Construction of Ag deposited g-C3N4 loaded Co Al LDH ternary composites with aim of pharmaceutical wastewater treatment:Pathways and mechanism for ciprofloxacin degradation
Source abstract
Abstract
Elimination of pharmaceutical drugs from wastewater through photocatalysis is considered an effective and environment-friendly approach to prevent their introduction into the aquatic environment. We constructed ternary Ag deposited g-C 3N 4 loaded Co Al layered double hydroxide (LDH) composites through multistep synthesis for wastewater remediation of the pharmaceutical industry. We explored the role of g-C 3N 4 (CN) and Ag NPs in Ag@CN-LDH heterostructure for improving the photocatalytic performance of LDH. This study revealed that the photoactivity of the ternary composite got significantly affected by the CN and Ag loadings. The visible light-driven ternary composite with 10 wt% of CN and 1 wt% of Ag loadings over LDH exhibited the maximum 97% degradation of commercial ciprofloxacin within 90 min, which was highly superior to that noticed for bare LDH. The improved photocatalytic proficiency was credited to the expanded surface region, quick charge move at the CN-LDH interface, and the Surface Plasmon resonance and electron-accepting capability of Ag NPs. The ternary composite was highly stable and recyclable up to five cycles with less than a 3% fall in degradation efficiency. The LC-MS analysis was performed to determine the intermediates and final products. Three degradation pathways were proposed including the cleavage of the piperazine ring and the decarboxylation of the quinoline ring. A possible mechanism for efficient charge transfer and photocatalytic degradation was proposed based on the band edge positions calculated from valence band XPS spectra, photoluminescence analysis, and scavenging experiments.
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Research context
OpenAlex topics: Advanced Photocatalysis Techniques · Layered Double Hydroxides Synthesis and Applications · Covalent Organic Framework Applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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