Cationic Nanoparticle Networks (CNNs) with Remarkably Efficient, Simultaneous Adsorption of Microplastics and PFAS

Of the past decade, micro/nanoplastics (MP/NP) and per- and polyfluoroalkyl substances (PFAS) have become two of the most pervasive persistent organic pollutants leading to significant accumulation within waterways. Various sorbent materials have been evaluated for PFAS and MP/NP removal, but their simultaneous removal has rarely been explored. Herein, we report a library of polymer-based, cationic nanoparticle networks (CNN) with systematic variation in surface charge density, polymer molecular weight, and nanoparticle size for the removal of anionic MP/NP and PFAS from aqueous solutions. These materials are synthesized in three, one-pot steps starting with polymerization-induced self-assembly (PISA) followed by rapid photocuring and quaternary ammonium salt formation resulting in 3D networks consisting solely of cationic polymer nanoparticles. Our best performing CNN material demonstrated record-high MP removal capacities of <i>Q</i><sub>max</sub> = 1865 mg/g and <i>K</i><sub>F</sub> = 58.0 (mg/g)(L/mg)<sup>1/<i>n</i></sup> based on Langmuir and Freundlich isotherm model estimations, respectively. Furthermore, the CNN materials demonstrated efficient removal of NPs and MPs in complex water media, such as in seawater and at different pH values, demonstrating the overall material applicability. Finally, simultaneous and efficient removal of MPs and perfluorooctanoic acid (PFOA) was accomplished with similar <i>Q</i><sub>max</sub> (MP) = 478.4 mg/g and <i>Q</i><sub>max</sub> (PFOA) = 134.6 mg/g allowing for dual use.

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Publication Details

Journal
ACS Applied Materials & Interfaces
Published
2025-02-10
DOI
https://doi.org/10.1021/acsami.4c21249
Citations
15
Primary Topic
Membrane Separation Technologies
Type
article
Field-Weighted Citation Impact
12.26

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article

Cationic Nanoparticle Networks (CNNs) with Remarkably Efficient, Simultaneous Adsorption of Microplastics and PFAS

Dylan B. Shuster, Ali Shahrokhinia, Sahaj Rijal, James F. Reuther et al.
15 citations
ACS Applied Materials & Interfaces
Membrane Separation Technologies
12.26
article

Cationic Nanoparticle Networks (CNNs) with Remarkably Efficient, Simultaneous Adsorption of Microplastics and PFAS

Dylan B. Shuster, Ali Shahrokhinia, Sahaj Rijal, James F. Reuther, Shayesteh Tafazoli, David J. Morefield, Dorcas M. Ruhamya, Kamryn A. Dubray
article en
15 citations

Abstract

Of the past decade, micro/nanoplastics (MP/NP) and per- and polyfluoroalkyl substances (PFAS) have become two of the most pervasive persistent organic pollutants leading to significant accumulation within waterways. Various sorbent materials have been evaluated for PFAS and MP/NP removal, but their simultaneous removal has rarely been explored. Herein, we report a library of polymer-based, cationic nanoparticle networks (CNN) with systematic variation in surface charge density, polymer molecular weight, and nanoparticle size for the removal of anionic MP/NP and PFAS from aqueous solutions. These materials are synthesized in three, one-pot steps starting with polymerization-induced self-assembly (PISA) followed by rapid photocuring and quaternary ammonium salt formation resulting in 3D networks consisting solely of cationic polymer nanoparticles. Our best performing CNN material demonstrated record-high MP removal capacities of <i>Q</i><sub>max</sub> = 1865 mg/g and <i>K</i><sub>F</sub> = 58.0 (mg/g)(L/mg)<sup>1/<i>n</i></sup> based on Langmuir and Freundlich isotherm model estimations, respectively. Furthermore, the CNN materials demonstrated efficient removal of NPs and MPs in complex water media, such as in seawater and at different pH values, demonstrating the overall material applicability. Finally, simultaneous and efficient removal of MPs and perfluorooctanoic acid (PFOA) was accomplished with similar <i>Q</i><sub>max</sub> (MP) = 478.4 mg/g and <i>Q</i><sub>max</sub> (PFOA) = 134.6 mg/g allowing for dual use.

ACS Applied Materials & InterfacesVol. 17(7)
University of Massachusetts Lowell (US), Johns Hopkins University (US), BASF (United States) (US)
National Science Foundation, U.S. Geological Survey, Michigan Technology Tri-Corridor, Division of Graduate Education
Openalex Percentile: Top 1%
Membrane Separation Technologies
12.26
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