Experimental investigation and prediction of compressive strength of mortar incorporating zinc tailings using artificial neural network

Mining activities play a pivotal role in a country's economy, contributing significantly to industrial growth and infrastructure development. However, the generation of tailings is a significant concern due to issues such as land use, water pollution, and the risk of tailings dam failures. The present research paper explores the feasibility of zinc tailings as a sustainable alternative to sand in mortar production, aiming to mitigate the depletion of natural sand resources and manage waste effectively. Mortar specimens were prepared using zinc tailings to replace natural sand at varying percentages (0–50 %) and different water-to-cement ratios (0.45, 0.50, and 0.55). Main parameters such as compressive strength, water absorption, microstructure, XRD analysis were studied using zinc tailings incorporation. ANNs have been trained to predict the compressive strength of mortar incorporating zinc tailings. SEM analysis reveals a denser microstructure and improved bonding over time due to increased hydration and C-S-H gel formation from reactive silica and alumina. X-ray diffraction shows higher quartz and dolomite peaks but no new crystalline phases, with C-S-H and C-A-S-H phases remaining amorphous. The model R² value of 0.939 indicates strong predictive accuracy, explaining 93.9 % of the variation in compressive strength based on actual results. The partial replacement of sand by zinc tailings in mortar results in a slightly increased water absorption, from 7 % to 7.22 % (at 0 % to 50 % replacement). X-ray diffraction analysis showed higher intensities of quartz and dolomite peaks in mortars with zinc tailings. These findings reveal that replacing 20–30 % of the sand with zinc tailings can be a sustainable approach to minimizing the environmental footprint of tailing production.