Self-compacting concrete (SCC) became a strong candidate for various construction applications owing to its excellent workability, low labor demand, and enhanced finish-ability, and because it provides a solution to the problem of mechanical vibration and related noise pollution in urban settings. However, the production of Portland cement (PC) as a primary constituent of SCC is energy-intensive, contributing to about 7% of global carbon dioxide (CO₂) emissions. Conversely, the use of alternative geopolymer binders (GBs) in concrete can significantly reduce the energy consumption and CO₂ emissions. In addition, using GBs in SCC can produce unique sustainable concrete with unparallel engineering properties. In this outlook, this work investigated the development of some eco-efficient self-compacting geopolymer concretes (SCGCs) obtained by incorporating different dosages of fly ash (FA) and ground blast furnace slag (GBFS). The structural, morphological, and mechanical traits of these SCGCs were examined via non-destructive tests like X-ray diffraction (XRD) and scanning electron microscopy (SEM). The workability and mechanical properties of six SCGC mixtures were examined using various measurements, and the obtained results were analyzed and discussed. Furthermore, an optimized hybrid artificial neural network (ANN) coupled with a metaheuristic Bat optimization algorithm was developed to estimate the compressive strength (CS) of these SCGCs. The results demonstrated that it is possible to achieve appropriate workability and mechanical strength through 50% partial replacement of GBFS with FA in the SCGC precursor binder. It is established that the proposed Bat-ANN model can offer an effective intelligent method for estimating the mechanical properties of various SCGC mixtures with superior reliability and accuracy via preventing the need for laborious, costly, and time-consuming laboratory trial batches that are responsible for substantial materials wastage.

The purpose of this study is to study the life cycle assessment of biocementitious materials production in comparison to traditional cement materials production. The environmental impact of production processes over the life cycle was evaluated on the basis of global warming and ozone depletion, human health, land, freshwater, marine ecotoxicity, and natural water system eutrophication. LCA uses endpoint methods (ECO indicators) and SimaPro 8 software to assess the health and environmental impact of raw materials used in the production process, including cement, Ca(NO₃)₂·4H₂O, urea, molasses, and electricity. The results showed that cement materials made 82.88% of the world’s warming in all raw materials used in production processes, 87.24% of the world’s health, 89.54% of the deforestation of freshwater, and 30.48% to marine eutrophication. Ca(NO₃)₂·4H₂O contributes by 58.88% to ozone depletion, 15.37 to human carcinogenic toxicity, 3.19% to freshwater eutrophication, and 11.76% to marine eutrophication. In contrast, urea contributes 38.15% to marine eutrophication and 5.25% to freshwater eutrophication. Molasses contribute by 13.77% to marine eutrophication. Cement contributes 74.27% to human health damage, 79.36% to ecosystem damage; Ca(NO₃)₂·4H₂O contributes 13.54% to human health damage and 9.99% to ecosystem damage; while urea contributes 6.5% to human health damage and 5.91% to ecosystem damage. Bio-cementitious wastewater should undergo a treatment process to remove urea and molasses residues, as well as nitrates, before final disposal into the environment.