Self-driving laboratories (SDLs), which combine automated experimental hardware with computational experiment planning, have emerged as powerful tools for accelerating materials discovery. The intrinsic complexity created by their multitude of components requires an effective orchestration platform to ensure the correct operation of diverse experimental setups. Existing orchestration frameworks, however, are either tailored to specific setups or have not been implemented for real-world synthesis. To address these issues, we introduce ChemOS 2.0, an orchestration architecture that efficiently coordinates communication, data exchange, and instruction management among modular laboratory components. By treating the laboratory as an “operating system” ChemOS 2.0 combines ab-initio calculations, experimental orchestration and statistical algorithms to guide closed-loop operations. To demonstrate its capabilities, we showcase ChemOS 2.0 in a case study focused on discovering organic laser molecules. The results confirm the ChemOS 2.0’s prowess in accelerating materials research and demonstrate its potential as a valuable design for future SDL platforms.

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ChemOS 2.0: an orchestration architecture for chemical self-driving laboratories

Malcolm Sim 1,2, Mohammad Ghazi Vakili 1,2, Felix Strieth-Kalthoff 1,2, Han Hao 1,2, Riley J. Hickman 1,2,3, Santiago Miret 4, Sergio Pablo-García 1,2, and Alán Aspuru-Guzik 1,2,3,5,6,7,8

1. Department of Chemistry, University of Toronto, Lash Miller Chemical Laboratories 80 St. George Street, ON M5S 3H6, Toronto, Canada 

2. Department of Computer Science, University of Toronto, Sandford Fleming Building, 40 St. George Street, ON M5S 2E4, Toronto, Canada

3. Vector Institute for Artificial Intelligence, 661 University Ave. Suite 710, ON M5G 1M1, Toronto, Canada

4. Intel Labs, 2200 Mission College Blvd, Santa Clara, CA 95054, USA

5. Department of Materials Science & Engineering, University of Toronto, 184 College St., M5S 3E4, Toronto, Canada

6. Department of Chemical Engineering & Applied Chemistry, University of Toronto, 200 College St. ON M5S 3E5, Toronto, Canada

7. Lebovic Fellow, Canadian Institute for Advanced Research (CIFAR), 661 University Ave., M5G 1M1, Toronto, Canada

8. Acceleration Consortium, 80 St George St, M5S 3H6, Toronto, Canada

DOI: 10.26434/chemrxiv-2023-v2khf

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