Sustainable one-part engineered geopolymer composite with thermal insulation in coastal region: Utilizing red mud dual-function as precursor and activator
Source abstract
Abstract
Aiming to advance value-added utilization of red mud (RM) for mitigating its environmental footprint, this study strategically leverages its dual-function as both a silicon-aluminum geopolymerization precursor and alkali activator. A sustainable, easy-to-operate, and high-ductility one-part EGC with high RM incorporation and thermal insulation function were successfully developed. The density maintained around 1100 kg/m 3 , with a low thermal conductivity of 0.35 W/(m·K). Remarkably, EGCs containing 50% and 80% RM precursors exhibited compressive strengths exceeding 20 MPa and 10 MPa, respectively, which remained above 10 MPa even at 25% alkali reduction. In addition, at merely 0.5% fiber dosage, the EGC demonstrated tensile strength above 2 MPa, strain capacity exceeding 4%, and controlled crack widths of around 200 μm. The tensile behavior evolution mechanism was revealed by synergistic matrix fracture toughness and fiber bridging capacity. Microstructural analysis revealed that increased RM incorporation and reduced alkali suppressed geopolymerization gel formation, compromising matrix densification while rarely affecting fiber-matrix interfacial bonding. The EGC achieved up to 44% and 71% reductions in embodied energy and embodied carbon compared to ordinary concrete, coupled with a 70% cost reduction compared to conventional M45-ECC. Notably, the fiber-free matrix mortar attained cost parity with ordinary concrete. This work can provide an important reference for the preparation of sustainable and low-cost one-part EGC with thermal insulation function by recycling a large volume of RM.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Concrete and Cement Materials Research · Bauxite Residue and Utilization · Magnesium Oxide Properties and Applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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