Please use this identifier to cite or link to this item: https://doi.org/10.1002/app.30059
Title: Prediction of water retention capacity of hydrolysed electrospun polyacrylonitrile fibers using statistical model and artificial neural network
Authors: Dev, V.R.G.
Venugopal, J.R. 
Senthilkumar, M.
Gupta, D.
Ramakrishna, S. 
Keywords: Electrospinning
Hydrolysis
Nanofibers
Neural network
Statistical model
Issue Date: 5-Sep-2009
Citation: Dev, V.R.G., Venugopal, J.R., Senthilkumar, M., Gupta, D., Ramakrishna, S. (2009-09-05). Prediction of water retention capacity of hydrolysed electrospun polyacrylonitrile fibers using statistical model and artificial neural network. Journal of Applied Polymer Science 113 (5) : 3397-3404. ScholarBank@NUS Repository. https://doi.org/10.1002/app.30059
Abstract: Box Behnken design of experiment was used to study the effect of process variables such as alkali concentration, temperature and time on water retention capacity of the alkaline hydrolysed electrospun fibres. The hydrolysis of electrospun polyacrylonitrile fibres was carried out using sodium hydroxide with different processing conditions like concentration of alkali, temperature and time. With the increase in the concentration of alkali, time and temperature, the water retention capacity of membrane was found to increase in the membranes. Water retention capacities of the membranes were modeled and predicted using empirical as well as artificial neural network (ANN model). The fiber diameter and mean flow pore diameter of electrospun polyacrylonitrile fibers and hydrolyzed fibers shown in SEM images were 310 ± 50, 275 ± 75 nm, 0.9258 and 1.12 microns, respectively. The present study indicated that the nanofibrous membranes have potential for the water absorbing applications. © 2009 Wiley Periodicals, Inc.
Source Title: Journal of Applied Polymer Science
URI: http://scholarbank.nus.edu.sg/handle/10635/85565
ISSN: 00218995
DOI: 10.1002/app.30059
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