Abstract
In the experimental investigation, to analyse the effect of the superplasticiser on the GPC mechanical properties; it includes the compressive strength, flexural strength, splitting strength and MOE of the GPC. Superplasticizers used for reducing the water content from the mix design of the concrete, reduction in water content enlarges the strength of the concrete. GPC is an innovative, eco-friendly, cementless and durable concrete in which cement content replace by the pozzolanic content that is full of silica and alumina mineral constituent. GPC indirectly reduces the carbon footprints by the whole replacement of the cement because, in the production of cement, much amount of carbon dioxide emitted in the environment. After the comprehensive survey, the references conclude that the best superplasticiser for the GPC are SNF based because the comprehensive survey authors define the PCE based superplasticisers increases the workability of the GPC but the reduction of the strength at a very high level. So, in the experimental study, to analyse the different dosage of the SNF based superplasticiser in the GPC mix designs for the physical, mechanical properties, microstructural properties and thermal analysis of the specimens. The M2 mix got the optimum point of strength at 1% dosage of superplasticiser in the GPC mix design. It’s increasing the workability with the enhancement of the strength in the mixes of GPC. The mix design specimens show higher thermal stability at the elevated temperature.
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Acknowledgements
This work supported by the Civil Engineering Department, Delhi Technological University. Moreover, the help of Sandeep Mishra for XRD analysis and Ankesh Kumar and Jawed Alam for the another in the work that is related to the central instrumentation facility of the Delhi Technological University.
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This study was funded by the Delhi Technological University, Delhi, India.
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Verma, M., Dev, N. Effect of SNF-Based Superplasticizer on Physical, Mechanical and Thermal Properties of the Geopolymer Concrete. Silicon 14, 965–975 (2022). https://doi.org/10.1007/s12633-020-00840-4
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DOI: https://doi.org/10.1007/s12633-020-00840-4