Integrating DFT Computations and QSAR Modeling to Predict Adsorption of Organic Pollutants onto Microplastics in Aqueous Environments.

Ya Wang, Chao Li, Honghong Yi, Xiaolong Tang, Peng Zhao

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Article in Materials (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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5 authors.

Ya WangSchool of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China.ORCID 0000-0003-3101-0597

Chao LiEngineering Laboratory for Water Pollution Control and Resources Recovery, State Environmental Protection Key Laboratory of Wetland Ecology and Vegetation Restoration, School of Environment, Northeast Normal University, Changchun 130117, China.

Honghong YiSchool of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China.

Xiaolong TangSchool of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China.

Peng ZhaoSchool of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China.

Funding

Fundamental Research Funds for the Central Universities FRF-BD-25-003Fundamental Research Funds for the Central Universities FRF-TP-22-087A1National Key R&D Program of China 2023YFB3810800National Natural Science Foundation of China 22206095

6 · The paper itself

Abstract

Understanding the adsorption of organic pollutants onto microplastics in aqueous environments is crucial for assessing their environmental behavior and ecological risks. Herein, we used density functional theory (DFT) computations to simulate the aqueous adsorption of 54 organic compounds onto three representative microplastics, namely polyethylene (PE), polyoxymethylene (POM), and polyvinyl alcohol (PVA). Afterwards, based on theoretical molecular structural descriptors, we developed six quantitative structure activity relationship (QSAR) models based on datasets of 43 and 54 organic compounds, respectively. The results demonstrated that the oxygen-containing POM and PVA microplastics exhibited weaker adsorption in the aqueous phase compared to that in the gas phase. Furthermore, it revealed that the electron-rich atoms, van der Waals volumes and molecular polarizability exert substantial effects on the adsorption process on microplastics in water. These robust QSAR models can enable the prediction of adsorption energies for various organic pollutants on microplastics, which can offer a rapid approach for generating adsorption data. Moreover, the insights into adsorption mechanisms can provide a theoretical basis for designing modified or alternative plastics with lower environmental risks.

Indexed as

adsorption energyaqueous environmentdensity functional theory computationmicroplasticsquantitative structure activity relationship

Identifiers

PMID41976695

DOI10.3390/ma19071403

PMCPMC13074982

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