Abstract
ABSTRACT In this study, a handmade device was developed to prepare polymeric polypropylene (PP) nanofibres by forcespinning method. The characterisations of the prepared adsorbent were investigated by Fourier transform infrared spectroscopy (FTIR) and Scanning electron microscopy (SEM). Then, the performance of the prepared nanofibres was investigated as an adsorbent for the removal of uranium (VI) ion from the aqueous solution. Experimental parameters such as contact time and pH were optimised. The maximum adsorption was obtained with the adsorbent weight of 0.03 g, contact time of 60 min, and pH of 4. This study showed that PP nanofibre is an efficient adsorbent for uranium removal from aqueous solution. Also, the uranium removal process was modelled by artificial neural network (ANN) for predicting capacity removal. In this method, feed-forward back-propagation learning with Levenberg-Marquardt (LM), adaptive learning rate back-propagation (GDX) and resilient back-propagation (RP) algorithms were used.
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