Modeling the relationship between electrospinning process parameters and ferrofluid/polyvinyl alcohol magnetic nanofiber diameter by artificial neural networks

Abstract

The relationship between the fiber diameter and electrospinning process variables is complicated and nonlinear. In this study, we developed an artificial neural network model to correlate the relationships between the electrospinning process variables (voltage, flow rate, distance, and collector rotating speed) and the fiber diameter of Ferrofluid/polyvinyl alcohol. The model was able to find the significance of each process variable on fiber diameter for the desired experimental set by both qualitative (index of relative importance) and quantitative analysis. We developed a user interface design of the ANN model for easy use.