ArticleScientific reports2026
Cost-effective and sustainable ultra-high-performance concrete with electric arc furnace slag and calcium carbonate: a multi-objective optimization and experimental validation approach.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Ultra-high-performance concrete (UHPC) delivers exceptional performance, but it is still largely a high-clinker material, which drives up both cost and embodied CO₂. Here, we present a low-clinker UHPC matrix that incorporates electric arc furnace slag (EAFS) and calcium carbonate powder (CaC), with quartz flour fully replaced by CaC. The mixtures were proportioned using the Modified Andreasen & Andersen particle-packing approach and then explored through a central composite design to quantify how cement dosage, water-to-binder ratio, and high-range water-reducer (HRWR) dosage control fresh flow and strength development. A desirability-based optimization was finally used to minimize cement content while maintaining self-compacting workability (240–260 mm slump flow) and UHPC-level 28-day strength (≥ 150 MPa). Relative to the control mixture, the optimized formulation reduced cement from 852 to 598 kg/m³ (− 29.8%), which corresponds to an approximate ≈ 30% reduction in cement-related embodied CO₂ (≈ 127–178 kg CO₂/m³ avoided on a cement-only basis). Under ambient curing, the optimized mix achieved a slump flow of 252 mm and compressive strengths of 151.1 ± 7.9 MPa at 28 days and 158.9 ± 3.1 MPa at 90 days (+ 5.1% from 28 to 90 days). Young’s modulus increased from 40.1 ± 1.5 GPa at 7 days to 45.0 ± 1.4 GPa at 90 days. RCPT charge passed decreased with age (281 ± 11 C at 28 days to 78 ± 7 C at 90 days), indicating improved resistance to chloride-ion penetration over time, although values remained higher than the control. Overall, the results show that UHPC-level strength and self-compacting flow can be achieved with a substantially reduced clinker demand using a particle packing-theory and statistic-guided mixture design strategy.
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