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Evaluation of the Effective Forcespinning Parameters Controlling Polyvinyl Alcohol Nanofibers Diameter Using Artificial Neural Network Publisher



Naghibzadeh M1 ; Adabi M2 ; Rahmani HR3 ; Mirali M4 ; Adabi M2
Authors
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Authors Affiliations
  1. 1. Department of Nanotechnology, Research and Clinical Centre for Infertility, Shahid Sadoughi University of Medical Sciences, Yazd, Iran
  2. 2. Young Researchers and Elite Club, Roudehen Branch, Islamic Azad University, Roudehen, Iran
  3. 3. Department of Food Science and Technology, Tehran North Branch, Islamic Azad University, Tehran, Iran
  4. 4. Nanotechnology Department, Pharmaceutical Sciences Branch, Islamic Azad University, Tehran, Iran
  5. 5. Department of Medical Nanotechnology, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran
  6. 6. Student's Scientific Research Center, Tehran University of Medical Sciences, Tehran, Iran

Source: Advances in Polymer Technology Published:2018


Abstract

In this research, the polyvinyl alcohol (PVA) nanofibers through forcespinning process were successfully produced and the effective parameters for predicting nanofibers diameter using artificial neural network (ANN) were investigated. The various parameters of forcespinning process including rotational speed, orifice, distance to the collector, and polymer concentration were designed to produce PVA nanofibers. Scanning electron microscopy (SEM) showed that the produced fibers diameter was in the range of 0.56–1.9 μm. The neural network with four input factors, three hidden layers with 5, 10, 1 nodes in each layers, respectively, and one output layer had the best performance in the testing sets. Moreover, the mean squared error (MSE) and linear regression (R) between observed and predicted nanofibers diameter were about 0.1077 and 0.9387, respectively, demonstrating a suitable performance for the prediction of nanofibers diameter using the selected neural network model. © 2017 Wiley Periodicals, Inc.