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A QSAR prediction model for adsorption of organic contaminants on microplastics: Dubinin-Astakhov plus linear solvation energy relationships
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Researchers combined the Dubinin-Astakhov isotherm model with linear solvation energy relationships to build a QSAR model predicting the adsorption of pharmaceuticals and personal care products onto various microplastic polymer types.
Numerous pharmaceuticals and personal care products (PPCPs) co-exist with various types of microplastics (MPs) in the environment, making it extremely hard to experimentally measure all their adsorption interactions. Thus, a precise prediction model is on demand. In this study, we combined the commonly used Dubinin-Astakhov (DA) model and the linear solvation energy relationships (LSERs) model to predict the adsorption capacity (Q) and adsorption affinity (E) of MPs for PPCPs, including the key parameters of MP (specific surface area, oxygen-containing functional groups), and the Kamlet-Taft solvation parameters of organic contaminants. The model was validated with the experimental data of 8 PPCPs and 8 MPs (i.e. pristine and aged PE, PET, PS, PVC) plus some published adsorption data. This new model also indicated that the adsorption of PPCPs on those MPs was primarily governed by hydrophobic interaction and hydrogen bonding. The developed model can predict the adsorption of PPCPs onto MPs with a high accuracy and can also provide insights into the understanding of interaction forces in the adsorption process.
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