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Metal removal from aqueous solutions: insights from modeling precipitation titration curves

[Display omitted] •Focus on process of metal ion removal rather than outcome•The analytical model exposes important parameters during metal ion removal•The initial pH, metal ion concentration and - valence are key parameters•The PHREEQC model exposes the analytical model's strengths and limitat...

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Published in:Journal of environmental chemical engineering 2020-02, Vol.8 (1), p.103596, Article 103596
Main Authors: Eggermont, Sam G.F., Prato, Rafael, Dominguez-Benetton, Xochitl, Fransaer, Jan
Format: Article
Language:English
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Summary:[Display omitted] •Focus on process of metal ion removal rather than outcome•The analytical model exposes important parameters during metal ion removal•The initial pH, metal ion concentration and - valence are key parameters•The PHREEQC model exposes the analytical model's strengths and limitations•Both models can act as a reference for a large variety of metal ion waste streams To provide a good reference for many metal ion removal processes, we developed an analytical model (AM) and used the PHREEQC computer program to numerically model (NM) arbitrary metal hydroxide precipitation titration curves (PTCs). For validation, these models were compared to slow titration experiments of ZnCl2 with NaOH to precipitate Zn(OH)2. The AM effectively demonstrates how initial pH, metal ion concentration and - valence and metal hydroxide equilibrium constant affect the shape of the PTCs. Comparison of AM and NM exposed AM limitations that include the effect of NaCl concentration, activity coefficients, and multi-species ions, on the shape of the PTCs. The experimental results agree well with either model for different concentrations of ZnCl2 at slow titration rates. However, the models and experiments deviated at higher titration rates. These deviations were attributed to inhomogeneities in the solution concentration, which caused precipitation at a bulk pH below the theoretical precipitation pH (i.e., pre-precipitation).
ISSN:2213-3437
2213-3437
DOI:10.1016/j.jece.2019.103596