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A platform that designs, prints and tests catalytic reactors

Nature Reviews Materials (2025)Cite this article

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The design of catalytic reactors has so far been based on human input, and the exploration of reactor geometry remains underdeveloped, particularly for multiphasic systems where variables such as surface-to-volume ratio and flow patterns are key. Now, writing in Nature Communications, Victor Sans and collaborators present a digital platform that integrates the design, fabrication and optimization of catalytic reactors, combining machine learning and 3D printing.

The effectiveness of this tailored reactor design was tested on two multiphasic reactions: the hydrogenation of acetophenone and the CO₂ cycloaddition to epoxides. The reactors optimized for the two reactions have substantially different structures, but they both achieve excellent space–time yield. Combining geometric design and precise control of reaction conditions is a powerful paradigm that can be extended to more complex reactions, and the closed-loop system of Reac-Discovery enhances catalytic performance while saving researchers’ time.

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References

Original article

  • Tinajero, C. et al. Reac-Discovery: an artificial intelligence-driven platform for continuous-flow catalytic reactor discovery and optimization. Nat. Commun. 16, 9062 (2025)

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  1. Nature Reviews Materials http://www.nature.com/natrevmats/

    Giulia Pacchioni

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  1. Giulia Pacchioni
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Correspondence to Giulia Pacchioni.

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Pacchioni, G. A platform that designs, prints and tests catalytic reactors. Nat Rev Mater (2025). https://doi.org/10.1038/s41578-025-00855-6

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  • DOI: https://doi.org/10.1038/s41578-025-00855-6

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