Surface Complexation Modeling Of The Effects Of Dissolved Inorganic Carbon On Adsorption Of U(Vi) Onto Fe3o4 Nanoparticles Coated With Lignite Humic Acid

COLLOIDS AND SURFACES A-PHYSICOCHEMICAL AND ENGINEERING ASPECTS(2021)

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摘要
Lignite humic acid (LHA) surface-functionalized magnetite nanoparticles (NPs) represent a promising sorbent for removal of U(VI) from industrial waste streams and contaminated environmental waters, but the effects of dissolved inorganic carbon (DIC) on the adsorption mechanisms and efficiency are poorly constrained. We measured the adsorption of U(VI) onto LHA-coated Fe3O4 NPs as a function of pH, ionic strength, adsorbent concentration, DIC concentration and dissolved calcium concentration. The observed U(VI) adsorption onto LHAcoated Fe3O4 NPs is ionic strength independent, and below pH 5, the extent of U(VI) adsorption increases with increasing pH and adsorbent concentration. The extent of U(VI) adsorption decreases dramatically with increasing concentration of added NaHCO3 and CaCl2 above pH 5 and pH 6 respectively. The adsorption data were modeled using a non-electrostatic surface complexation modeling approach to determine the identities and thermodynamic stabilities of possible uranyl complexes on the LHA-coated Fe3O4 NP surfaces. The modeling results indicate that L-1-(UO2)(+), >L-2-UO2(OH), >L-2-(UO2)(3)(OH)(5), >L-2-UO2(CO3)-, >L-3-(UO2)(2)(CO3)(OH)(3)(2-), >L4UO2(CO3)(2)(3-) and >L-4-(UO2)(3)(OH)(7)(2-) are involved in the adsorption under different pH (3.0-9.5) and DIC (0-25 mM) concentration conditions. The log stability constant values (+/- 2s) of these uranyl surface complexes are calculated as 4.59(+/- 0.12), 6.59(+/- 0.14), 6.33(+/- 0.13), 6.08(+/- 0.18), 6.16(+/- 0.06), 7.07(+/- 0.19) and6.13(+/- 0.15). The model can be applied to predict the distribution of U(VI) in complex LHA-coated Fe3O4 NP-bearing systems under a wide range of pH, ionic strength, DIC, and solute: sorbent conditions.
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关键词
Uranium, Adsorption, Lignite humic acid, Dissolved inorganic carbon, Surface complexation modeling
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