CationicNanoparticle Networks (CNNs) with RemarkablyEfficient, 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.

Publication Details

Journal
Figshare
Published
2025-02-10
DOI
https://doi.org/10.1021/acsami.4c21249.s001
Primary Topic
Per- and polyfluoroalkyl substances research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

CationicNanoparticle Networks (CNNs) with RemarkablyEfficient, Simultaneous Adsorption of Microplastics and PFAS

Figshare
Per- and polyfluoroalkyl substances research
article

CationicNanoparticle Networks (CNNs) with RemarkablyEfficient, Simultaneous Adsorption of Microplastics and PFAS

article en

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.

Figshare
Life below water
Openalex Percentile: Top 63%
Per- and polyfluoroalkyl substances research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.