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Abstract
Achieving controllable fine-tuning of defects in catalysts at the atomic level has become a zealous pursuit in catalysis-related fields. However, the generation of defects is quite random, and their flexible manipulation lacks theoretical basis. Herein, we present a facile and highly controllable thermal tuning strategy that enables fine control of nanodefects via subtle manipulation of atomic/lattice arrangements in electrocatalysts. Such thermal tuning endows common carbon materials with record high efficiency in electrocatalytic degradation of pollutants. Systematic characterization and calculations demonstrate that an optimal thermal tuning can bring about enhanced electrocatalytic efficiency by manipulating the N-centered annulation–volatilization reactions and C-based sp3/sp2 configuration alteration. Benefiting from this tuning strategy, the optimized electrocatalytic anodic membrane successfully achieves >99% pollutant (propranolol) degradation during a flow-through (~2.5 s for contact time), high-flux (424.5 L m−2 h−1), and long-term (>720 min) electrocatalytic filtration test at a very low energy consumption (0.029 ± 0.010 kWh m−3 order−1). Our findings highlight a controllable preparation approach of catalysts while also elucidating the molecular level mechanisms involved.
Achieving controllable fine-tuning of defects is desired for electrocatalysts. Here, the authors present a facile and controllable thermal tuning strategy that enables fine control of nanodefects, thereby endowing common carbon materials with high electrocatalytic oxidation efficiency.
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1 Tsinghua University, State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Beijing, China (GRID:grid.12527.33) (ISNI:0000 0001 0662 3178)
2 Beijing Forestry University, Beijing Key Lab for Source Control Technology of Water Pollution, College of Environmental Science and Engineering, Beijing, China (GRID:grid.66741.32) (ISNI:0000 0001 1456 856X)
3 Yale University, Department of Chemical and Environmental Engineering, New Haven, USA (GRID:grid.47100.32) (ISNI:0000000419368710)