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Science acceleration and accessibility with self-driving labs

Author

Listed:
  • Richard B. Canty

    (North Carolina State University)

  • Jeffrey A. Bennett

    (North Carolina State University)

  • Keith A. Brown

    (Boston University)

  • Tonio Buonassisi

    (Massachusetts Institute of Technology)

  • Sergei V. Kalinin

    (The University of Tennessee)

  • John R. Kitchin

    (Carnegie Mellon University)

  • Benji Maruyama

    (Materials and Manufacturing Directorate)

  • Robert G. Moore

    (Oak Ridge National Laboratory)

  • Joshua Schrier

    (Fordham University)

  • Martin Seifrid

    (North Carolina State University)

  • Shijing Sun

    (University of Washington)

  • Tejs Vegge

    (Technical University of Denmark)

  • Milad Abolhasani

    (North Carolina State University)

Abstract

In the evolving landscape of scientific research, the complexity of global challenges demands innovative approaches to experimental planning and execution. Self-Driving Laboratories (SDLs) automate experimental tasks in chemical and materials sciences and the design and selection of experiments to optimize research processes and reduce material usage. This perspective explores improving access to SDLs via centralized facilities and distributed networks. We discuss the technical and collaborative challenges in realizing SDLs’ potential to enhance human–machine and human–human collaboration, ultimately fostering a more inclusive research community and facilitating previously untenable research projects.

Suggested Citation

  • Richard B. Canty & Jeffrey A. Bennett & Keith A. Brown & Tonio Buonassisi & Sergei V. Kalinin & John R. Kitchin & Benji Maruyama & Robert G. Moore & Joshua Schrier & Martin Seifrid & Shijing Sun & Tej, 2025. "Science acceleration and accessibility with self-driving labs," Nature Communications, Nature, vol. 16(1), pages 1-11, December.
    • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-59231-1
    DOI: 10.1038/s41467-025-59231-1
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