Abstract
Strontium ions can be removed from wastewater in fixed-bed reactors by adsorption on hierarchical materials (different pore sizes and phases). A detailed understanding of the materials multiscale structure is therefore crucial to optimize their sorption properties. This article presents a multi-technique approach developed to characterize the relationship between microstructure and adsorption in a range of Linde-type A (LTA) zeolite-geopolymer composites,. Two-dimensional scanning electron microscopy and 3D X-ray tomography were used to image the porous and solid phases at different length scales. Advanced numerical methods involving machine learning were applied to segment the images and provide quantitative morphological values describing the porous network geometry and the location and accessibility of the zeolite particles in the geopolymer. These results were then correlated with the materials sorption properties, measured in batch and column processes. Increasing the materials zeolite content (from 0 to 27 wt%) slowed down their adsorption kinetics but increased their maximal adsorption capacities from 20 to 49 mg.g−1 and Sr2+-selectivity at equilibrium. In breakthrough experiments, the material with highest zeolite content had a much higher breakthrough volume passing from 169 to 478 ml in the presented experimental conditions (much higher wastewater decontamination capacity), but a shallower breakthrough curve (lower column efficiency).
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