Urea electrolysis is critically important for the advancement of sustainable and clean energy conversion technologies,addressing global energy shortages and environmental concerns.The urea oxidation reaction(UOR)poses a significant challenge due to its unfavorable thermodynamics,making it a pivotal step in urea splitting.The 6-electron transfer process of UOR presents a bottleneck due to its sluggish kinetics.Consequently,the development of efficient urea oxidation electrocatalysts and gaining insights into the electronic configuration of the central metal ion are of paramount significance in achieving high-performance urea-based energy conversion technologies.In this study,we report the successful synthesis of hierarchical Ni2P nanosheets@nanorods(P-Ni2P HNNs)as promising catalysts to enhance UOR efficiency.This catalyst is designed and constructed using a hexamethylenetetramine-hydrolytic coprecipitation-oxidation process and a straightforward phosphorus-substituted method.X-ray absorption fine structure spectroscopy indicates that the presence of P-modified metal centers is responsible for the elevated UOR activity of P-Ni2P HNNs,with the electronic structure of Nin+significantly enhancing Ni―O―O bond coupling for rapid UOR kinetics.Thanks to the highly exposed Nin+centers and the well-designed architecture,P-Ni2P HNNs exhibit superior UOR activity and stability,with a low overpotential of 132 mV at 10 mA∙cm-2,a small Tafel slope of 33.7 mV∙dec-1,and sustained durability for 6 h at 10 mA∙cm-2.Furthermore,a two-electrode cell for overall urea electrolysis is assembled with a P-Ni2P HNNs-2/NF anode,yielding a low potential of 1.411 V at 10 mA∙cm-2 and a high current density of 100 mA∙cm-2 at 1.595 V.This study presents an effective and viable approach for designing and synthesizing high-efficiency nickel-based phosphide electrocatalysts,which could pave the way for cost-effective and energy-efficient electrochemical hydrogen production,and advance phosphide research for various energy-related applications.
国家科技期刊平台
NSTL
万方数据
