Optimizing the photodegradation process of low-density polyethylene using Taguchi's robust statistical design

Abstract

The present study employs the Taguchi statistical design for optimizing the photodegradation process of low-density polyethylene (LDPE) films by varying five significant parameters i.e., catalyst loading (%), exposure time (in days), pH, size of the films (cm x cm), and temperature (℃), simultaneously to determine the maximum photodegradation on LDPE. The physiochemical, morphological, and molecular structural changes were observed in all-nanocomposite (LDPE and catalyst samples) before and after degradation. One way-ANOVA (Analysis of Variance) results demonstrated that catalyst loading, and exposure time were the most influential factors and contributed 65 % and 25 %, respectively to determine the degradation rate. Further, a kinetic study was performed to determine the photo-degradation rate, and it follows first-order photo-kinetics model. The maximum photodegradation was observed for that LDPE sample that was loaded with 12 % catalyst with a pH of 6 at 45°C that was exposed to the UV light for 10 days in a photoreactor, it degraded most efficiently with a weight loss of 16.25 %. Additionally, recyclability studies confirmed that stability and reusability of TiO₂ as a photocatalyst for carrying out degradation experiments upto three consecutive cycles. Moreover, there is a high co-relation between predicted and experimental data with R²> 0.96, which demonstrates the effectiveness of the prediction with the maximum degradation of LDPE film.