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Favoring the Originally Unfavored Oxygen for Enhancing Nitrogen-to-Nitrate Electroconversion

  • Xin Li (Co-first Author)
  • , Guangtong Hai (Co-first Author)
  • , Daniel H. C. Wan
  • , Yiwen Liao
  • , Zhangyi Yao
  • , Fenglin Zhao
  • , Lingzhi Huang
  • , Jinsong Zhou
  • , Gang Li
  • , Gao-Feng Chen*
  • , Feng Ryan Wang*
  • , Michael K. H. Leung*
  • , Haihui Wang*
  • *Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

Current nitrate production involves a two-step thermochemical process that is energy-intensive and generates substantial CO2 emissions. Sustainable NO3- production via the nitrogen electrooxidation reaction powered by renewable electricity is highly desirable, but the Faradaic efficiency (FE) at high production rates is unsatisfactory due to competition from the oxygen evolution reaction (OER). In this study, we propose reengineering the catalyst’s microstructure-to-macroenvironment interface by particularly utilizing the previously considered unfavored oxygen from the OER. We demonstrate that the re-engineered interface facilitates a record-breaking FE of 35.52% under 8 atm air, with an impressive increase in FE (41.56%) observed during a continuous electrochemical process lasting for 60 h due to the in situ formation of the O2-rich macro-interface environment. The revelation is anticipated to furnish groundbreaking perspectives for the reaction systems design in electrochemical nitrate production and other electrocatalytic fields. © 2025 American Chemical Society.
Original languageEnglish
Pages (from-to)8587-8596
Number of pages10
JournalJournal of the American Chemical Society
Volume147
Issue number10
Online published27 Feb 2025
DOIs
Publication statusPublished - 12 Mar 2025

Funding

We gratefully acknowledge the funding from the National Key R&D Program of China (Grant No. 2022YFB4002602), the Natural Science Foundation of China (Grant No. 22138005), Tsinghua University Initiative Scientific Research Program (2023Z02JMP001), the Research Grants Council of the Hong Kong Special Administrative Region, China (Project No. CityU 11206520), Ningbo Municipal Government Innovation 2025 Scheme (No. 2018B10023), the Shenzhen Knowledge Innovation Program (Basic Research, JCYJ20190808181205752), and the New Cornerstone Science Foundation through the XPLORER PRIZE. We acknowledge the BL01B1 beamline at SPring-8 (Japan) for the XAS experiments.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 13 - Climate Action
    SDG 13 Climate Action

RGC Funding Information

  • RGC-funded

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