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Issue 10, 2020, Issue in Progress
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Nuclear wastewater decontamination by 3D-Printed hierarchical zeolite monoliths

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Abstract

The selective removal of radioactive cationic species, specifically 137Cs+ and 90Sr2+, from contaminated water is critical for nuclear waste remediation processes and environmental cleanup after accidents, such as the Fukushima Daiichi Nuclear Power Plant disaster in 2011. Nanoporous silicates, such as zeolites, are most commonly used for this process but in addition to acting as selective ion exchange media must also be deployable in a correct physical form for flow columns. Herein, Digital Light Processing (DLP) three-dimensional (3D) printing was utilized to form monoliths from zeolite ion exchange powders that are known to be good for nuclear wastewater treatment. The monoliths comprise 3D porous structures that will selectively remove radionuclides in an engineered form that can be tailored to various sizes and shapes as required for any column system and can even be made with fine-grained powders unsuitable for normal gravity flow column use. 3D-printed monoliths of zeolites chabazite and 4A were made, characterized, and evaluated for their ion exchange capacities for cesium and strontium under static conditions. The 3D-printed monoliths with 50 wt% zeolite loadings exhibit Cs and Sr uptake with an equivalent ion-capacity as their pristine powders. These monoliths retain their porosity, shape and mechanical integrity in aqueous media, providing a great potential for use to not only remove radionuclides from nuclear wastewater, but more widely in other aqueous separation-based applications and processes.

Graphical abstract: Nuclear wastewater decontamination by 3D-Printed hierarchical zeolite monoliths

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Supplementary files

Article information


Submitted
28 Nov 2019
Accepted
27 Jan 2020
First published
05 Feb 2020

This article is Open Access

RSC Adv., 2020,10, 5766-5776
Article type
Paper

Nuclear wastewater decontamination by 3D-Printed hierarchical zeolite monoliths

O. Halevi, T. Chen, P. S. Lee, S. Magdassi and J. A. Hriljac, RSC Adv., 2020, 10, 5766
DOI: 10.1039/C9RA09967K

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