Neural Network for Modeling the Mechanical Properties of Gelatin-Cellulose Nanocrystals Hydrogel Membrane for Heavy Metal ions Removal from Wastewater

Abstract

The mechanical properties of Gelatin-cellulose nanocrystals hydrogel membrane were investigated for the removal of heavy metal ions from wastewater. The membrane was characterized using Scanning Electron Microscopy (SEM) and Fourier Transform Infrared Spectroscopy (FTIR) analysis. Neural Network (NN) model was developed to predict the mechanical properties such as Young’s modulus, tensile strength, and elongation. The NN predicted results are very close to the experimental results with R2 = 0.99315. The predicted values were found to be in excellent agreement with the experimental data and the current model has a good learning precision and generalization. The results revealed that the developed model is very accurate.