Modeling Mechanochemical Depolymerization of PET in Ball-Mill Reactors Using DEM Simulations

Area of Science:

• Materials Science
• Chemical Engineering
• Computational Modeling

Background:

• Consumer plastic waste poses significant environmental challenges.
• Efficient and sustainable recycling methods are crucial for waste management.
• Mechanochemical depolymerization offers a solvent-free approach to polymer recycling.

Purpose of the Study:

• To develop a physics-based mathematical model for mechanochemical depolymerization in ball mills.
• To optimize operating conditions for efficient polymer-to-monomer transformation.
• To establish a predictive tool for monomer yield in plastic recycling.

Main Methods:

• Calibrated and validated a discrete element method (DEM) model using experimental video data and computer vision.
• Systematically studied the influence of ball mill operating parameters on energy input.
• Developed a linear correlation between DEM simulations and experimental monomer yield for poly(ethylene terephthalate) (PET).
• Trained a reduced-order model to predict monomer yields rapidly.

Main Results:

• A direct relationship was found between vibrating milling vessel conditions and total energy supplied.
• A linear correlation was established between DEM simulations and experimental monomer yield for PET depolymerization.
• The reduced-order model enables fast estimation of monomer yields, reducing computational cost.

Conclusions:

• The developed mathematical model accurately predicts monomer yields for mechanochemical depolymerization.
• This approach facilitates the optimization of operating conditions for sustainable plastic recycling.
• The study provides a pathway for efficient, solvent-free transformation of polymers into monomers.