Identification of main factors affecting mechanical characteristics of silicon carbide sludge‐based geopolymer via experimental design and associated statistical analysis

Despite considerable research in geopolymer materials, the design of experiment (DOE) method has not previously been used for the analysis of geopolymers containing silicon carbide sludge (SCS) waste and/or metakaolin (MK). This study used DOE methods to quantitatively assess the correlation between factor parameters and the macroscopic and microstructural properties of SCS‐based geopolymers (SCSGPs). Statistical analysis identified Na/Si molar ratio, Na/Al molar ratio, and the dissolution rate of Al as the factors with the most profound influence on the compressive strength of the SCSGPs. Analysis of setting time and compressive strength revealed that in SCSGP samples containing 20% SCS, coefficient b in power function regression analysis was the most influential, due to the synergy between MK and SCS. The results obtained in this study using a multivariate adaptive regression splines model to establish a valuable reference for the further development and standardization of geopolymer mixture designs based on SCS.