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Influence of structural Al and Si vacancies on the interaction of kaolinite basal surfaces with alkali cations: A molecular dynamics study.

Authors :
Naderi Khorshidi, Zeinab
Tan, Xiaoli
Liu, Qi
Choi, Phillip
Source :
Computational Materials Science. Dec2017, Vol. 140, p267-274. 8p.
Publication Year :
2017

Abstract

Point defects, particularly vacancies, exist abundantly in the structure of a variety of clay minerals (e.g., kaolinite). Such defects significantly alter the physical/chemical characteristics of the minerals. Dissolution of kaolinite in an alkali medium is a critical step in the geopolymerization process and it determines the properties of the final product. In this work, a series of molecular dynamics (MD) simulations were carried out in the isothermal-isobaric (NPT) ensemble at 298 K and 1 atm to study the influence of structural vacancies (Al and Si vacancies in particular) on the interaction/dissolution of the two basal surfaces of kaolinite (partially deprotonated octahedral and tetrahedral surfaces) exposed to alkali media. Two different alkali media were used. One contained sodium cation (Na + ) only while the other potassium cation (K + ) and their concentrations were 3 M and 5 M. The MD results showed that regardless of the type of cation and cation concentration, Al vacancies on the octahedral surface promoted the dissolution of Al into the solution compared to the surface without Al vacancies. However, there existed a vacancy concentration (2 Al vacancies per 576 Al atoms) at which the dissolution amount was the maximum and above which the dissolution decreased with increasing Al vacancy concentration. The presence of Si vacancies in the tetrahedral surface did not show significant effect on the dissociation of Si. Radial distribution function (RDF) analyses indicated that the degree of crystallinity of the octahedral surface decreased as the number of Al vacancies increased but this was not the case for the tetrahedral surface. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09270256
Volume :
140
Database :
Academic Search Index
Journal :
Computational Materials Science
Publication Type :
Academic Journal
Accession number :
125546186
Full Text :
https://doi.org/10.1016/j.commatsci.2017.09.004