Closed-loop photoreactor design enabled by machine learning and digital twins
Researchers have developed a closed-loop photoreactor design workflow that combines digital twins and Bayesian optimization. This framework accelerates the development of efficient chemical reactors by simulating light behavior and optimizing geometry.
Why it matters
This innovation demonstrates how machine learning and digital modeling can significantly speed up chemical engineering and photochemical research.
Nature Communications ( 2026 ) Cite this article
We’re sharing this article early to provide faster access to peer-reviewed, accepted research. It is citable and carries a permanent DOI. This version is subject to further edits and will be replaced automatically by the final Version of Record. All legal disclaimers apply.
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