Cu/Mn–ZnO nanoparticles with dual-reaction centers (DRCs) induced peroxymonosulfate (PMS) activation for refractory organic compounds catalytic degradation
Source abstract
Abstract
Heterogeneous, sulfate radical-based advanced oxidation processes (AOPs) have arisen in recent decades due to their high reactivity and oxidation capabilities for a wide spectrum of hazardous and refractory organic compounds. The presence of a rate-limiting step with a slow conversion rate from ≡Me(n+1)+ to ≡Men+ in transition metal oxides, on the other hand, severely limits the performance of PMS activation. Also, the activity of metal catalysts is pH-sensitive. Herein, we provide a promising strategy to solve these issues. In this paper, Cu/Mn–ZnO nanoparticles consisting of dual reaction centers (DRCs) with electron-rich/poor areas were synthesized by hydrothermal methods, which demonstrated high activity, stability, and reusability in heterogeneous catalysis. Characterization results (e.g., XPS) revealed that the catalysts present surface electron-rich Cu & oxygen vacancies (OVs) centers/deficient micro-areas, avoiding direct reaction with metal ions, while pollutants can be captured and preliminarily degraded by the electron-deficient areas as electron donors. As a result, the structure eliminated the influence of pH on activity in the range of 2.5–10.5 and exhibited significant catalytic activity. Using Rhodamine B (Rh-B) as the target pollutant, the degradation rate was up to 96% at 10 min. Moreover, the EPR analysis and quenching experiments revealed that 1O2 was the predominant reactive oxygen species (ROS) attacking the pollutants. Overall, the catalyst developed in this study has great potential for the treatment of refractory pollutants by activating peroxymonosulfate (PMS).
Source: expertdata · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Advanced oxidation water treatment · Advanced Photocatalysis Techniques · Catalytic Processes in Materials Science
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (65)
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