Fly ash, a by product from coal and biomass combustion in fossil-fuel power plants, is composed of fine particulate matter that can contribute to terrestrial and atmospheric pollution if not properly contained. In this study, we explored the use of an alkali activator in the production of fly ash-based concrete to contain fly ash particles. Fly ash was mixed with different concentrations of an alkaline activator (sodium hydroxide) for up to 28 days. We employed SEM images and laboratory tests supported by an Artificial Neural Network (ANN) to determine the properties and strength of concrete. Our findings reveal that sodium hydroxide at 5 and 6% optimized the strength of colloidal sand mixture and the precursor of concrete at 3 and 28 days, respectively. Fly ash content of 10% optimized concrete strength, while 20% and 30% fly ash contents at 3 and 28 days resulted in better cement strength compared to the control. Sodium hydroxide initially rapidly improved colloidal sand mixture strength but its influence tapered over time. Amorphous silica and alumina phases significantly affected the performance of ordinary fly ash alkali-activated mortar. ANN learning training data effectively assisted laboratory tests to determine the strength of concrete with a percent error of 10, demonstrating the potential of this approach in enhancing the understanding of concrete properties and strength development.
Xu et al. (Thu,) studied this question.