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Thermodynamic Modeling of Portland Cement—Metakaolin—Limestone Blends

  • Wolfgang KuntherEmail author
  • Zhuo Dai
  • Jørgen Skibsted
Conference paper
Part of the RILEM Bookseries book series (RILEM, volume 10)

Abstract

The partial replacement of Portland cement by different supplementary cementitious materials (SCM´s) has been investigated extensively in recent years with the aim of reducing the embodied CO2 of blended Portland cements. In this work, we have utilized the maximum cement substitution of 35 wt%, according to the standard EN 197-1, and investigated the effect of changing the metakaolin/limestone ratio on the hydrating phase assemblages. Paste samples of the hydrated cement blends have been characterized by XRD, 27Al and 29Si MAS NMR spectroscopy and the results are compared with thermodynamic modeling. 29Si MAS NMR is a very valuable technique for studies of hydrated cement blends, since it allows detection of amorphous and crystalline phases in an equal manner. The determined degrees of hydration have been implemented into thermodynamic modeling to improve the modeling approach and thereby the agreement between predicted and observed phase assemblages. A simple equation has been established for implementation of the hydration kinetics which employs only one mass and one dissolution-rate parameter to describe the hydration successfully. The agreement between the experimental and modeled phase assemblages improves significantly when the hydration kinetics for the anhydrous alite, belite, and amorphous MK phases are implemented. The phase assemblages of the hydrated blends change only for very high MK contents from a C(-A)-S-H, calcite, portlandite, monocarbonate and ettringite system to a phase assemblage that in addition contains strätlingite and other AFm phases.

Keywords

Portland Cement Thermodynamic Modeling Phase Assemblage Supplementary Cementitious Material Hydration Kinetic 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Notes

Acknowledgment

The Danish National Advanced Technology Foundation is acknowledged for financial support to the SCM project.

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Copyright information

© RILEM 2015

Authors and Affiliations

  1. 1.Department of Chemistry and Interdisciplinary Nanoscience Center (iNANO)Aarhus UniversityAarhus CDenmark

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