Research of CO2 Mineralization Mechanism in Coal Mine Backfill: Experimental Characterization, Molecular Simulation, and Engineering Knowledge Transfer

Abstract

Abstract The escalating global climate crisis necessitates innovative solutions for CO 2 mitigation, particularly within resource-intensive industries. This study develops a high-performance CO 2 mineralized backfill to address the dual challenge of carbon sequestration and industrial waste utilization. To bridge the gap between fundamental scientific understanding and complex industrial applications, this research employs a systematic engineering lifecycle framework, encompassing conceptualization, design, implementation, and operational validation, as a robust methodology for technology development. Utilizing industrial fly ash and cement, backfill slurries were prepared and subjected to accelerated carbonation curing. A comprehensive experimental program, encompassing rheological testing, mechanical testing, thermogravimetric analysis, and molecular dynamics (MD) simulations, was conducted. Results indicate that the optimal mix, PB-5 (63% mass fraction, 10% cement content), achieved a 5.106% CO 2 sequestration rate while maintaining rheological stability. Crucially, full-scale engineering validation confirmed that the backfill satisfies the mechanical support requirements. A novel exponential regression model was established to elucidate the strength enhancement mechanism, revealing a Microstructural connectivity transformation: strength gain is triggered when carbonate products evolve from discrete fillers to a continuous interlocking skeleton. Furthermore, MD simulations visualized the hydration-mediated ion transport mechanism, revealing that the desolvation of Ca 2 + ions is the rate-limiting step for carbonate nucleation. Importantly, this study demonstrates that this integrated macro–micro research framework serves as a robust paradigm for engineering knowledge transfer. By successfully bridging abstract reaction kinetics with practical industrial processes, this work provides a reproducible methodological framework for translating complex scientific data into actionable engineering guidelines, optimizing process control parameters, accelerating sustainable industrial transformation, and enhancing systemic resilience in the mining sector.