4.7 Article

Removing forever chemicals via amphiphilic functionalized membranes

Journal

NPJ CLEAN WATER
Volume 5, Issue 1, Pages -

Publisher

NATURE PORTFOLIO
DOI: 10.1038/s41545-022-00193-y

Keywords

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Funding

  1. Independent Research and Development (IRAD) Fund from the Research and Exploratory Development Mission Area of the Johns Hopkins University Applied Physics Laboratory

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An amphiphilic coating was developed to functionalize an aluminum oxide hydroxide membrane for efficient removal of PFAS contaminants in drinking water. The new coated filters outperformed the commonly used granular activated carbon technology in PFAS removal. Molecular dynamics simulations were used to predict the interaction between coatings and contaminants, providing a potential for future design.
Per- and poly-fluoroalkyl species (PFAS) remain ever-present drinking water contaminants. While some physical adsorption technologies for PFAS removal have been implemented on a large scale, they are limited by high cost and low effectiveness. In this work, an amphiphilic coating was developed and used to functionalize an aluminum oxide hydroxide membrane. Dynamic filtration of challenge water containing eighteen PFAS demonstrated >99% removal of eleven of eighteen PFAS as defined in EPA 537.1. Comparable performance was observed under gravity filtration conditions with >90% removal of fifteen of the eighteen PFAS. A comparison of breakthrough rates using amphiphilic silanes versus granular activated carbon (GAC), the commonly used filtration technology, was performed. Filters with the new amphiphilic coating outperformed GAC under dynamic filtration conditions by more than an order of magnitude for the perfluorooctanoic acid adsorption capacity and even greater for perfluorooctane sulfonic acid. Molecular dynamics simulations were used to compute the free energy, enthalpy, and entropy of interactions between coatings and six PFAS contaminants. Computed interaction free-energy (FE) values agree with experimental filtration performance across contaminants. The ability to use simulated FE values to predict filtration efficiency presents an opportunity for future in-silico rational design with overall reduced cost and development time.

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