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@article{203029,
author = {V Srilekha and Dr S Sameem Banu},
title = {Utilization of Cow Dung Ash and Eggshell Powder as Partial Cement Replacement in Concrete},
journal = {International Journal of Innovative Research in Technology},
year = {2026},
volume = {12},
number = {12},
pages = {9598-9609},
issn = {2349-6002},
url = {https://ijirt.org/article?manuscript=203029},
abstract = {The production of cement is associated with significant carbon dioxide emissions, necessitating the development of sustainable alternatives in concrete technology. This study investigates the utilization of cow dung ash (CDA) and eggshell powder (ESP) as partial replacements for ordinary Portland cement (OPC) in concrete. Experimental investigations were conducted on M20 grade concrete by incorporating CDA (2.5–10%) and ESP (2.5–7.5%) in both binary and ternary combinations. The performance of the modified concrete was evaluated in terms of workability, compressive strength, and microstructural characteristics using X-ray diffraction (XRD) analysis. In addition, an artificial neural network (ANN) model was developed to predict compressive strength based on mix composition. The results indicate that workability increases with CDA content, while ESP exhibits a dosage-dependent influence. The optimum performance was achieved for the ternary mix containing 2.5% CDA and 5% ESP, which exhibited higher compressive strength compared to the control mix. XRD analysis confirmed enhanced formation of calcium silicate hydrate (C–S–H) gel and reduced portlandite content, indicating improved microstructural densification. The ANN model demonstrated high prediction accuracy with a strong correlation between experimental and predicted results. The findings suggest that CDA and ESP can be effectively utilized as sustainable supplementary cementitious materials, contributing to improved concrete performance and reduced environmental impact.},
keywords = {Cow dung ash, Eggshell powder, Sustainable concrete, Cement replacement, Compressive strength, X-ray diffraction (XRD), Artificial neural network (ANN), Pozzolanic materials, Microstructural analysis},
month = {May},
}
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