Application of Computational Studies Using Density Functional Theory (DFT) to Evaluate the Catalytic Degradation of Polystyrene.

The degradation of polystyrene (PS) represents a significant challenge in plastic waste management due to its chemical stability and low biodegradability. In this study, the catalytic degradation mechanisms of PS were investigated by density functional theory (DFT)-based calculations using the hybrid functional B3LYP and the 6-311G++(d,p) basis in Gaussian 16. The influence of acidic (AlCl, Fe(SO)) and basic (CaO) catalysts was evaluated in terms of activation energy, reaction mechanisms, and degradation products. The results revealed that acid catalysts induce PS fragmentation through the formation of carbocationic intermediates, promoting the selective cleavage of C-C bonds in branched chains with bond dissociation energies (BDE) of 176.8 kJ/mol (C1-C7) and 175.2 kJ/mol (C3-C8). In contrast, basic catalysts favor β-scission by stabilizing carbanions, reducing the BDE to 151.6 kJ/mol (C2-C3) and 143.9 kJ/mol (C3-C4), which facilitates the formation of aromatic products such as styrene and benzene. Fe(SO) was found to significantly decrease the activation barriers to 328.12 kJ/mol, while the basic catalysts reduce the energy barriers to 136.9 kJ/mol. Gibbs free energy (ΔG) calculations confirmed the most favorable routes, providing key information for the design of optimized catalysts in PS valorization. This study highlights the usefulness of computational modeling in the optimization of plastic recycling strategies, contributing to the development of more efficient and sustainable methods.