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Rapid proton transport through a bio-inspired PO4-built protective layer for stabilizing 5-hydroxymethylfurfural conversion at high current densities

  • Wei Ji
  • , Wenjie Zhang
  • , Chen Deng*
  • , Yuwei Xiong
  • , Qi Hao
  • , Hao Zhang
  • , Bing Song
  • , Wenlei Zhu
  • , Dekui Shen
  • , Jason Chun-Ho Lam*
  • , Richen Lin*
  • *Corresponding author for this work

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

Abstract

Nickel-based electrocatalysts are pivotal for converting biomass-derived 5-hydroxymethylfurfural to 2,5-furandicarboxylic acid (FDCA), a key renewable precursor for biopolymers. However, their industrial adoption is limited by sluggish proton transfer kinetics, which restricts current density (targeting ≥200 mA cm−2) and triggers catalyst corrosion via proton accumulation, reducing stability. Inspired by biological phosphate buffers that regulate protons to stabilize intracellular pH, we engineered a phosphate-built protective layer (PO4-BPL) on a CuNiO catalyst. The PO4-BPL serves dual roles: creating rapid proton channels to enhance proton-coupled electron transfer and protecting the catalyst from proton-induced corrosion. The PO4-BPL/CuNiO delivers a current density exceeding 700 mA cm−2 with FDCA faradaic efficiency above 90% over 36 cycles, showcasing 7-fold stability improvement versus unmodified catalysts. In a continuous-flow electrolyzer, PO4-BPL/CuNiO operates for 70 h, far exceeding the 6 h lifetime of the CuNiO. Density functional theory calculations confirm PO4-BPL lowers proton migration energy barriers, enhancing mass transfer and preventing structural damage. This biomimetic strategy not only enables robust electrocatalysts for high current density applications, but also represents a green advance toward the sustainable and efficient production of biopolymer precursors.© The Royal Society of Chemistry 2026.
Original languageEnglish
Pages (from-to)225-241
Number of pages17
JournalGreen Chemistry
Volume28
Issue number1
Online published21 Nov 2025
DOIs
Publication statusPublished - 5 Jan 2026

Funding

This work was supported by Jiangsu Provincial Department of Science and Technology (BZ2024054), the National Natural Science Foundation of China (52276177, 52376172), the State Key Laboratory of Clean Energy Utilization (Open Fund Project No. ZJUCEU2023008), and the Natural Science Foundation of Jiangsu Province (BK20241315). The authors thank the Big Data Computing Center of Southeast University and the Center for Fundamental and Interdisciplinary Sciences of Southeast University. C. Deng acknowledges the Horizon Europe Guarantee MSCA Postdoctoral Fellowship (No. 101153313) funded by the UKRI Engineering and Physical Sciences Research Council (Ref: EP/Z002753/1).

UN SDGs

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

  1. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure

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