Science acceleration and accessibility with self-driving labs

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.…

• NS
  National Science Foundation

  Awards: 2226511, 2320718, DE-AC05-00OR22725, 2332452
• UD
  U.S. Department of Energy

  Awards: AC05-00OR22725, DE-AC05, 00OR22725
• B
  Battelle

  Awards: DE-AC05, DE-AC05-00OR22725
• NC
  North Carolina State University
• U
  UT-Battelle

  Awards: DE-AC05-, AC05-00OR22725
• DG
  Danmarks Grundforskningsfond
• MR
  Materials Research Science and Engineering Center, Harvard University
• DO
  Division of Materials Research
• OR
  Oak Ridge National Laboratory

  Award: AC05-00OR22725