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An integrated self-optimizing programmable chemical synthesis and reaction engine

Author

Listed:
  • Artem I. Leonov

    (The University of Glasgow)

  • Alexander J. S. Hammer

    (The University of Glasgow)

  • Slawomir Lach

    (The University of Glasgow)

  • S. Hessam M. Mehr

    (The University of Glasgow)

  • Dario Caramelli

    (The University of Glasgow)

  • Davide Angelone

    (The University of Glasgow)

  • Aamir Khan

    (The University of Glasgow)

  • Steven O’Sullivan

    (The University of Glasgow)

  • Matthew Craven

    (The University of Glasgow)

  • Liam Wilbraham

    (The University of Glasgow)

  • Leroy Cronin

    (The University of Glasgow)

Abstract

Robotic platforms for chemistry are developing rapidly but most systems are not currently able to adapt to changing circumstances in real-time. We present a dynamically programmable system capable of making, optimizing, and discovering new molecules which utilizes seven sensors that continuously monitor the reaction. By developing a dynamic programming language, we demonstrate the 10-fold scale-up of a highly exothermic oxidation reaction, end point detection, as well as detecting critical hardware failures. We also show how the use of in-line spectroscopy such as HPLC, Raman, and NMR can be used for closed-loop optimization of reactions, exemplified using Van Leusen oxazole synthesis, a four-component Ugi condensation and manganese-catalysed epoxidation reactions, as well as two previously unreported reactions, discovered from a selected chemical space, providing up to 50% yield improvement over 25–50 iterations. Finally, we demonstrate an experimental pipeline to explore a trifluoromethylations reaction space, that discovers new molecules.

Suggested Citation

  • Artem I. Leonov & Alexander J. S. Hammer & Slawomir Lach & S. Hessam M. Mehr & Dario Caramelli & Davide Angelone & Aamir Khan & Steven O’Sullivan & Matthew Craven & Liam Wilbraham & Leroy Cronin, 2024. "An integrated self-optimizing programmable chemical synthesis and reaction engine," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
  • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-45444-3
    DOI: 10.1038/s41467-024-45444-3
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    References listed on IDEAS

    as
    1. Ian W. Davies, 2019. "The digitization of organic synthesis," Nature, Nature, vol. 570(7760), pages 175-181, June.
    2. Benjamin J. Shields & Jason Stevens & Jun Li & Marvin Parasram & Farhan Damani & Jesus I. Martinez Alvarado & Jacob M. Janey & Ryan P. Adams & Abigail G. Doyle, 2021. "Bayesian reaction optimization as a tool for chemical synthesis," Nature, Nature, vol. 590(7844), pages 89-96, February.
    3. Sourav Chatterjee & Mara Guidi & Peter H. Seeberger & Kerry Gilmore, 2020. "Automated radial synthesis of organic molecules," Nature, Nature, vol. 579(7799), pages 379-384, March.
    Full references (including those not matched with items on IDEAS)

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