Evaluation of the Potential of Metakaolin, Electric Arc Furnace Slag, and Biomass Fly Ash for Geopolymer Cement Compositions.

The widespread use of geopolymer cement (GPC) has been hindered by a lack of scientific knowledge that still exists regarding its synthesis process. Key points, such as the release of aluminosilicate species from the raw materials and its link to the properties of GPC, have still not been completely studied. As a result, most of the GPC formulations covered in the literature are based on precursors' elemental analysis using XRF (X-ray Fluorescence), or other equivalent analysis methods, and consider that the total aluminosilicate content of the precursors is available for participating in the geopolymerization process, which seems very unlikely. In this study, the amounts of aluminate and silicate species released from metakaolin (MK), electric arc furnace slag (EAFS), and biomass fly ash (BFA) in alkaline dissolution tests were determined by simple spectrophotometric methods. It was found that MK yields the highest aluminosilicate dissolution amount, about 2.1 mmol of silicate + aluminate per gram of MK, while EAFS and BFA yield about 0.53 and 0.32 mmol/g precursor, respectively. These results were used to estimate the total amounts of dissolved aluminosilicates in a series of GPC mortars prepared from these raw materials, which were thereafter subjected to mechanical tests. It was shown that the mortars' compressive strength (which ranged from 1 to 63 MPa) is linearly correlated with their estimated total amount of dissolved aluminosilicates, with the best linear fit yielding a coefficient of determination above 0.99. It was concluded that by using the results of the dissolution tests, the estimation of compressive strength is greatly improved when compared to using the elemental analysis obtained by XRF, which yields a coefficient of determination of 0.88 and a larger dispersion of data points. The results reveal the usefulness of this simple method for evaluating the potential of inorganic industrial waste streams as precursors for GPC.