Prediction of water retention capacity of hydrolysed electrospun polyacrylonitrile fibers using statistical model and artificial neural network

  1. Venkateshwarapuram Rengaswami Giri Dev1,2,*,
  2. Jayarama Reddy Venugopal1,
  3. Muthusamy Senthilkumar3,
  4. Deepika Gupta1,
  5. Seeram Ramakrishna1

Article first published online: 8 MAY 2009

DOI: 10.1002/app.30059

Issue

Journal of Applied Polymer Science

Journal of Applied Polymer Science

Volume 113, Issue 5, pages 3397–3404, 5 September 2009

Additional Information

How to Cite

Giri Dev, V. R., Venugopal, J. R., Senthilkumar, M., Gupta, D. and Ramakrishna, S. (2009), Prediction of water retention capacity of hydrolysed electrospun polyacrylonitrile fibers using statistical model and artificial neural network. Journal of Applied Polymer Science, 113: 3397–3404. doi: 10.1002/app.30059

Author Information

  1. 1

    Division of Bioengineering, Nanoscience and Nanotechnology Initiative, National University of Singapore, Singapore 117576

  2. 2

    Department of Textile Technology, A.C. College of Technology, Anna University, Chennai 625025

  3. 3

    Department of Textile Technology, P.S.G. College of Technology, Coimbatore 641004

*Division of Bioengineering, Nanoscience and Nanotechnology Initiative, National University of Singapore, Singapore 117576

Publication History

  1. Issue published online: 1 JUN 2009
  2. Article first published online: 8 MAY 2009
  3. Manuscript Accepted: 13 JAN 2009
  4. Manuscript Received: 10 OCT 2008

Funded by

  • Department of Biotechnology, Ministry of Science and Technology, India. Grant Number: BT/IN/BTOA/Niche/2006

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Keywords:

  • electrospinning;
  • nanofibers;
  • hydrolysis;
  • neural network;
  • statistical model

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. J Appl Polym Sci, 2009

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