Catalytic technologies play a pivotal role in wastewater treatment, yet identifying high-performance catalysts through conventional approaches remains challenging. A multi-agent artificial intelligence system has been developed to enable application-oriented catalyst discovery by coordinating tasks typically distributed among human experts.
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References
Burger, B. et al. Nature 583, 237–241 (2020).
Bran, A. M. et al. Nat. Mach. Intell. 6, 525–535 (2024).
Boiko, D. A., MacKnight, R., Kline, B. & Gomes, G. Nature 624, 570–578 (2023).
Steiner, S. et al. Science 363, eaav2211 (2019).
Strieth-Kalthoff, F. et al. Science 384, eadk9227 (2024).
Tom, G. et al. Chem. Rev. 124, 9633–9732 (2024).
Parvulescu, V. I., Epron, F., Garcia, H. & Granger, P. Chem. Rev. 122, 2981–3121 (2022).
Wee, S. Y. & Aris, A. Z. npj Clean Water 6, 57 (2023).
Lee, J., von Gunten, U. & Kim, J.-H. Environ. Sci. Technol. 54, 3064–3081 (2020).
Pan, Y. et al. Nat. Water https://doi.org/10.1038/s44221-026-00634-9 (2026).
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Jiang, Y., Wang, C. Catalyst discovery through AI agent collaboration. Nat Water 4, 548–549 (2026). https://doi.org/10.1038/s44221-026-00637-6
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DOI: https://doi.org/10.1038/s44221-026-00637-6
