ISI Papers With Our Products

Title: Optimizing Parameters on Alignment of Pcl/Pga Nanofibrous Scaffold: An Artificial Neural Networks Approach
Journal: International journal of biological macromolecules
Author: 1. Esmaeil Mirzaei, Amir Amani, Reza Faridi-Majidi, 1,2. Farnoush Asghari Paskiabi, 1,3. Reza Saber
Year: 2015
Address: 1. Department of Medical Nanotechnology, School of Advanced Technologies in medicine, Tehran University of Medical Sciences, Tehran, Iran 2. National Cell Bank of Iran, Pasteur Institute of Iran, Tehran, Iran 3. Research Center for Science and Technology in Medicine (RCSTIM), Imam Khomeini Hospital Complex - Keshavarz Blvd., Tehran, Iran
Abstract: This paper proposes an artificial neural networks approach to finding the effects of electrospinning parameters on alignment of poly(-caprolactone)/poly(glycolic acid) blend nanofibers. Four electrospinning parameters, namely total polymer concentration, working distance, drum speed and applied voltage were considered as input and the standard deviation of the angles of nanofibers, introducing fibers alignments, as the output of the model. The results demonstrated that drum speed and applied voltage are two critical factors influencing nanofibers alignment, however their effect are entirely interdependent. Their effects also are not independent of other electrospinning parameters. In obtaining aligned electrospun nanofibers, the concentration and working distance can also be effective. In vitro cell culture study on random and aligned nanofibers showed directional growth of cells on aligned fibers.
Keywords: Electrospinning Artificial neural networks Nanofibers alignment Poly(-caprolactone) Poly(glycolic acid)
Application: Scaffold, Tissue Engineering
Product Model 1: Electroris
Product Model 2:
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