Facile green synthesis of silver nanoparticles using Terminalia bellerica kernel extract for catalytic reduction of anthropogenic water pollutants
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 ultraviol...
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| Published in | Colloid and interface science communications Vol. 37; p. 100276 |
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| Main Authors | , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier B.V
01.07.2020
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| Subjects | |
| Online Access | Get full text |
| ISSN | 2215-0382 2215-0382 |
| DOI | 10.1016/j.colcom.2020.100276 |
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| Abstract | 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 spectroscopy, transmission electron & scanning electron microscopy, energy dispersive X-ray analysis, X-ray diffraction, and Fourier transform infrared spectroscopy. Synthesized silver nanoparticles displayed innate catalytic reduction 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 between 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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•Biogenic silver nanoparticles were synthesized using novel T. bellerica kernel extract.•Reaction parameters were evaluated for the facile one pot synthesis of nanosilver.•Silver nanoparticles displayed innate catalytic reduction of organic pollutants.•Nanoparticles catalysis data was modelled via Artificial neural networks modeling. |
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| AbstractList | 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 spectroscopy, transmission electron & scanning electron microscopy, energy dispersive X-ray analysis, X-ray diffraction, and Fourier transform infrared spectroscopy. Synthesized silver nanoparticles displayed innate catalytic reduction 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 between 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.
[Display omitted]
•Biogenic silver nanoparticles were synthesized using novel T. bellerica kernel extract.•Reaction parameters were evaluated for the facile one pot synthesis of nanosilver.•Silver nanoparticles displayed innate catalytic reduction of organic pollutants.•Nanoparticles catalysis data was modelled via Artificial neural networks modeling. |
| ArticleNumber | 100276 |
| Author | Sohail, Ayesha Sherin, Lubna Ul-Hamid, Anwar Amjad, Um-e-Salma Mustafa, Maria Jabeen, Riffat |
| Author_xml | – sequence: 1 givenname: Lubna surname: Sherin fullname: Sherin, Lubna email: lubnasherin@cuilahore.edu.pk organization: Department of Chemistry, COMSATS University Islamabad, Lahore, Defence Road, Off Raiwind Road, Lahore 54000, Pakistan – sequence: 2 givenname: Ayesha surname: Sohail fullname: Sohail, Ayesha organization: Department of Mathematics, COMSATS University Islamabad, Lahore, Defence Road, Off Raiwind Road, Lahore 54000, Pakistan – sequence: 3 givenname: Um-e-Salma surname: Amjad fullname: Amjad, Um-e-Salma organization: Department of Chemical Engineering, COMSATS University Islamabad, Lahore, Defence Road, Off Raiwind Road, Lahore 54000, Pakistan – sequence: 4 givenname: Maria surname: Mustafa fullname: Mustafa, Maria organization: Department of Chemical Engineering, COMSATS University Islamabad, Lahore, Defence Road, Off Raiwind Road, Lahore 54000, Pakistan – sequence: 5 givenname: Riffat surname: Jabeen fullname: Jabeen, Riffat organization: Department of Statistics, COMSATS University Islamabad, Lahore, Defence Road, Off Raiwind Road, Lahore 54000, Pakistan – sequence: 6 givenname: Anwar surname: Ul-Hamid fullname: Ul-Hamid, Anwar organization: Center for Engineering Research, Research Institute, King Fahd University of Petroleum & Minerals, Dhahran 31261, Saudi Arabia |
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| Keywords | Catalytic reduction Pollutants Silver nanoparticles Terminalia bellerica Artificial neural networks |
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