Estimation of Digital Porosity of Electrospun Veils by Image Analysis.

The present work reports on an empirical mathematical expression for predicting the digital porosity (DP) of electrospun nanofiber veils, employing emulsions of poly(vinyl alcohol) (PVOH) and olive and orange oils. The electrospun nanofibers were analyzed by scanning electron microscopy (SEM), observing orientation and digital porosity (DP) in the electrospun veils. To determine the DP of the veils, the SEM micrographs were transformed into a binary system, and then the threshold was established, and the nanofiber solid surfaces were emphasized. The relationship between the experimental results and those obtained with the empirical mathematical expression displayed a correlation coefficient (R2) of 0.97 by employing threshold II. The mathematical expression took into account experimental variables such as the nanofiber humidity and emulsion conductivity prior to electrospinning, in addition to the corresponding operation conditions. The results produced with the proposed expression showed that the prediction of the DP of the electrospun veils was feasible with the considered thresholds.

Artificial Neural Networks for Predicting the Diameter of Electrospun Nanofibers Synthesized from Solutions/Emulsions of Biopolymers and Oils.

In the present work, different configurations of nt iartificial neural networks (ANNs) were analyzed in order to predict the experimental diameter of nanofibers produced by means of the electrospinning process and employing polyvinyl alcohol (PVA), PVA/chitosan (CS) and PVA/aloe vera (Av) solutions. In addition, gelatin type A (GT)/alpha-tocopherol (α-TOC), PVA/olive oil (OO), PVA/orange essential oil (OEO), and PVA/anise oil (AO) emulsions were used. The experimental diameters of the nanofibers electrospun from the different tested systems were obtained using scanning electron microscopy (SEM) and ranged from 93.52 nm to 352.1 nm. Of the three studied ANNs, the one that displayed the best prediction results was the one with three hidden layers with the flow rate, voltage, viscosity, and conductivity variables. The calculation error between the experimental and calculated diameters was 3.79%. Additionally, the correlation coefficient (R2) was identified as a function of the ANN configuration, obtaining values of 0.96, 0.98, and 0.98 for one, two, and three hidden layer(s), respectively. It was found that an ANN configuration having more than three hidden layers did not improve the prediction of the experimental diameter of synthesized nanofibers.