4.7 Article

Membranes with Thin Hydrogel Selective Layers Containing Viral-Templated Palladium Nanoparticles for the Catalytic Reduction of Cr(VI) to Cr(III)

Journal

ACS APPLIED NANO MATERIALS
Volume 2, Issue 8, Pages 5233-5244

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/acsanm.9b01099

Keywords

catalytic membrane; hydrogel; ultrathin; hybrid membrane; biotemplated nanomaterials

Funding

  1. Tufts University
  2. Tufts Collaborates program
  3. National Science Foundation (NSF) [CBET-1703549, CBET-1553661]
  4. National Science Foundation under NSF [ECS-0335765]

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Membranes that simultaneously remove large organic molecules and catalytically treat smaller contaminants can provide a simple, compact, single-step water treatment solution. Incorporating nanoparticles (NPs) into membranes can impart catalytic activity but is extremely challenging to achieve while preventing aggregation, maintaining high stability, and retaining accessibility to the NP surfaces. Here, we present a new tunable and scalable strategy, interfacially initiated free radical polymerization (IIFRP), for hybrid water filtration membranes incorporating small, uniform, well-dispersed catalytic NPs immobilized on tobacco mosaic virus (TMV) nanotemplates within their ultrathin hydrogel selective layers. Hybrid membranes are prepared by adding the TMV-templated NPs to the monomer solution during IIFRP. These membranes catalytically reduce Cr(VI), an acutely toxic and carcinogenic contaminant, to Cr(III), an essential nutrient. The catalytic NPs are fully accessible to the reactants within the hydrogel and exhibit extremely high catalytic activity, achieving up to 98% conversion in a single pass. Furthermore, because of the hydrogel network, these NPs are exceptionally stable, fully retaining their catalytic activity with continuous filtration for at least 3 days. These results illustrate a versatile approach for integration of various nanomaterials within membrane selective layers, enabling the creation of advanced membranes with new and versatile functionalities for next-generation applications.

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