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Tuning nitrate reduction reaction selectivity via selective adsorption in electrified membranes

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

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Abstract

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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Fig. 1: Characterization of TTM-CuNP/CNT-EM.
Fig. 2: Mechanistic investigation of TTM ionophore in nitrite adsorption/desorption and its impact on nitrate reduction product selectivity.
Fig. 3: Nitrite binding models on CuNP and TTM.
Fig. 4: Electrochemical nitrate reduction performance of the TTM-CuNP/CNT-EM for practical applications.
Fig. 5: Preliminary techno-economic analysis.

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Data availability

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.

Code availability

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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Acknowledgements

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.

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Authors and Affiliations

  1. 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

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

    Yingzheng Fan

  3. 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

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

    Xiaoxiong Wang

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

    Xiaoxiong Wang

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  1. Yingzheng Fan
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Contributions

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.

Corresponding author

Correspondence to Lea R. Winter.

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Competing interests

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.

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

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Supplementary information

Supplementary Information

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

Supplementary Data 1

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

Supplementary Data 2

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

Source data

Source Data Fig. 1

Statistical source data.

Source Data Fig. 2

Statistical source data.

Source Data Fig. 3

Statistical source data.

Source Data Fig. 4

Statistical source data.

Source Data Fig. 5

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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