ThinkFactory 2025: Community discussion on harmonizing and accelerating self-driving laboratories

<h2>Summary</h2> ThinkFactory 2025 was a virtual workshop jointly hosted by the Acceleration Consortium and CMAC to facilitate discussion on harmonizing and accelerating self-driving laboratories. The 3-h event brought together more than 50 participants for plenary and breakout discussion across four themed tracks: AI and machine learning, data, orchestration, and robotics. Key priorities highlighted by the community included the need for clearer benchmarks to demonstrate value, improved accessibility for experimentalists without programming expertise, and stronger standards for interoperability, safety, and reproducibility. Participants also emphasized the importance of structured human-AI collaboration and shared infrastructure to promote openness and efficiency. This paper outlines the event structure and design and key discussion insights, providing a reproducible framework for hosting collaborative, cross-institutional virtual workshops.

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Publication Details

Journal
Matter
Published
2026-03-31
DOI
https://doi.org/10.1016/j.matt.2026.102757
Primary Topic
Scientific Computing and Data Management
Type
article
Field-Weighted Citation Impact
0.00

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article

ThinkFactory 2025: Community discussion on harmonizing and accelerating self-driving laboratories

Mohammad Salehian, Alastair J. Florence, Sterling G. Baird, Thomas Pickles
Matter
Scientific Computing and Data Management
article

ThinkFactory 2025: Community discussion on harmonizing and accelerating self-driving laboratories

Mohammad Salehian, Alastair J. Florence, Sterling G. Baird, Thomas Pickles
article en

Abstract

<h2>Summary</h2> ThinkFactory 2025 was a virtual workshop jointly hosted by the Acceleration Consortium and CMAC to facilitate discussion on harmonizing and accelerating self-driving laboratories. The 3-h event brought together more than 50 participants for plenary and breakout discussion across four themed tracks: AI and machine learning, data, orchestration, and robotics. Key priorities highlighted by the community included the need for clearer benchmarks to demonstrate value, improved accessibility for experimentalists without programming expertise, and stronger standards for interoperability, safety, and reproducibility. Participants also emphasized the importance of structured human-AI collaboration and shared infrastructure to promote openness and efficiency. This paper outlines the event structure and design and key discussion insights, providing a reproducible framework for hosting collaborative, cross-institutional virtual workshops.

MatterVol. 9(5)
University of Strathclyde (GB), University of Toronto (CA)
University of Strathclyde, University of Toronto, Canada First Research Excellence Fund, Engineering and Physical Sciences Research Council
Industry, innovation and infrastructure
Openalex Percentile: Top 33%
Scientific Computing and Data Management
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