Abstract
The present study aims toward green synthesis of copper oxide nanoparticles utilizing Sal seed deoiled cake (Sal DOC) extract, a by-product of forest industries, thereby adding value to it. Characteristic brownish-black color precipitate and peak at 260–280 nm in UV–Vis spectrophotometer confirmed the synthesis of CuO NPs which were further characterized by using various morphological, and structural techniques. The green synthesized CuO NPs demonstrated remarkable ability to remove three azo dyes, namely Erichrome Black T (EBT), Congo Red (CR), and Reactive Violet 1 (RV1) through adsorption. After employing NPs, decolorization of 97.1%, 96.8%, and 98.7%, and was attained in 30min, 1 h, and 3 h of reaction time for RV1, CR, and EBT, respectively. Further, the CuO NPs could successfully be recovered and re-used for seven consecutive cycles, retaining more than 80% of dye removal efficiency. Implementation of adsorption isotherms and kinetics models showed that removal of all three dyes followed Langmuir isotherm and pseudo-second-order kinetics respectively. The CuO NPs were then applied for the remediation of real textile wastewater spiked with a mixture of EBT, CR and RV1 dyes, where 76.2% of decolorization was achieved within 3 h of treatment. Enhanced radicle growth and germination percentage of Vigna radiata seeds showed toxicity removal and environmental safety of using CuO NPs-treated textile wastewater for irrigation purposes, thus aligning with sustainability goals by reducing the need for wastewater disposal and its associated environmental impact. Synthesized NPs displayed promising antibacterial activity against S. aureus, B. subtilis, Aeromonas sp. and S. epidermidis both by agar well diffusion method as well as by impregnation of cotton fabrics, which states their potential applicability in the biomedical field. Thereby, the current study suggests an environment-friendly and economical approach for CuO NPs biosynthesis with multifaceted applications, thus contributing to the principles of sustainability and resource optimization.
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