Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/174919
Title: A dynamic knowledge graph approach to distributed self-driving laboratories
Authors: Bai, Jiaru
Mosbach, Sebastian
Taylor, Connor J.
Karan, Dogancan
Lee, Kok Foong
Rihm, Simon D.
Akroyd, Jethro
Lapkin, Alexei A.
Kraft, Markus
Keywords: Engineering
Issue Date: 2024
Source: Bai, J., Mosbach, S., Taylor, C. J., Karan, D., Lee, K. F., Rihm, S. D., Akroyd, J., Lapkin, A. A. & Kraft, M. (2024). A dynamic knowledge graph approach to distributed self-driving laboratories. Nature Communications, 15(1), 462-. https://dx.doi.org/10.1038/s41467-023-44599-9
Journal: Nature Communications
Abstract: The ability to integrate resources and share knowledge across organisations empowers scientists to expedite the scientific discovery process. This is especially crucial in addressing emerging global challenges that require global solutions. In this work, we develop an architecture for distributed self-driving laboratories within The World Avatar project, which seeks to create an all-encompassing digital twin based on a dynamic knowledge graph. We employ ontologies to capture data and material flows in design-make-test-analyse cycles, utilising autonomous agents as executable knowledge components to carry out the experimentation workflow. Data provenance is recorded to ensure its findability, accessibility, interoperability, and reusability. We demonstrate the practical application of our framework by linking two robots in Cambridge and Singapore for a collaborative closed-loop optimisation for a pharmaceutically-relevant aldol condensation reaction in real-time. The knowledge graph autonomously evolves toward the scientist's research goals, with the two robots effectively generating a Pareto front for cost-yield optimisation in three days.
URI: https://hdl.handle.net/10356/174919
ISSN: 2041-1723
DOI: 10.1038/s41467-023-44599-9
Schools: School of Chemical and Biomedical Engineering 
Organisations: Cambridge Centre for Advanced Research and Education in Singapore
Rights: © The Author(s) 2024. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/.
Fulltext Permission: open
Fulltext Availability: With Fulltext
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