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Computationally predicted persistence of micro- and nanoplastics: Decay of polyethylene terephthalate in neutral, acidic and alkaline media
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Researchers combined density functional theory calculations with a Shrinking Core Model to predict PET nanoplastic degradation rates across neutral, acidic, and alkaline conditions without relying on empirically fitted constants, finding that alkaline conditions decompose PET within days while acidic conditions extend persistence to decades, and that surface area and porosity are the primary drivers governing how quickly particles break down.
Polyethylene terephthalate micro- and nanoplastics (PET-NPs) constitute a prevalent and enduring environmental risk, yet detailed mechanistic kinetics of their breakdown in environment remain poorly studied. This work presents robust multi-scale computational methodology which extends a semi-empirical computational procedure for predicting multistep chemical reaction kinetics for polymers, specifically focusing on PET nanoparticles degradation under neutral, acidic, and alkaline conditions. Our approach combines Density Functional Theory calculations with an adapted Shrinking Core Model to predict degradation rates, eliminating the reliance on empirically adjusted rate constants. Model accuracy was confirmed by strong agreement with experimental PET degradation data. Our findings reveal a striking difference in degradation rates: alkaline conditions significantly accelerate the hydrolysis of PET, decomposing it within hundreds of hours to days, while acidic conditions, cause extremely slow degradation, taking decades. Crucially, our model quantifies that increased BET surface area and porosity of PET nanoparticles are primary drivers of degradation efficiency. The multiscale platform serves as a reliable, predictive nanoengineering tool model for evaluating that describes PET longevity in aquatic systems and supports advanced strategies for the safe and sustainable development of synthetic polymers and for improved plastic waste management.
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