Reverse Monte Carlo modeling of metakaolin and metakaolin- based geopolymer
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Abstract (EN)
A metakaolin-based geopolymer with an approximate composition of NaAlSi2O6.5.5H2O is synthesized by mixing metakaolin powder with a Na2Si3O7/NaOH solution at ambient conditions. High-energy x-ray diffraction data are collected for kaolinite, metakaolin and the geopolymer at the Advanced Photon Source (APS) in Argonne National Laboratory. The data is initially used to study the structural changes during dehydroxylation of kaolinite to metakaolin. The radial distribution functions show that the nearest-neighbor Al coordination environment changes from ochahedral to mainly tetrahedral form with calcination. Reverse Monte Carlo (RMC) modeling is employed to generate realistic three-dimensional models of metakaolin and geopolymer systems based on experimental high-energy x-ray diffraction data. The RMC model of metakaolin indicated that the Al and Si layers in the kaolinite structure is somewhat preserved after dehydroxylation, although greatly distorted. The interlayer distance between Al and Si layers in metakaolin is found to be 3.1 Å. RMC model of the geopolymer, on the other hand, resulted in a three-dimensional structure consisting of randomly cross-linked AlO4 and SiO4 tetrahedral units. The bond angle distributions obtained from this model is found to be comparable to leucite mineral. A ring size distribution analysis performed on the system revealed that intermediate-range order in NaAlSi2O6.5.5H2O geopolymer system mainly consist of 7 and 8 membered rings together with considerable amount of 6 membered rings. When the results for the geopolymer model are compared to those for minerals that are considered as analogs to geopolymer structure, namely leucite, nepheline and analcime, it is seen that a much wider variety of ring sizes exists in geopolymer structure compared to these minerals.
Author
Serhat Arca
How to Cite
Serhat Arca (Master Thesis). Reverse Monte Carlo modeling of metakaolin and metakaolin- based geopolymer, 2016, Boğaziçi University.
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