Multi-site surface complexation modelling of Se(IV) sorption on biotite

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Li , X , Puhakka , E , Liu , L , Zhang , W , Ikonen , J , Lindberg , A & Siitari-Kauppi , M 2020 , ' Multi-site surface complexation modelling of Se(IV) sorption on biotite ' , Chemical Geology , vol. 533 , 119433 .

Title: Multi-site surface complexation modelling of Se(IV) sorption on biotite
Author: Li, Xiaodong; Puhakka, Eini; Liu, Longcheng; Zhang, Wenzhong; Ikonen, Jussi; Lindberg, Antero; Siitari-Kauppi, Marja
Contributor organization: Department of Chemistry
Geological disposal of spent nuclear fuel
Ion exchange for nuclear waste treatment and for recycling
Date: 2020-02-05
Language: eng
Number of pages: 11
Belongs to series: Chemical Geology
ISSN: 0009-2541
Abstract: A surface complexation model of Se(IV) sorption on biotite with one type of strong sorption sites and two types of weak sorption sites were developed based on experimental data obtained from titration, sorption edge and sorption isotherm experiments. Titration data was collected using a batch-wise manner together with back-titration to calibrate the effect of mineral dissolution in 0.01 M KClO4 background electrolytes from pH 3 to 11 in an inert atmosphere glovebox. Further calibrations of the titration curve include proton exchange and cation exchange in which the calculations of cation occupancies on biotite surfaces were taken into account. The sorption edge measurements were determined by measuring the sorption of 10(-9) M total Se with a radioactive Se-75 tracer on converted biotite in 0.01 M KClO4 solution from pH 3 to 11. Se sorption was observed to be strongly dependent on pH. Surface complexation modelling was performed by deriving a set of optimized parameters that can fit titration, sorption edge and sorption isotherm (at pH similar to 7.7) experimental data. A CASTEP code implemented into Materials Studio was used to calculate the site densities and site types on the biotite surfaces. Weak sorption sites with site densities of 3.2 sites/nm(2) and 1.4 sites/nm(2) were derived from the codes and used in the sorption model. A computer code that coupled PHREEQC with Python was developed for the fitting and optimizing processes. The model was validated by sorption data at pH similar to 9.5. The results show that the model can provide quantitative predicts of Se(IV) sorption in groundwater conditions of a deep geological repository and help improve the performance assessments by giving more convincing estimates of the release of radionuclides towards aquifers and biosphere.
Subject: Se(IV)
Surface complexation modelling
1171 Geosciences
116 Chemical sciences
Peer reviewed: Yes
Rights: cc_by
Usage restriction: openAccess
Self-archived version: publishedVersion

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