In a significant stride towards sustainable construction, researchers have developed a novel predictive model that could revolutionize the use of industrial solid wastes in building materials. The study, led by Guanqi Wei from the College of Civil and Transportation Engineering at Shenzhen University, introduces a reactive-phase-driven approach to design alkali-activated materials (AAMs), offering a more intelligent and universal solution to the inherent variability in waste reactivity.
The research, published in the journal *Cleaner Materials* (translated as “Cleaner Materials”), addresses a longstanding challenge in the construction industry: the inconsistent reactivity of industrial by-products like fly ash, slag, and circulating fluidized bed ash. These materials, often destined for landfills, can be repurposed as eco-friendly alternatives to traditional cement. However, their variable chemical compositions have made it difficult to standardize mix designs, hindering widespread adoption.
“We aimed to create a more scientific and rigorous method for classifying and utilizing these amorphous aluminosilicates,” Wei explains. The team employed advanced analytical techniques, including backscattered electron and energy dispersive spectroscopy, to classify the amorphous phases in solid wastes into 42 groups based on their atomic ratios. These groups were further graded into nine categories according to their microhardness.
The findings were striking. Medium-hardness phases (grades H40–H70) exhibited the highest reaction degrees and a strong positive correlation with compressive strength. This discovery paves the way for more precise and effective use of these materials in construction.
To capitalize on this insight, the researchers developed a grey wolf optimizer-enhanced backpropagation neural network model. This AI-driven approach uses phase content as input to predict the compressive strength of AAMs with exceptional accuracy. “Our model significantly outperforms conventional dosage-driven models, offering a more universal and intelligent design framework,” Wei notes.
The implications for the energy and construction sectors are profound. By enabling the intelligent design of multi-source solid waste-based AAMs, this research could accelerate the adoption of sustainable building materials. This shift could reduce the environmental impact of construction, decrease reliance on finite resources, and open new avenues for waste management.
As the world grapples with climate change and resource depletion, innovations like this are crucial. They not only drive technological advancements but also foster a more sustainable and circular economy. With further development and application, this reactive-phase-driven model could become a cornerstone of future construction practices, shaping a greener and more resilient built environment.