期刊
COLLOID AND INTERFACE SCIENCE COMMUNICATIONS
卷 37, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.colcom.2020.100276
关键词
Silver nanoparticles; Terminalia bellerica; Catalytic reduction; Pollutants; Artificial neural networks
资金
- COMSATS University Islamabad, Pakistan [16-57/CRGP/CUI/LHR]
Biogenic silver nanoparticles were synthesized using novel Terminalia bellerica kernel extract. Optimal synthesis of silver nanoparticles was achieved at 0.016 mg/mL kernel extract and 2.0 mM silver nitrate concentrations under ambient conditions. Silver nanoparticles were characterized by ultraviolet-visible absorption spectro-scopy, transmission electron & scanning electron microscopy, energy dispersive X-ray analysis, X-ray diffraction, and Fourier transform infrared spectroscopy. Synthesized silver nanoparticles displayed innate catalytic re-duction of organic pollutants such as 4-nitrophenol, methylene blue, eosin yellow and methyl orange. Results revealed that among all the pollutants, nanosilver exhibited higher reduction of 4-nitrophenol than others and reaction was found following the pseudo-first order kinetics. An artificial neural networks (ANNs) model based on experimental data was developed to predict the catalytic performance of nanosilver. Good correlation be-tween ANN model based results and experimental data indicated that it could be used to forecast the catalytic performance and hence extent of pollutant reduction at various catalyst concentrations.
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