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Jun 28, 2025

Tuning nitrate reduction reaction selectivity via selective adsorption in electrified membranes | Nature Chemical Engineering

Nature Chemical Engineering volume 2, pages 379–390 (2025)Cite this article 536 Accesses 53 Altmetric Metrics details Improving electrochemical reactions by manipulating the properties of catalyst

Nature Chemical Engineering volume 2, pages 379–390 (2025)Cite this article

536 Accesses

53 Altmetric

Metrics details

Improving electrochemical reactions by manipulating the properties of catalyst active sites often involves tradeoffs in activity, selectivity, stability and material costs. Here we incorporate a nitrite-adsorbing ionophore as a cooperative nitrite-enriching component into an electrified membrane to achieve high nitrate conversion (94.6%) and ammonia selectivity (91.9%) with a treatment time of only a few seconds (6 s). The ionophore enriched nitrite within the local electrocatalyst environment, facilitating conversion of unreacted nitrite to ammonia to inhibit overall nitrite formation (1.1%) without directly modifying the catalytic active sites. Integrating the ionophore as a selective adsorption component into a copper/carbon nanotube-based electrified membrane led to long-term selective ammonia production from low-concentration nitrate in real surface water and wastewater effluent without using precious metals. The concept of employing cooperative adsorption components to manipulate the local electrocatalyst environment and control reaction selectivity without precious metals or complex synthesis, especially when coupled with the stability and efficiency of scalable electrified membranes, could be extended to advance diverse electrocatalytic applications beyond nitrate.

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All data are presented in the article and its Supplementary Information. Source data are provided with this paper, including the atomic coordinates of the optimized computational models.

The code for generating Fig. 3d,e in the study is publicly available on GitHub at https://github.com/yyan107/Cu_TTM.

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This research was supported by the NSF Nanosystems Engineering Research Center for Nanotechnology-Enabled Water Treatment (grant no. EEC-1449500 to L.R.W.). The computations were conducted through the Arizona State University research computing environment. We thank Y. Duan (Yale University) for discussions on electrofiltration mechanisms.

Department of Chemical and Environmental Engineering, Yale University, New Haven, CT, USA

Yingzheng Fan, Weiyi Pan, Eric Chen, Ji-Yong Kim, Julia Simon, Max Saffer-Meng & Lea R. Winter

State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing, China

Yingzheng Fan

Chemical Engineering and Materials Science and Engineering, School for the Engineering of Matter, Transport and Energy, Arizona State University, Tempe, AZ, USA

Yu Yan, Obinna Nwokonkwo, Daniel J. Rivera & Christopher Muhich

Institute for Ocean Engineering, Shenzhen International Graduate School, Tsinghua University, Shenzhen, China

Xiaoxiong Wang

Center of Double Helix, Shenzhen International Graduate School, Tsinghua University, Shenzhen, China

Xiaoxiong Wang

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Y.F., X.W. and L.R.W. conceived of the idea and designed the experiments. L.R.W. supervised the project. Y.F., E.C. and J.S. fabricated the membranes. Y.F., E.C., J.S., J.-Y.K., M.S.-M. and W.P. performed the membrane tests and analyzed the results. Y.F., Y.Y., O.N., D.J.R. and C.M. carried out the DFT calculations and analysis. Y.F., Y.Y. and L.R.W. wrote the paper. All authors discussed the results and revised the paper.

Correspondence to Lea R. Winter.

Y.F. and L.R.W. are listed as coinventors on International Patent Application No. PCT/US25/27226 filed on 1 May 2025, submitted by Yale University, which covers the coupling electrofiltration with a cooperative nitrite-enriching component for nitrate reduction as described in this paper. The other authors declare no competing interests.

Nature Chemical Engineering thanks Bryan Goldsmith and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Figs. 1–33, Tables 1–9 and Notes 1–4.

Atomic coordinates of the optimized computational models for CuNP in Fig. 3c.

Atomic coordinates of the optimized computational models for TTM in Fig. 3c.

Statistical source data.

Statistical source data.

Statistical source data.

Statistical source data.

Statistical source data.

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Fan, Y., Yan, Y., Nwokonkwo, O. et al. Tuning nitrate reduction reaction selectivity via selective adsorption in electrified membranes. Nat Chem Eng 2, 379–390 (2025). https://doi.org/10.1038/s44286-025-00237-3

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Received: 10 July 2024

Accepted: 16 May 2025

Published: 20 June 2025

Issue Date: June 2025

DOI: https://doi.org/10.1038/s44286-025-00237-3

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