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Novel SnO2@Cu3(BTC)2 Composites as a Highly Efficient Photocatalyst and Fluorescent Sensor.
Deepika1, Heena2, Manpreet Kaur1
1Department of Chemistry, Punjabi University, Patiala-147 002, Punjab, India.
A novel tin oxide and metal-organic framework composite efficiently degrades methylene blue dye and detects trinitrophenol in water. This recyclable material shows promise for industrial photocatalysis and sensing applications.
Area of Science:
- Materials Science
- Nanotechnology
- Environmental Chemistry
Background:
- Metal-organic frameworks (MOFs) offer tunable porosity for various applications.
- Tin oxide (SnO2) nanoparticles exhibit photocatalytic properties.
- Developing efficient and cost-effective materials for environmental remediation and sensing is crucial.
Purpose of the Study:
- To synthesize a novel SnO2@Cu3(BTC)2 composite material.
- To evaluate its efficiency as a photocatalyst for dye degradation.
- To assess its capability for selective sensing of 2,4,6-trinitrophenol (TNP).
Main Methods:
- Bottom-up synthesis via impregnation of SnO2 nanoparticles into Cu3(BTC)2 MOF.
- Characterization using FTIR, PXRD, SEM, and EDS.
- Photocatalytic degradation experiments with methylene blue (MB) dye under sunlight.
- Fluorescence sensing of TNP in aqueous solutions.
- Density Functional Theory (DFT) calculations for mechanism assessment.
Main Results:
- The SnO2@Cu3(BTC)2 composite was successfully synthesized and characterized.
- Achieved 85.12% degradation of MB dye within 80 minutes.
- Demonstrated excellent recyclability over five cycles with retained efficiency.
- Successfully detected TNP with a limit of detection (LOD) of 2.82 µM.
- Exhibited high selectivity for TNP over other nitroaromatic compounds.
Conclusions:
- The synthesized SnO2@Cu3(BTC)2 composite is a cost-effective and efficient material.
- It shows significant potential as a reusable photocatalyst for dye degradation.
- The composite serves as a highly selective and sensitive fluorescent sensor for TNP.
- The findings suggest broad industrial applicability in environmental sensing and remediation.
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