Abstract

Core Ideas Sb(V) adsorption by kaolinite is pH and ionic strength dependent, with adsorption decreasing with increasing pH and ionic strength. Sb(V) adsorption is hysteretic in acidic systems, but reversible in alkaline. Adsorbed Sb(V) generates a downward shift in the isoelectric point and an upward shift in the point of zero net proton charge. Phosphate decreases Sb(V) adsorption, but the influence of sulfate is minimal. The macroscopic findings indicate that Sb(V) is retained by innersphere in acidic and outersphere in neutral to alkaline systems. The environmental fate and behavior of antimony (Sb) is controlled by adsorption processes at the solid–solution interface of surface‐reactive solids. One such solid is kaolinite, which bears the aluminol (≡AlOH) surface functional group. The objectives of this study are to characterize antimonate [Sb(V) in the Sb(OH)6– species] adsorption by kaolinite as a function of pH, ionic environment, and competing ligands (PO4 and SO4); to describe the reversibility of the adsorption and the influence of adsorbed Sb(V) on the surficial properties of kaolinite; and to develop predictive surface complexation models. The results of this study show adsorbed Sb(V) is at a maximum in strongly acidic suspensions, and retention decreases with increasing pH and ionic strength. Adsorption is hysteretic in pH < 5 suspensions, becoming reversible with increasing pH. The point of zero net proton charge (PZNPC) increases from 4.5 in KNO3 to 5.6 in KSb(OH)6. Correspondingly, the isoelectric point decreases from 4.5 in KNO3 to <3 in KSb(OH)6. The macroscopic findings indicate that Sb(V) is retained by a combination of inner and outersphere mechanisms, with the former dominating in acidic suspensions. The inclusion of SO4 had little impact on the retention of Sb(V); however, PO4 reduced Sb(V) retention. The inclusion of both inner‐ and outersphere complexes in the triple layer surface complexation model (TLM) provided an adequate description of the Sb(V) adsorption envelopes. Further, the TLM successfully predicted ligand retention in competitive systems without re‐optimization.

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