Characterization of gelatin/cellulose acetate nanofibrous scaffolds: Prediction and optimization by response surface methodology and artificial neural networks

Abstract

Gelatin/cellulose acetate electrospun nanofibers are a good candidates for simulation of extracellular matrix (ECM). Electrospinning of the blend is controlled by many parameters such as applied voltage, gap distance, solvent composition, polymer composition and solution concentration. The individual and interactive effects of these parameters on pH, electrical conductivity (EC) and viscosity of solutions, and diameter and quality of fibers were investigated. Response surface methodology (RSM) and artificial neural networks (ANNs) were considered to model and optimize the responses. EC, pH and viscosity of solutions were dependent on the solution parameters. The solvent composition and solution concentration had an influence on the fiber diameter and quality. The optimum conditions for fabricating qualified nanofibers with minimum diameter were 16.9 kV, 15.3 cm, 77.5 wt % of gelatin, 88.9 vol % of acetic acid and solution concentration of 20 wt %/vol %. Uniform beadless nanofibers with a diameter of 284 nm were attained at this optimum condition.