Direct observation of C3S particle dissolution using fast nano X-ray computed tomography

Li, Xiaodan; Hu, Qinang; Robertson, Bret; Ley, M. Tyler; Andrade, Vincent Joseph De; Sokhansefat, Ghazal

doi:10.1016/j.cemconres.2023.107097

Cited by 11 publications

(5 citation statements)

References 58 publications

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“…On the one hand, the spatial resolution can be determined by the edge sharpness across selected interfaces. A point spread function (PSF) used to determine the spatial resolution of the images as ISO/TS 24597 defines the Gaussian radius of the PSF as the resolution, which equals a change between 25%–75% grey value along the studied interfaces 38 . The spatial resolutions, determined by this approach, were 250(25) nm, 264(25) nm, 272(34) nm, 748(19) nm and 2.21(17) μm, for PXCT-19h, PXCT-47h, PXCT-93h, Syn-μCT and Lab-μCT datasets, respectively.…”

Section: Resultsmentioning

confidence: 99%

“…Moreover, μCT is being widely used 23 and in particular to follow in situ 4D (3D + time) some specific features of cement hydration 24 – 33 . In the last three years, important advances have been reported including: i) the automated correction for the movement of suspended particles at very early ages 34 which allowed to follow in situ PC hydration after water mixing 35 ; ii) to follow the fast dissolution of plaster and the precipitation of gypsum 36 ; iii) the simultaneous use of neutron and laboratory X-ray tomographies for in situ studying the microstructural changes of PC mortars on moderate heating 37 ; and iv) the measurement of alite particle dissolution using fast synchrotron nano X-ray computed tomography 38 , 39 . However, none of these 4D imaging works combine the stringent four requirements needed for carrying out relevant contributions to the understanding of the mechanism(s) of Portland cement hydration at early ages: (i) water to cement mass ratio (w/c) close to 0.50, (ii) submicrometer spatial resolution, (iii) good contrast to be able to identify the different evolving components (more than eight), and (iv) relatively large scanned volume to allow hydration to progress with appropriate particle sampling, the particle sizes of commercial PCs have D v,50 ∈10-20 μm.…”

Section: Introductionmentioning

confidence: 99%

“…However, none of these 4D imaging works combine the stringent four requirements needed for carrying out relevant contributions to the understanding of the mechanism(s) of Portland cement hydration at early ages: (i) water to cement mass ratio (w/c) close to 0.50, (ii) submicrometer spatial resolution, (iii) good contrast to be able to identify the different evolving components (more than eight), and (iv) relatively large scanned volume to allow hydration to progress with appropriate particle sampling, the particle sizes of commercial PCs have D v,50 ∈10-20 μm. In particular, hard X-ray synchrotron microtomography has not the required submicrometer spatial resolution neither sufficient component contrast 35 , 40 , hard X-ray synchrotron nanotomography has not the required contrast between the components to be able to classify the hydrates 38 , 39 and soft X-ray synchrotron nanotomography has the contrast but it requires very large w/c ratios and very small fields of view which does not allow the hydrates to growth in relevant condition (i.e. confined space with low water-cement ratios) 32 .…”

Section: Introductionmentioning

confidence: 99%

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4D nanoimaging of early age cement hydration

et al. 2023

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Despite a century of research, our understanding of cement dissolution and precipitation processes at early ages is very limited. This is due to the lack of methods that can image these processes with enough spatial resolution, contrast and field of view. Here, we adapt near-field ptychographic nanotomography to in situ visualise the hydration of commercial Portland cement in a record-thick capillary. At 19 h, porous C-S-H gel shell, thickness of 500 nm, covers every alite grain enclosing a water gap. The spatial dissolution rate of small alite grains in the acceleration period, ∼100 nm/h, is approximately four times faster than that of large alite grains in the deceleration stage, ∼25 nm/h. Etch-pit development has also been mapped out. This work is complemented by laboratory and synchrotron microtomographies, allowing to measure the particle size distributions with time. 4D nanoimaging will allow mechanistically study dissolution-precipitation processes including the roles of accelerators and superplasticizers.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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4D nanoimaging of early age cement hydration

et al. 2023

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“…The spatial resolution was estimated by employing edge sharpness across interfaces. According to ISO/TS 24597 (Donnelly et al, 2020), the resolution is defined as the Gaussian radius of the point spread function, which is the change between 25 and 75% grey value across the studied sharp interface (Donnelly et al, 2020;Li et al, 2023;Shirani et al, 2023). This method, applied to the air/capillary outer wall boundary, gave 2.2 (3) mm from six measurements in three different capillaries.…”

Section: In Situ Mct Studymentioning

confidence: 99%

Mix and measure II: joint high-energy laboratory powder diffraction and microtomography for cement hydration studies

Fernandez-Sanchez,

Cuesta,

Shirani

et al. 2024

J Appl Crystallogr

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Portland cements (PCs) and cement blends are multiphase materials of different fineness, and quantitatively analysing their hydration pathways is very challenging. The dissolution (hydration) of the initial crystalline and amorphous phases must be determined, as well as the formation of labile (such as ettringite), reactive (such as portlandite) and amorphous (such as calcium silicate hydrate gel) components. The microstructural changes with hydration time must also be mapped out. To address this robustly and accurately, an innovative approach is being developed based on in situ measurements of pastes without any sample conditioning. Data are sequentially acquired by Mo Kα1 laboratory X-ray powder diffraction (LXRPD) and microtomography (µCT), where the same volume is scanned with time to reduce variability. Wide capillaries (2 mm in diameter) are key to avoid artefacts, e.g. self-desiccation, and to have excellent particle averaging. This methodology is tested in three cement paste samples: (i) a commercial PC 52.5 R, (ii) a blend of 80 wt% of this PC and 20 wt% quartz, to simulate an addition of supplementary cementitious materials, and (iii) a blend of 80 wt% PC and 20 wt% limestone, to simulate a limestone Portland cement. LXRPD data are acquired at 3 h and 1, 3, 7 and 28 days, and µCT data are collected at 12 h and 1, 3, 7 and 28 days. Later age data can also be easily acquired. In this methodology, the amounts of the crystalline phases are directly obtained from Rietveld analysis and the amorphous phase contents are obtained from mass-balance calculations. From the µCT study, and within the attained spatial resolution, three components (porosity, hydrated products and unhydrated cement particles) are determined. The analyses quantitatively demonstrate the filler effect of quartz and limestone in the hydration of alite and the calcium aluminate phases. Further hydration details are discussed.

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“…In contemporary geotechnical engineering, various advanced 3D imaging methods [16], such as X-ray computed tomography (X-ray CT) [17][18][19][20], laser scanning [21], stereophotography [22], and structured light techniques [16], have overcome the challenge of capturing complex 3D particle geometries. Jia extended Wadell's 2D definition of angularity and sphericity to propose a 3D definition [11].…”

Section: Introductionmentioning

confidence: 99%

Three-dimensional sand particle shape characterization by PointConv-Transformer deep learning

Xi,

Zheng,

Gao

et al. 2024

Preprint

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Angularity and sphericity of sand particles significantly influence the shear strength, compressibility, void structure, and deformation behavior of soils. However, current computational geometry (CG) algorithms face challenges in simultaneously charactering angularity and sphericity, as well as handling defective granular three-dimensional(3D) mesh. To address these efficiency and robustness limitations, this paper introduces the PointConv-Transformer deep learning algorithm for characterization and classification of sand particles point cloud. The PointConv efficiently captures local features of angularity and sphericity. Subsequently, the Transformer integrates these local features into global features to form the judgement basis for classification. The 4800 particle point clouds are labeled with 12 angularity-sphericity classes. The PointConv-Transformer model, trained on the produced dataset, achieves an automatic classification accuracy of 96.65%. Furthermore, we explore the impact of normal vectors and point cloud size on the performance of the PointConv-Transformer model. Experimental results demonstrate that the optimal performance of the trained model is achieved when the point cloud size is 2000 and includes normal vectors. Finally, compared to traditional 3D CG, the classification results align closely in volume, surface area, and convex hull volume metrics. As the number of classified particles increases, the advantage in classification efficiency becomes more pronounced.

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Direct observation of C3S particle dissolution using fast nano X-ray computed tomography

Cited by 11 publications

References 58 publications

4D nanoimaging of early age cement hydration

4D nanoimaging of early age cement hydration

Mix and measure II: joint high-energy laboratory powder diffraction and microtomography for cement hydration studies

Three-dimensional sand particle shape characterization by PointConv-Transformer deep learning

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