The effect of the functional groups of organic contaminants on their adsorption to PET microplastics: A combined DFT and QSPR approach

The adsorption of contaminants of emerging concern (CECs) onto microplastics (MPs) can alter their environmental behavior and toxicity. Thus, understanding adsorption and desorption processes is essential for accurate risk assessment. Models based on adsorption capacities lack robustness due to experimental variability. To address this, we applied a computational approach, combining density functional theory (DFT) and quantitative structure property relationship (QSPR) modeling to study interactions between polyethylene terephthalate (PET) MPs and model organic pollutants (m-COPs). Four QSPR models were developed by correlating interaction energies (E) at distinct PET adsorption sites, computed by DFT, with molecular descriptors of m-COPs. Model performance was evaluated through internal and external validation, including also external set of 7 selected CECs. Key descriptors reflect structural features influencing adsorption, particularly functional group size, flexibility, and the ability to form hydrogen bonds, which varied depending on the adsorption site. At the sites close to terminal hydroxyl or carboxyl groups adsorption is mainly controlled by the ability of m-COPs and CECs to form hydrogen bonds. At other sites, adsorption was driven by molecular size and the ability to form multiple interactions all of which contribute to the total interaction energy.