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Breakthrough studies of the adsorption of Cs from freshwater using a mesoporous silica material containing ferrocyanide

•In flow adsorption of Cs using mesoporous silica containing ferrocyanide nanoparticles.•Diffusion in the material is fast enough to allow high flow rate.•Role of the operating parameters: Darcy velocity and column geometry.•A reactive transport model coupling ion diffusion and exchange inside the p...

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Published in:Chemical engineering journal (Lausanne, Switzerland : 1996) Switzerland : 1996), 2018-05, Vol.339, p.288-295
Main Authors: Michel, Caroline, Barré, Yves, Ben Guiza, Mehdi, de Dieuleveult, Caroline, De Windt, Laurent, Grandjean, Agnès
Format: Article
Language:English
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Summary:•In flow adsorption of Cs using mesoporous silica containing ferrocyanide nanoparticles.•Diffusion in the material is fast enough to allow high flow rate.•Role of the operating parameters: Darcy velocity and column geometry.•A reactive transport model coupling ion diffusion and exchange inside the porous adsorbent. The selectivity and fast exchange kinetics of porous silica adsorbents containing Cu or K ferrocyanide make them ideal candidates for the column decontamination of 137Cs effluents. The exchange thermodynamics of the K+ ions in Sorbmatech® (S202, one such adsorbent) with the major cations present in natural (fresh or sea) water have recently been studied in competition with Cs+ sorption to properly model batch data. This article reports an evaluation of this material for continuous, column processes of freshwater decontamination. Experimental data show that its performance is excellent under these conditions, with a steep breakthrough curve of Cs at column exit. The sorption capacity of S202 is completely retained at high flow rates (up to 10 m·h−1 Darcy velocity) and its column behavior remains ideal down to a height/diameter ratio of 2. A reactive transport model accounting for dispersive flow through the bed coupled to ion diffusion and exchange inside the porous adsorbent grains accurately reproduces the experimental data.
ISSN:1385-8947
1873-3212
DOI:10.1016/j.cej.2018.01.101