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FA-GGBFS based geopolymer concrete incorporating CMRW and SS as fine and coarse aggregates

  • Aman Deep , Nikhil P. Zade and Pradip Sarkar ORCID logo EMAIL logo
Published/Copyright: December 19, 2024
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Abstract

Geopolymer concrete, which utilizes aluminosilicate precursor materials such as metakaolin, volcanic ash, industrial solid waste including fly ash and ground granulated blast furnace slag as a binder, is an eco-friendly alternative to Portland cement concrete. Although geopolymer concrete does not use cement, it still has shortcomings in terms of environmental friendliness because the aggregates (fine and coarse) used to prepare geopolymer concrete are natural resources and their excessive use in concrete manufacturing leads to natural resource depletion. In view of this, several researchers have tried to replace natural aggregates with various waste materials, which not only conserves natural resources but also helps in waste management. In the present study, the potential of steel slag and coal mine rock waste as a substitute for coarse and fine aggregates in geopolymer concrete to make it truly green is experimentally evaluated. The use of steel slag and coal mine rock waste as coarse and fine aggregates in geopolymer concrete was observed to significantly improve its strength and durability properties compared to fly ash based geopolymer concrete.


Corresponding author: Pradip Sarkar, Department of Civil Engineering, National Institute of Technology, Rourkela, 769008 Odisha, India, E-mail:

  1. Research ethics: Not applicable.

  2. Informed consent: Not applicable.

  3. Author contributions: The authors have accepted responsibility for the entire content of this manuscript and approved its submission. Detailed information about an individual author’s contribution is as follows: Aman Deep: Writing – original draft, Visualization, Methodology, investigation, Formal analysis, Data curation, Conceptualization. Nikhil P. Zade: Writing – original draft, Visualization, Supervision. Pradip Sarkar: Writing – original draft, Writing – review & editing Supervision, Conceptualization.

  4. Use of Large Language Models, AI and Machine Learning Tools: None declared.

  5. Conflict of interest: All other authors state no conflict of interest.

  6. Research funding: None declared.

  7. Data availability: The raw data can be obtained on request from the corresponding author.

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Received: 2024-02-01
Accepted: 2024-11-19
Published Online: 2024-12-19
Published in Print: 2024-11-26

© 2024 Walter de Gruyter GmbH, Berlin/Boston

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