Integrating Backscattered Electron Imaging and Multi-Feature-Weighted Clustering for Quantification of Hydrated C<sub>3</sub>S Microstructure

Integrating Backscattered Electron Imaging and Multi-Feature-Weighted Clustering for Quantification of Hydrated C<sub>3</sub>S Microstructure

The microstructure of cement paste is governed by the hydration of its major component, tricalcium silicate (C<sub>3</sub>S). Quantitative analysis of C<sub>3</sub>S microstructural images is critical for elucidating the microstructure-property correlation in cementitious sys...

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Bibliographic Details
Main Authors: Xin Wang, Yongjun Luo
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Buildings
Subjects:
tricalcium silicate hydration
microstructure analysis
K-means clustering
backscattered electron imaging
denoising method
Online Access:https://www.mdpi.com/2075-5309/15/10/1699
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Summary:The microstructure of cement paste is governed by the hydration of its major component, tricalcium silicate (C<sub>3</sub>S). Quantitative analysis of C<sub>3</sub>S microstructural images is critical for elucidating the microstructure-property correlation in cementitious systems. Existing image segmentation methods rely on image contrast, leading to a struggle with multi-phase segmentation in regions with close grayscale intensities. Therefore, this study proposes a weighted K-means clustering method that integrates intensity gradients, texture variations, and spatial coordinates for the quantitative analysis of hydrated C<sub>3</sub>S microstructure. The results indicate the following: (1) The deep convolutional neural network with guided filtering demonstrates superior performance (mean squared error: 53.52; peak signal-to-noise ratio: 26.35 dB; structural similarity index: 0.8187), enabling high-fidelity preservation of cementitious phases. In contrast, wavelet denoising is effective for pore network analysis but results in partial loss of solid phase information. (2) Unhydrated C<sub>3</sub>S reflects optimal boundary clarity at intermediate image relative resolutions (0.25–0.56), while calcium hydroxide peaks at 0.19. (3) Silhouette coefficients (0.70–0.84) validate the robustness of weighted K-means clustering, and the Clark–Evans index (0.426) indicates CH aggregation around hydration centers, contrasting with the random CH distribution observed in Portland cement systems.
ISSN:2075-5309

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