A novel method for biosynthesis of copper oxide nanoparticles using banana blossom and E-waste: characterization and application in malachite green dye removal through response surface methodology optimization

被引:0
|
作者
A. H. Anchani [1 ]
A. H. Abishini [1 ]
T. Ashokkumar [2 ]
机构
[1] St. Joseph’s College of Engineering,
[2] Haramaya University Harar,undefined
[3] The Assam Royal Global University,undefined
来源
Discover Biotechnology | / 1卷 / 1期
关键词
E-waste; Green reduction; Copper oxide nanoparticle; Nanoscale imaging; Dye degradation; RSM; Box Behnken design;
D O I
10.1007/s44340-024-00004-9
中图分类号
学科分类号
摘要
Textile dyes pose a significant threat to water resources, adversely affecting living organisms. Treating such contaminated water demands sophisticated technology, often expensive and requiring meticulous care. The use of copper oxide nanoparticles as a photocatalyst for degrading textile dyes is a promising solution. However, conventional chemical synthesis of copper oxide nanoparticles can be lengthy and environmentally unfriendly. To address this, a green technology approach was adopted in this research. A novel process was developed by extracting copper sulfate solution from E-waste, utilizing it as a precursor. Simultaneously, banana blossom extract (Musa paradisiaca) acted as a reducing agent in the biosynthesis of copper oxide nanoparticles, serving as a biocatalyst for malachite green dye removal. Optical characterization using a UV–Visible spectrophotometer revealed a peak around ~250 nm, indicating the presence of copper oxide. Fourier-transform infrared spectroscopy identified chemical groups within the sample, and X-ray diffraction spectroscopy confirmed its crystalline nature. The morphology of the synthesized copper oxide nanoparticles was investigated using transmission electron microscopy and energy-dispersive X-ray analysis. The potential application of CuO-NP in malachite green dye removal was successfully demonstrated, achieving a dye removal efficiency of 92% under optimal conditions. A quantitative analysis of dye removal was conducted and optimized using response surface methodology and analysis of variance, which indicated significant interactions among the variables. This eco-friendly and cost-effective approach showcases the feasibility of green technology in addressing environmental challenges associated with textile dye contamination.
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