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Georget, Fabien; Schmatz, Joyce; Wellmann, Eva; Matschei, Thomas
Journal of microscopy, 20/May , Letnik: 294, Številka: 2Journal Article
Many methods have been proposed to analyse SEM‐EDS hypermaps of hydrated cementitious materials but none can fit all purposes. In this presentation, we review existing methods for phase identification, stoichiometry quantification, and microstructure quantification in cementitious materials and related materials. We first discuss the unique contribution of SEM‐EDS with respect to the outstanding scientific challenges towards sustainable construction materials. We then compare the SEM‐EDS and image analysis techniques which contribute to answering these challenges. Convergence and divergence in current methods and workflows, and knowledge gaps are highlighted in terms of the specificities of the material (phase assemblage complexity, grain sizes, mixtures, etc.). The discussion is weighted by the required expert knowledge for the sample preparation, microscope operation, and data analysis. We conclude by discussing how microscopy and image analysis integrate into the overall experimental toolkit to investigate and improve cementitious materials. LAY DESCRIPTION Concretes, mortars and hardened cement pastes are very complex and heterogeneous. As such, the visualisation of phases in the microstructure is often necessary to understand the processes by which this microstructure forms and evolves. Scanning electron microscopy coupled with energy dispersive spectroscopy (SEM‐EDS) is one of the techniques that allows studying these materials at the micron‐scale level, by forming images combining the elemental composition. But the analysis of the data is challenging due to the heterogeneity of the material. This article is a review of the latest advancements in the analysis of SEM‐EDS data for cementitious materials. It focuses on two aspects, the most successful applications of SEM‐EDS to study the microstructure of hardened cementitious materials; and some of the main methods used to analyse the dataset. The discussion aims to highlight the requirements of each method and each application, so that readers can pick and mix methods to answer their own scientific questions.
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JCR | SNIP | JCR | SNIP | JCR | SNIP | JCR | SNIP |
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in: SICRIS
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