journal article·2026-06Open access

Lignin ligand boosts Ni3+ species generation for biomass electrocatalytic oxidation

Tairan Pang, Tonghui Zhao, Mingxuan Liu, Guanhua Wang, Yi Liu, Yuanjiamei Zhou, Yinjuan Wan, Wenjie Hu, Junkai Li, Ting Xu, Kun Liu, Xupo Liu, Wenjie Sui, Rui Xu, Ligang Wang, Chuanling Si, Deli Wang

Abstract

The electrocatalytic oxidation of biomass-derived platform molecules provides a sustainable pathway to high-value chemicals. The most commonly used Ni(OH) 2 catalyst, valued for its inherent redox activity, low cost, and structural tunability, however, suffers from insufficient active Ni 3+ species during the oxidation process. Herein, we developed an SL-Ni(OH) 2 catalyst with boosted Ni 3+ generation capability through a biomass-derived sulfonated lignin (SL) ligand regulation strategy. Leveraging the multifunctional structure of lignin, SL constructs an unsaturated Ni–O coordination environment on Ni(OH) 2 , which induces defect formation and Ni-site electronic modulation to synergistically reduce crystal field stability and weaken lattice hydroxyl O–H bond strength, thereby facilitating the generation of active Ni 3+ . The optimized SL-Ni(OH) 2 delivers a 29.90-fold enhancement in current density compared to pristine Ni(OH) 2 for the 5-hydroxymethylfurfural oxidation reaction (HMFOR), achieving a Faradaic efficiency > 99% for 2,5-furandicarboxylic acid (FDCA). Moreover, the assembled HMFOR electrolytic cell operates continuously for 100 h at a current density of 300 mA cm −2 with a > 90% FDCA yield, indicating excellent stability. This work demonstrates the potential of bio-derived polymers as sustainable ligands to tailor the electronic structures of electrocatalysts, turning underused lignin into a multi-site synergistic ligand and also offering a promising strategy for efficient biomass electrocatalytic oxidation.
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Research context

OpenAlex topics: Electrocatalysts for Energy Conversion · Lignin and Wood Chemistry · Catalysis for Biomass Conversion

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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