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Articles

Investigation on the microstructure of a 3D-printed mortar through a novel leaching-subsidiary tomography

, , , , , , & show all
Pages 818-831 | Published online: 06 Mar 2023
 

Abstract

The microstructure of a 3D-printed mortar was investigated in present study. To enhance the density contrast between sand and cementitious slurry, a novel leaching strategy was used as an auxiliary method, based on which the spatial dispersion of sands in 3D-printed mortar was rendered. Meanwhile, to alleviate the problem of CT’s limited resolution, X-ray attenuation method (XRAM) was introduced in this study to investigate the spatial distribution of local porosity in 3D-printed mortar. Besides, focusing on single filaments, the upper part of the filaments presented lower sand rate and higher porosity than the lower part, and the difference between the filaments located near the top of 3D-printed mortar was more significant. Finally, based on the sliding method, the interlayer width, average porosity and average sand ratio of 3D-printed mortar were estimated as 640 μm, 21.9% and 43.1%, respectively. The research results would deepen the understanding of 3D-printed concrete.

Authors’ contributions

Conceptualization, D.C. and YX.W.; methodology, X.X., G.H. and G.T.; investigation, D.C. X.X, K.Z. and W.L.; validation, K.Z., G.T. and YX.W.; writing—original draft preparation, D.C. and YX.W.; writing—review and editing, K.Z. and W.L.; visualization, WT.L. and Y.W.; funding acquisition, D.C, WT.L. and Y. W.; supervision, WT.L. and K. Z. All authors have read and agreed to the published version of the manuscript.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This research was funded by the National Natural Science Foundation of China (Grant number: 52008210, 12004182, 51878481), Jiangsu Province Science Foundation (Grant number: BK20200481) and Fundamental Research Fund for the Central Universities (Grant number: 30920021146). Undergraduate scientific research training program from Nanjing University of Science and Technology (Grant number: S202210288089).

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