Multi-response optimization of thermally efficient RC-based geopolymer binder using response surface methodology approach

This research addresses the persistent challenge of strength degradation in geopolymer-based materials incorporating rubber crumb (RC). An optimization model was developed, focusing on critical variables such as RC grade (particle size), percentage incorporation, and the molarity of NaOH, using slags as alumina-silicate precursors. Response surface methodology (RSM) was employed for experimental design and statistical modelling to predict the strengths and thermal conductivity of the resulting geopolymer. The study meticulously analyzed the influence of each parameter on the performance of RC-based geopolymers to understand their practical implications. The models generated were highly significant, demonstrating high practicability and minimal errors. The optimization revealed that a geopolymer with the highest strength (41.91 MPa) and lowest thermal conductivity (0.504 W/mK) can be achieved using a molarity of 10, grade 20 RC, and 18.5% RC content. This study highlights the potential of optimizing RC-based geopolymer mixes to enhance material performance, promoting the sustainable use of waste tires and advancing the development of high-performance construction materials. • Alkali activation of Steel slag and GGBS for a dense microstructure aluminosilicate polymer network. • Finer crumb rubber boosts matrix dispersion, strengthening bonding for higher compressive strength. • Higher quantity and coarser crumb rubber particles enhance geopolymer thermal performance. • RSM is used to optimally predict and optimized the density, strengths, and thermal conductivity of Geopolymer. • Optimization by RSM suggest the best mix is the geopolymer with a molarity of 10, grade 20 rubber and 18.5% rubber crumb.