材料科学
纳米颗粒
氢
结晶学
控制重构
电子结构
化学
纳米技术
光电子学
化学物理
作者
Chengyu Zhang,Longyu Wang,Fabrice Ndayisenga,Anam Jalil,Yiming Zhang,Zhisheng Yu
标识
DOI:10.1038/s42004-026-02012-8
摘要
The hydrogen evolution reaction (HER) is critical for clean energy conversion, yet achieving efficient and durable electrocatalysis across a wide pH range remains a major challenge. Modulating the electronic structure of metal single atoms has shown promise, but is often constrained by weak metal–support interactions in conventional carbon matrices. Here, we report a pH–universal HER electrocatalyst comprising atomically dispersed Ru sites and carbon–confined Ru nanoparticles, synthesized via one–step pyrolysis of biomass–derived precursors. The catalyst delivered low overpotentials of 176 mV (Tafel slope: 23 mV dec–1) in acidic and 241 mV (40 mV dec–1) in alkaline media at 200 mA cm–2, along with outstanding operational stability exceeding 500 hours—outperforming commercial Pt/C. This performance arises from electron–rich Ru single atoms (RuN4) modulated by neighboring Ru nanoparticles, synergistically embedded within a hydrophilic and porous carbon scaffold. Density functional theory (DFT) calculations revealed a near–optimal hydrogen adsorption free energy (ΔGH* = –0.25 eV) in acidic conditions and a moderate water dissociation barrier (0.94 eV) in alkaline media. Our findings demonstrate a viable strategy for integrating nanoparticles and single atoms to achieve both high activity and durability, while highlighting the upcycling of biomass into advanced HER catalysts via rational interface engineering. Achieving efficient and durable electrocatalysis for the hydrogen evolution reaction (HER) across a wide pH range remains a major challenge. Here, the authors use biomass-derived precursors to prepare a pH–universal HER electrocatalyst comprising atomically dispersed Ru sites and carbon–confined Ru nanoparticles that exhibits low overpotentials in both acidic and alkaline media, with operational stability exceeding 500 hours.
科研通智能强力驱动
Strongly Powered by AbleSci AI