzik, Alán
N1 - The authors acknowledge the Defense Advanced Research Projects Agency (DARPA) under the Accelerated Molecular Discovery Program under cooperative agreement no. HR00111920027, dated 1 August 2019. The content of the information presented in this work does not necessarily reflect the position or the policy of the government. This research was undertaken thanks in part to funding provided to the University of Toronto\u2019s Acceleration Consortium from the Canada First Research Excellence Fund CFREF-2022-00042. F.S.-K. is a postdoctoral fellow in the Eric and Wendy Schmidt AI in Science Postdoctoral Fellowship Program, a program by Schmidt Futures. R.P. acknowledges funding through a Postdoc.Mobility fellowship by the Swiss National Science Foundation (SNSF; project no. 191127). C.B.-G. acknowledges funding from a Marie Sklodowska Curie Actions Postdoctoral Fellowship grant (101064374). C.A. thanks the Japan Science and Technology Agency (JST) CREST (grant no. JPMJCR22B3) Specially Promoted Research (grant no. 23H05406). L.C. and the Glasgow team thank EPSRC (grant nos. EP/L023652/1, EP/R01308X/1, EP/S019472/1, and EP/ P00153X/1) and the ERC (project 670467 SMART-POM). L.C. thanks Schmidt Futures for an Innovation Fellowship. B.A.G. was supported by the Institute for Basic Science, Korea (project code IBS-R020-D1). M.D.B. acknowledges funding from the Molecule Maker Lab Institute, an AI Institutes program supported by the US National Science Foundation under grant no. 2019897. A.A.-Gu. thanks A. G. Fr\u00F8seth for his generous support. A.A.-Gu. also acknowledges the generous support of Natural Resources Canada and the Canada 150 Research Chairs program. Computations were performed on the Niagara supercomputer (SciNet HPC consortium; Canada Foundation for Innovation; Government of Ontario; Ontario Research Fund \u2013 Research Excellence; University of Toronto), the Cedar supercomputer (WestGrid consortium; Digital Research Alliance of Canada), and the Beluga and Narval supercomputers (\u00C9cole de technologie sup\u00E9rieure, Calcul Qu\u00E9bec; Digital Research Alliance of Canada; Canada Foundation for Innovation; Minist\u00E8re de l\u2019\u00C9conomie, des Sciences et de l\u2019innovation du Qu\u00E9bec; Fonds de recherche du Qu\u00E9bec \u2013 Nature et technologies). The authors thank A. Fischer for conceiving the DARPA Accelerated Molecular Discovery Program and for numerous fruitful discussions. R. Keunen (University of Toronto) is acknowledged for experimental and administrative assistance. Funding: The authors acknowledge the Defense Advanced Research Projects Agency (DARPA) under the Accelerated Molecular Discovery Program under cooperative agreement no. HR00111920027, dated 1 August 2019. The content of the information presented in this work does not necessarily reflect the position or the policy of the government. This research was undertaken thanks in part to funding provided to the University of Toronto\u2019s Acceleration Consortium from the Canada First Research Excellence Fund CFREF-2022-00042. F.S.-K. is a postdoctoral fellow in the Eric and Wendy Schmidt AI in Science Postdoctoral Fellowship Program, a program by Schmidt Futures. R.P. acknowledges funding through a Postdoc.Mobility fellowship by the Swiss National Science Foundation (SNSF; project no. 191127). C.B.-G. acknowledges funding from a Marie Sklodowska Curie Actions Postdoctoral Fellowship grant (101064374). C.A. thanks the Japan Science and Technology Agency (JST) CREST (grant no. JPMJCR22B3) Specially Promoted Research (grant no. 23H05406). L.C. and the Glasgow team thank EPSRC (grant nos. EP/L023652/1, EP/R01308X/1, EP/S019472/1, and EP/ P00153X/1) and the ERC (project 670467 SMART-POM). L.C. thanks Schmidt Futures for an Innovation Fellowship. B.A.G. was supported by the Institute for Basic Science, Korea (project code IBS-R020-D1). M.D.B. acknowledges funding from the Molecule Maker Lab Institute, an AI Institutes program supported by the US National Science Foundation under grant no. 2019897. A.A.-Gu. thanks A. G. Fr\u00F8seth for his generous support. A.A.-Gu. also acknowledges the generous support of Natural Resources Canada and the Canada 150 Research Chairs program. Computations were performed on the Niagara supercomputer (SciNet HPC consortium; Canada Foundation for Innovation; Government of Ontario; Ontario Research Fund \u2013 Research Excellence; University of Toronto), the Cedar supercomputer (WestGrid consortium; Digital Research Alliance of Canada), and the Beluga and Narval supercomputers (\u00C9cole de technologie sup\u00E9rieure, Calcul Qu\u00E9bec; Digital Research Alliance of Canada; Canada Foundation for Innovation; Minist\u00E8re de l\u2019\u00C9conomie, des Sciences et de l\u2019innovation du Qu\u00E9bec; Fonds de recherche du Qu\u00E9bec \u2013 Nature et technologies). Author contributions: F.S.-K. and H.H. contributed equally to this work, and the order of authorship was determined through a coin flip. Conceptualization: F.S.-K., H.H., V.R., J.D., T.G., N.H.A., M.S., R.P., T.C.W., C.A., B.A.G., L.C., J.E.H., M.D.B., and A.A.-Gu. Data curation: F.S.-K., H.H., V.R., J.D., N.H.A., M.S., E.T., M.G., J.L., X.T., M.M., W.W., T.T., L.B., A.Wo., R.R., C.T.S., L.C., and J.E.H. Formal analysis: F.S.-K., H.H., V.R., J.D., N.H.A., M.S., E.T., M.G., J.L., X.T., M.M., T.T., A.Wo., R.R., and C.T.S. Funding acquisition: C.A., B.A.G., L.C., J.E.H., M.D.B., and A.A.-Gu. Investigation: F.S.-K., H.H., V.R., J.D., T.G., N.H.A., M.S., E.T., M.G., J.L., X.T., M.M., W.W., T.T., L.B., S.Li, A.Wo., R.R., C.T.S., L.C., and J.E.H. Methodology: F.S.-K., H.H., V.R., J.D., T.G., N.H.A., M.S., E.T., M.G., J.L., X.T., M.M., W.W., C.L., R.P., T.C.W., K.H., M.H., A.Wo., R.R., C.T.S., C.B.-G., R.J.H., J.V., A.A.-Gr., E.L.K., R.C.S., W.H., D.G., S.La., A.Wa., O.B., S.R., B.S.-L., C.A., B.A.G., L.C., J.E.H., M.D.B., and A.A.-Gu. Project administration: F.S.-K., H.H., V.R., J.D., N.H.A., M.S., R.P., T.C.W., C.A., B.A.G., L.C., J.E.H., M.D.B., and A.A.-Gu. Resources: C.A., B.A.G., L.C., J.E.H., M.D.B., and A.A.-Gu. Software: F.S.-K., H.H., T.G., M.S., C.L., R.P., T.C.W., K.H., M.H., A.Wo., R.R., C.T.S., and D.G. Supervision: C.A., B.A.G., L.C., J.E.H., M.D.B., and A.A.-Gu. Validation: F.S.-K., H.H., V.R., J.D., N.H.A., M.S., E.T., M.G., J.L., W.W., L.B., S.Li., C.T.S., and C.B.-G. Visualization: F.S.-K. and T.G. Writing \u2013 original draft: F.S.-K., H.H., C.A., B.A.G., L.C., J.E.H., M.D.B., and A.A.-Gu. Writing \u2013 review & editing: all authors. Competing interests: L.C. is a founder of Chemify Ltd. J.E.H. is the founder and CEO of Telescope Innovations, an enabling technologies startup located in Vancouver, BC, Canada. A.A.-Gu. is chief visionary officer and board member of Kebotix Inc., a company that carries out closed-loop molecular materials discovery. M.D.B., N.H.A., and W.W. are inventors on patents and/or patent applications related to MIDA and/or TIDA boronates held and submitted by the University of Illinois at Urbana-Champaign that cover composition of matter and methods of use. The authors declare no other competing interests. Data and materials availability: All data and code generated as part of this study are openly accessible either in the supplementary materials or in open repositories. Raw characterization data [nuclear magnetic resonance (NMR) spectra of all building blocks and scaled-up materials and raw HPLC-MS data in open-source format] are available at Zenodo (61). Synthesis and optical spectroscopy results for all target compounds are given in data S6 and have been deposited at Zenodo (61). Results of the high-throughput computational analysis are available at Zenodo (61). All training data for ML models are given in data S4 and S5 and are deposited at Zenodo (61). All software used in this work is freely available on Github (62), and a snapshot of the code has been deposited at Zenodo (63). License information: Copyright \u00A9 2024 the authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original US government works. https://www.science.org/about/ science-licenses-journal-article-reuse
PY - 2024/5/17
Y1 - 2024/5/17
N2 - 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.
AB - 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.
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U2 - 10.1126/science.adk9227
DO - 10.1126/science.adk9227
M3 - Article
C2 - 38753786
AN - SCOPUS:85193501585
SN - 0036-8075
VL - 384
JO - Science
JF - Science
IS - 6697
M1 - eadk9227
ER -