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Autonomous platforms for data-driven organic synthesis

Author

Listed:
  • Wenhao Gao

    (Massachusetts Institute of Technology)

  • Priyanka Raghavan

    (Massachusetts Institute of Technology)

  • Connor W. Coley

    (Massachusetts Institute of Technology
    Massachusetts Institute of Technology)

Abstract

Achieving autonomous multi-step synthesis of novel molecular structures in chemical discovery processes is a goal shared by many researchers. In this Comment, we discuss key considerations of what an ideal platform may look like and the apparent state of the art. While most hardware challenges can be overcome with clever engineering, other challenges will require advances in both algorithms and data curation.

Suggested Citation

  • Wenhao Gao & Priyanka Raghavan & Connor W. Coley, 2022. "Autonomous platforms for data-driven organic synthesis," Nature Communications, Nature, vol. 13(1), pages 1-4, December.
    • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-28736-4
    DOI: 10.1038/s41467-022-28736-4
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    References listed on IDEAS

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    Cited by:

    1. Michael G. Taylor & Daniel J. Burrill & Jan Janssen & Enrique R. Batista & Danny Perez & Ping Yang, 2023. "Architector for high-throughput cross-periodic table 3D complex building," Nature Communications, Nature, vol. 14(1), pages 1-11, December.

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