Enhancing styrene monomer recovery from polystyrene pyrolysis: insights from density functional theory

Plastic waste pyrolysis offers a potential solution to reduce plastic accumulation, but prioritizing monomer recovery from the process is crucial to effectively address the environmental consequences of plastic accumulation. This study focuses on enhancing the yield of styrene during the pyrolysis of polystyrene by investigating thermal and kinetic data. A comprehensive investigation into the thermal degradation pathways of polystyrene is imperative to overcome the challenges associated with its waste management. The calculated bond dissociation energies reveal that the cleavage of non-terminal carbon-carbon bonds is energetically favorable, resulting in the formation of high molecular weight benzylic radicals. Based on these findings, four pyrolysis pathways are proposed, and the associated thermodynamic and kinetic parameters are determined using the DFT method. The major products identified in this study include styrene, α-methylstyrene, isopropylbenzene, methylbenzene, ethylbenzene, and methane. Furthermore, optimizing the temperature profile of the reactor is shown to enhance the recovery of styrene, thereby contributing to the reduction of plastic waste. This study provides valuable insights into the effective resource recovery from polystyrene waste pyrolysis, emphasizing the significance of managing pyrolysis conditions to achieve maximum yield. By controlling the temperature profile during the pyrolysis process, it is possible to obtain a high yield of styrene, facilitating the efficient recovery of the monomer from waste polystyrene and addressing the environmental concerns associated with plastic accumulation.

In this study, all calculations were performed using the B3LYP/6-31G(d) level of theory with the Gaussian 16 program package. The proposed model underwent geometry optimization and frequency calculations. Transition states were optimized using the TS Berny method, and energy profiles along reaction pathways were refined using the QST3 method. The IRC method validated proposed mechanisms and investigated energy profiles. Structural models were visualized using GaussView 6.0.