Effect of electrospinning parameters on the production of polyvinyl alcohol (PVA)/Collagen (Type I) nanofiber membranes and the use of an adaptive neuro-fuzzy inference system for evaluating nanofiber diameters

Collagen Type I protein-based scaffolds are most commonly used because of their better healing properties. Production of type I collagen nanofibers is a challenge because of the high molecular weight of collagen obtained using the electrospinning method. For this reason, biodegradable polyvinyl (alchool) (PVA) was employed as an electrospun collagen type I source for bovine tendon. The aim of this study was to model the average diameter (D-a) of PVA/collagen type-I nanofibers using the input parameters PVA ratio (P), collagen type I ratio (C), PVA mixing ratio/collagen type I mixing ratio (M-r), applied voltage (V), and feed rate (F-r) parameters. The specified parameters were designed to produce nanofibers with various diameters. Scanning electron microscopy (SEM) with image software was used to calculate the D-a of the nanofibers. The mean squared error (MSE) and coefficient of determination (R-2) were evaluated for the observed and predicted nanofiber diameters. The findings show that increasing the ratio of PVA from 7 wt% to 9 wt% rise similar to 7% the average diameter. The average nanofiber diameter of PVA/collagen type I was varied according to the mixture, quantity of collagen, and electrospinning parameters. Furthermore, the D-a of the nanofibers increased with increasing collagen ratio and mixing ratio. In adverse cases, PVA (8 wt%) with Collagen Type I (4 wt%) having a ratio of 2:1 exhibited lower D-a with 76.2 nm. The observed results indicated that the designed adaptive neuro-fuzzy inference system model was effective for evaluating the relevant parameters and predicting the D-a of PVA/collagen type I.