Litcius/Paper detail

Engineering the Electronic Structures of Metal–Organic Framework Nanosheets via Synergistic Doping of Metal Ions and Counteranions for Efficient Water Oxidation

Zhong‐Yin Zhao, Xiaoxu Sun, Hongwei Gu, Zheng Niu, Pierre Braunstein, Jian‐Ping Lang

2022ACS Applied Materials & Interfaces37 citationsDOI

Abstract

Metal–organic framework (MOF) nanosheets with attractive chemical and structural properties have been considered as prominent oxygen evolution reaction (OER) electrocatalysts, while the insufficient exposed active sites and low electrical conductivity of MOFs limit their electrocatalytic activity and further industrial applications. Herein, a unique strategy to remarkably boost electrocatalytic OER activity of one Ni-based MOF is developed by the simultaneous incorporation of Fe3+ ions and BF4– anions within its layer structure. The optimized electrocatalyst NiFe-MOF-BF4–-0.3 NSs shows superior OER activity with a required ultralow overpotential of 237 mV at 10 mA cm–2, a small Tafel slope of 41 mV dec–1, and outstanding stability in an alkaline medium. The experimental and density functional theory (DFT) calculation results verify that the interactions between metal (M) ions and BF4– anions (defined as M···F, M = Ni or Fe) in this catalyst can adjust the adsorption abilities of oxygen intermediates and lower the free energy barrier of the potential-determining step by tailoring its electronic structure, thereby remarkably boosting its OER activity. This protocol provides new insights into surface and structure engineering of 2D MOFs, leading to greatly enhanced electrocatalytic OER performance.

Topics & Concepts

OverpotentialOxygen evolutionTafel equationElectrocatalystMaterials scienceCatalysisMetal-organic frameworkChemical engineeringAdsorptionWater splittingInorganic chemistryNanotechnologyChemistryPhysical chemistryElectrochemistryElectrodeOrganic chemistryEngineeringPhotocatalysisElectrocatalysts for Energy ConversionAdvanced battery technologies researchAdvanced Memory and Neural Computing