1. Introduction
In 1978, Joseph Davidovits created the terminology “geopolymer” to describe inorganic, amorphous, and semicrystalline aluminosilicates [
1]. Geopolymerization involves the chemical reaction of aluminosilicate with silicates under highly alkaline conditions [
2] to generate polymeric Si–O–Al–O bonds [
3]. Metakaolin (MK) is a commonly used aluminosilicate material. In alkaline media, it dissolves to form single Al(OH)
4− and Si(OH)
4− species, which undergo polymerization [
4]. Alkali metal salts and hydroxides are dissolved to form silicon dioxides and alumina for catalytic condensation reactions [
4]. According to some reports, geopolymers exhibit excellent performance and are fire resistant [
5,
6]. The study and exploitation of various kinds of geopolymers have demonstrated their use as fireproof materials [
7], cement and concrete [
8,
9], thermal insulation materials [
10], refractory materials [
11], and high-tech composite materials [
12]. Many factors affect mechanical behavior following powder particle dissolution, polymerization, and hardening reaction processes [
13]. Regarding the mechanical properties, compressive strength was the focus. Only a few studies have applied engineering to exploit other mechanical factors.
Sodium metasilicate (Na
2SiO
3) can provide sufficient silicon ions during the polymerization process to promote the activation precursor of geopolymer materials and improve the mechanical properties [
14], and Xu and Van Deventer (2003) discovered a simple correlation between the sodium silicate solution concentration and the compressive strength of the prepared geopolymer [
15]. Many factors influence the structural properties of geopolymers. One technique to find influencing factors from geopolymers was the design of experiments [
16,
17]. Factorial design and mixture design are statistical techniques for the design of experiments (DOEs) aiming to evaluate the linear, nonlinear, and interaction effects of several factors (independent variables) on a measurable property or response (dependent variable) [
16,
17]. The compressive strength was found to be affected by the microstructure and the corresponding composition contents [
18]. The mechanical properties and microstructure were shown to be controlled by three factors, including the Si/Al ratio [
18], the Na/Al ratio [
19], and the H
2O/Na ratio [
20]. Natassia (2021) evaluated the use of rice husk ash and aluminum anodizing sludge as aluminosilicate sources to obtain geopolymers in a mixture of sodium silicate and sodium hydroxide used as alkaline solutions. The analysis of variance (ANOVA) results indicated that the aluminum sludge is the factor that most affects the apparent density, diametral shrinkage, tensile strength, and deformation at rupture. The higher the sodium silicate + sodium hydroxide solution content, the lower the apparent density, shrinkage, and deformation at rupture [
21]. João (2021) evaluated the valorization of clay ceramic waste as a raw material for the synthesis of geopolymers. Clay ceramic waste, sodium hydroxide, and sodium silicate were the independent variables of a mixture design used to define the geopolymeric system. The results indicated that the amount of silica (SiO
2 = 69.8) and alumina (Al
2O
3 = 17.3) on the clay ceramic waste results in a Si/Al ratio of 4.0, which is adequate for geopolymerization, with adequate strength at 28 days of age [
22].
Furthermore, Tailby and Mackenzie (2010) analyzed one combination that influenced the mechanical strength and microstructure of a curing polymer, and geopolymerization occurred easily in a highly alkaline environment [
23]. However, the excess Ca and OH
− ions in the reaction process might have caused the formation of Ca(OH)
2, hindering geopolymer formation and resulting in an incomplete geopolymer structure [
19]. Rovnanik (2010) examined the mechanical properties of a geopolymer by analyzing the work factor, and his results revealed an increase in the early strength of the geopolymer at high curing temperatures [
24]. A definite relationship between the key bond and structure type of a geopolymer and its strength, which required an interpretation of the relationships between the polymerization, structural properties, and mechanical properties, was not determined [
24]. Xiao et al. (2020) indicated that due to the synergy between geopolymers and waste material, the strength performance improved significantly after a curing time of 14 days, which was attributed to the reaction between waste glass and class C fly ash [
25]. Sourav (2021) examined the effect of the ratio of sodium silicate to sodium hydroxide and Na
2O% with different alkali proportions on the hardened properties. The results revealed that the optimum compressive strength of 20.7 MPa is achieved at a sodium silicate to sodium hydroxide of 1.54 and Na
2O% of 12.5% [
26]. Iman (2021) examined sandy soil stabilized using a geopolymer based on copper mine tailing dam sediments with different content (10–20%) in different concentrations of potassium hydroxide (1–10 M). The results indicated that a geopolymer based on copper mine tailing dam sediments can be utilized to efficiently improve the compressive strength of soil without damaging the environment. The inclusion of silica fume in the mixtures considerably improved the strength and microstructural density of the specimens [
27]. The goals of the Waste Electrical and Electronic Equipment directive are to prevent the inappropriate disposal of electrical and electronic equipment waste, reuse and recycle waste, and reduce e-waste deposition in landfills. This directive highlights the need to address the SiC sludge (SCS) problem. To our knowledge, the DOE approach has not been used to optimize the strength of a geopolymer obtained from SCS and MK [
22,
23,
24,
25,
26,
27]. Based on previous studies [
22,
23], optimization of design factors for a metakaolin-based geopolymer incorporated with SiC sludge (SCSGPs) was proposed using the DOE approach in this work. Mechanical properties were analyzed to determine the significant component factors based on the independent variable in the statistical analysis. The influences of the interactions between different component factors were considered, and it was expected that scientific data and a standardized design process for SCS admixtures would be provided for the production of suitable geopolymers.
4. Conclusions
In this study, the DOE method was used to perform a statistical analysis of experimental data to study the factors that affect the mechanical properties of SCSGPs. The result of the t-test shows that in terms of compressive strength, MK was the most important factor, followed by Na2SiO3. The p value of the Si/Na, S/L, and Si/Al ratios and OH− (M) was 5.14 × 10−4, 4.09 × 10−4, 4.45 × 10−4, and 1.92 × 10−3 respectively. The influence level of factors was S/L > Si/Al > Si/Na > OH−. The influence level of the S/L and Si/Al ratios is higher than that of the Si/Na ratio and OH−. Using multivariate statistical analysis methods, the relationship between the mechanical properties of geopolymers and related parameters was predicted. After adjusting the multivariate test coefficients, the r2 value was greater than 0.869. The statistical analysis shows that the compressive strength of SCSGPs was affected by the interaction between the NSR and the DRA as well as between the NAR and the DRA, indicating that the NSR and the NAR were the most important factors, followed by the DRA. Within the design range of this study, the highest compressive strength of SCSGPs was 66.08 MPa, and the coefficients of the NSR, the NAR, and the DRA of SCSGP were 0.15, 0.22, and 58.24, respectively. The analysis results of the multiple regression analysis models provide an effective reference for the application of a metakaolin-based geopolymer incorporated with SiC sludge, and the required strength level can be achieved without tedious mixing formulas.