Optimizing Parameters on Alignment of Pcl/Pga Nanofibrous Scaffold: An Artificial Neural Networks Approach Publisher Pubmed



Paskiabi FA^{1, 2} ; Mirzaei E¹ ; Amani A¹ ; Shokrgozar MA² ; Saber R^{1, 3} ; Faridimajidi R¹
Source: International Journal of Biological Macromolecules Published:2015

Abstract

This paper proposes an artificial neural networks approach to finding the effects of electrospinning parameters on alignment of poly(ε-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. © 2015 Elsevier B.V.