(2017) Application of Chitosan-Zinc Oxide Nanoparticles for Lead Extraction From Water Samples by Combining Ant Colony Optimization with Artificial Neural Network. Journal of Applied Spectroscopy. pp. 716-724. ISSN 0021-9037
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Abstract
Chitosan-zinc oxide nanoparticles (CZPs) were developed for solid-phase extraction. Combined artificial neural network-ant colony optimization (ANN-ACO) was used for the simultaneous preconcentration and determination of lead (Pb2+) ions in water samples prior to graphite furnace atomic absorption spectrometry (GF AAS). The solution pH, mass of adsorbent CZPs, amount of 1-(2-pyridylazo)-2-naphthol (PAN), which was used as a complexing agent, eluent volume, eluent concentration, and flow rates of sample and eluent were used as input parameters of the ANN model, and the percentage of extracted Pb2+ ions was used as the output variable of the model. A multilayer perception network with a back-propagation learning algorithm was used to fit the experimental data. The optimum conditions were obtained based on the ACO. Under the optimized conditions, the limit of detection for Pb2+ ions was found to be 0.078 mu g/L. This procedure was also successfully used to determine the amounts of Pb2+ ions in various natural water samples.
Item Type: | Article |
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Keywords: | lead zinc oxide nanoparticles chitosan artificial neural network ant colony optimization water samples modified nanometer sio2 solid-phase extraction aqueous-solution composite membranes genetic algorithm adsorption 1-(2-pyridylazo)-2-naphthol kinetics sorbent removal |
Divisions: | |
Page Range: | pp. 716-724 |
Journal or Publication Title: | Journal of Applied Spectroscopy |
Volume: | 84 |
Number: | 4 |
Identification Number: | 10.1007/s10812-017-0535-y |
ISSN: | 0021-9037 |
Depositing User: | مهندس مهدی شریفی |
URI: | http://eprints.zbmu.ac.ir/id/eprint/2349 |
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