Application of Chitosan-Zinc Oxide Nanoparticles for Lead Extraction From Water Samples by Combining Ant Colony Optimization with Artificial Neural Network

作者：Khajeh M^*; Pourkarami A; Arefnejad E; Bohlooli M; Khatibi A; Ghaffari Moghaddam M; Zareian Jahromi S

来源：Journal of Applied Spectroscopy, 2017, 84(4): 716-724.

DOI：10.1007/s10812-017-0535-y

• lead
• zinc oxide nanoparticles
• chitosan
• artificial neural network
• ant colony optimization
• water samples

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.

• 出版日期2017-9