The particle size distribution (PSD) has a significant influence on the fresh and final properties of cement and its derived products. In this paper, CSA cements with three different mean diameters (D₅₀), ranging from 6.04 to 26.62 μm were prepared by milling. The pre-hydration behavior was quantitatively analyzed, including the degree of pre-hydration, the dynamic change of mineral assemblage and the morphology of the prepared CSA cement exposed to 57%, 75% and 97% relative humidities (RHs) for up to 90 days. Hydration kinetics, porosity, and compressive strength of the cement paste made with fresh and pre-hydrated CSA cement with different PSD were also characterized. The results show that pre-hydration of CSA cement at RH higher than 75% has detrimental effects on the hydraulic activity and strength gain of CSA cement. However, coarser CSA cement (D₅₀ = 26.62 μm) does not only show better resistance to pre-hydration, but also higher compressive strength and lower porosity.

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This paper employs computer vision techniques to predict the micromechanical properties (i.e., elastic modulus and hardness) of cement paste based on an input of Backscattered Electron (BSE) images. A dataset comprising 40,000 nanoindentation tests and 40,000 BSE micrographs was built by express nanoindentation test and Scanning Electron Microscopy (SEM). A Residual Convolutional Neural Network (Res-Net) model, which differs from a typical Convolutional Neural Network (CNN) architecture by a shortcut connection, was employed and compared with a simple table model. The models were trained, tuned, and tested over a training, validation and testing set comprising 70%, 15% and 15% of the 40,000 data pairs, respectively. The following conclusions were drawn: 1) Express nanoindentation tests can provide reliable information for cement paste. Deconvolution based on Gaussian Mixture Model (GMM) can obtain almost invariant statistics for each phase; 2) Based on averaged greyscale values of each BSE image, a table model can predict the elastic modulus and hardness with R² of 0.80 and 0.83, respectively; 3) Based on the intensity of each pixel as well as their patterns in each BSE image, the Res-Net model can predict the elastic modulus and hardness with a R² of 0.85 and 0.88, respectively. Deconvolution of the Res-Net prediction obtains similar invariant statistics as derived by the nanoindentation tests, which gives strong evidence of the applicability of the Res-Net model.

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This paper presents a research on the chloride penetration behavior of engineered cementitious composites (ECC) under sustained flexural loads. Three load levels, i.e. 30 %, 60 % and 75 % of the ultimate flexural load were used. Chloride diffusion depth and concentration profile were measured 30, 60 and 150 days after the specimen was exposed to NaCl solution and compared with pre-loaded specimens. Influence of the sustained local bending stress and microcracks were investigated. It shows that under sustained loads, the relationship between the surface chloride content and maximum normal tensile stress can be described using an exponential equation. A binary model was developed to explain the correlation among the chloride ion diffusion coefficient, maximum normal tensile stress and exposure time. Changes of capillary pore structure and phase compositions were measured using mercury intrusion porosimeter and X-ray diffraction, respectively. Unlike mortar, the fiber bridging of ECC helps with limiting crack width and thus the diffusion process, and the measured results were used to explain the observed penetration behavior of ECC. It is believed that the current study provides theoretical foundation for the durable design of the ECC/concrete composite structure.

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White mud is a solid waste from the papermaking industry, composed mainly of CaCO₃ and residual alkali metal ions (such as Na+, Mg²⁺). In the current study, the feasibility of using white mud as partial replacement of slag in alkali activated materials is explored. The fluidity, setting time, autogenous shrinkage, mechanical properties, hydration products and microstructure of alkali activated slag containing different amount of white mud are studied. The results show that adding white mud reduces the fluidity of freshly mixed paste, setting time and autogenous shrinkage. The ions released from the white mud participate in the polymerization reaction, accelerate the hydration reaction in the early stage, and promotes the precipitation of Mg-Al and the formation of hydrotalcite. However, excessive quantities of white mud (above 15% of the binder) leads to the reduction of compressive strength. As the content of white mud is enhanced, the Ca/(Si + Al) ratio of the gel increases and the degree of polymerization is reduced. It has been shown that white mud has potential reactivity and can partially replace slag to prepare new alkali activated materials.

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Micro-cubes of hardened cement paste with the lengths of 100 μm and 200 μm were prepared by micro-dicing and thin-sectioning techniques. The compressive strength and splitting strength of these specimens were measured by a nanoindenter equipped with different types of tips. Considering the heterogeneity nature of the material in a micro-scale, we examined 100 specimens via a statistic analysis. The results show that the two-parameter Weibull distribution can be used to represent the probability distribution of both compressive strength and splitting strength in a micro-scale. The specimens with a higher water-to-binder ratio have a higher strength and a lower variability. Furthermore, the specimen size has an influence on the measured strength. The bigger specimens have lower strength and variability. The reported average value and variability of strengths obtained in this work are greater than those of the concrete in a meso-scale, but lower than those of the hydration product in a nano-scale.@en

A combination of laboratory experiments and numerical simulations at multiple length scales can provide in-depth understanding of fracture behaviour of hydrated cement paste (HCP). To that end, the current work presents a numerical study on compressive failure of hydrated cement paste (HCP) at the micro-scale. Virtual specimens consisting of various phases were obtained using a combination of X-ray computed tomography and image segmentation techniques. The discrete lattice fracture model was used for the deformation and fracture analysis of the specimens subjected to uniaxial compression. The input local mechanical properties of each individual phase were taken from the literature in which a micro-scale compression test was conducted for the calibration of the same type model. The influence of slenderness ratios (1 and 2), water-to-cement ratios (0.3, 0.4 and 0.5 respectively) and lateral confinement of the specimen ends (free and restricted) on the failure behaviour were investigated. It has been shown by the current study that the stress–strain response cannot be completely separated from the used boundary conditions. The proposed model provides an effective tool to understand the compressive fracture behaviour of cement paste at the micro-scale.@en