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Cited by 520

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Experimental study on mix proportion and fresh properties of fly ash based geopolymer for 3D concrete printing

Open access
Panda, Biranchi, Tan, Ming Jen·2018·Ceramics International

Abstract

Abstract This paper presents the material design and fresh properties of geopolymer mortar developed for 3D concrete printing application. Unlike traditional casting, in 3D printing, extruded materials are deposited layer-by-layer to build complex architectural and structural components without the need of any formwork and human intervention. Extrudability, shape retention, buildability and thixotropic open time (TOT) are identified as critical early-age properties to characterize the 3D printable geopolymer material. Five different mix designs of geopolymer are tested in a systematic experimental approach to obtain a best printable mix and later it is used to print a 60-centimeter-tall freeform structure using a concrete gantry printer to validate the formulation.

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Crossref · 10.1016/j.ceramint.2018.03.031

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Metadata

Authors
Panda, B., & Tan, M. J.
Venue
Ceramics International
Publisher
Elsevier BV
Published
2018-06
Volume
44
Issue
9
Pages
10258-10265
ISSN
0272-8842 (ISSN-L)
OpenAlex
W2790480906
Cited by
520
References
1
FWCI
36.58
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Experimental study on mix proportion and fresh properties of fly ash based geopolymer for 3D concrete printing. https://app.cochat.ai/papers/10.1016/j.ceramint.2018.03.031
The paper
Panda, B., & Tan, M. J. (2018). Experimental study on mix proportion and fresh properties of fly ash based geopolymer for 3D concrete printing. Ceramics International. https://doi.org/10.1016/j.ceramint.2018.03.031

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.