Activating Surface Oxygen in Ce/Mo‐Doped Ni Oxyhydroxide for Synergistically Enhancing Furfural Oxidation and Hydrogen Evolution at Ampere‐Level Current Densities
Abstract The integration of biomass‐platform molecule oxidation with water electrolysis is a promising strategy to reduce energy consumption in hydrogen production and obtain high‐value chemicals simultaneously, yet the efficiency of organic oxidation requires further improvement. Herein, we developed a highly efficient Ce, Mo co‐doped Ni‐based (oxy)hydroxide catalyst, where Mo with high spin state promotes the adsorption of furfural (FA), while Ce activates surface lattice oxygen (O L ), lowering the energy barrier for O L ─OH coupling to form OOH, the key intermediate for high current densities. The catalyst achieves an industrial‐grade current density of 1000 mA cm − 2 at a remarkably low potential of 1.46 V versus RHE in furfural oxidation, with exceptional selectivity (99.4%) and Faradaic efficiency (97.7%) for furoic acid. When deployed as anode in an anion‐exchange membrane reactor, the NiMoCe/NF catalyst sustains a current density of 500 and 1000 mA cm − 2 at a cell voltage of only 1.85 and 2.15 V, respectively, surpassing most reported continuous flow electrolyzers limited to 200 mA cm − 2 . Moreover, the system exhibits outstanding durability after 200 h of continuous operation. This work provides critical insights into the rational design of catalysts for energy‐efficient biomass valorization coupled with industrial hydrogen production.
Authors
- Zidong Wei (ORCID: https://orcid.org/0000-0001-8001-9729)
- Xun Huang (ORCID: https://orcid.org/0000-0001-9988-6953)
- Xiaohua Hu
- Lingping Hu (ORCID: https://orcid.org/0000-0001-8826-4526)
- Yang Xiang (ORCID: https://orcid.org/0000-0002-6634-7424)
- Tian Yu Cao (ORCID: https://orcid.org/0000-0002-4461-9409)
- Li Li (ORCID: https://orcid.org/0000-0001-5324-2271)
- Jia Cheng (ORCID: https://orcid.org/0009-0004-7042-4172)
Institutions
- Chongqing University (CN)
Publication Details
- Journal
- Angewandte Chemie
- Published
- 2025-05-07
- DOI
- https://doi.org/10.1002/ange.202506017
- Citations
- 1
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.73