Response Surface Model for Predicting the Compressive Strength of Metakaolin Geopolymer Concrete

This paper focuses on developing a response surface model (RSM) to predict and optimize the compressive strength of Metakaolin-based Geopolymer Concrete (MKGPC). The materials used include metakaolin (MK) as the precursor, granite, river sand, and an activator solution consisting of sodium hydroxide and sodium silicate. The mix design was created using the face-centered central composite design of RSM. Key factors influencing strength included the alkali activator-MK ratio, sodium silicate to sodium hydroxide ratio, sodium hydroxide concentration, curing time and curing temperature. The optimization of compressive strength was performed with RSM with desirability function. Experimental results revealed significant variations in compressive strength, ranging from 11.31 MPa to 19.67 MPa, with a 73.92% difference across the trials. Some mixtures achieved strengths over 17 MPa, indicating MKGPC's potential for lightweight construction. The RSM model developed for compressive strength prediction showed a high R² value of 89.98%, reflecting its accuracy in capturing the influence of mix parameters. The optimization process determined the ideal conditions for maximum compressive strength: an activator-to-metakaolin ratio of 0.2, a sodium silicate-to-sodium hydroxide ratio of 2.05, a sodium hydroxide concentration of 11.15, a curing time of 66.51 hours, and a curing temperature of 100.61°C, yielding a compressive strength of 19.44 MPa and a desirability function value of 97.32%. The results emphasize the importance of careful mix design and curing conditions to enhance MKGPC's mechanical properties, with potential applications in low-strength structural elements and lightweight construction.