How the dispersion and coalescence behaviors of CO2 bubbles affecting carbonation reaction in bubble column reactor: experimental and numerical simulation study

• Distinct CO 2 coalescence (h/d=3.15) versus optimal dispersion regime (h/d=4-5). • Axial CO 2 /H 2 CO 3 concentration gradients revealed via experiment-simulation synergy. • Intense stirring alters bubble trajectory from vertical ascent to radial dispersion. Carbon dioxide (CO 2 ) mineralization via carbide slag (an alkaline industrial solid waste mainly composed of Ca(OH) 2 , with a D 90 of 146.877 μm) presents a promising strategy for CO 2 capture and utilization. However, achieving precise control over CO 2 bubble behavior in bubble column reactors (BCR), particularly regarding bubble distribution, coalescence patterns, and spatial uniformity, remains a critical challenge for process optimization. This study elucidates how operational parameters influence CO 2 bubble behavior and subsequent carbonation efficiency through systematic experimental investigation and numerical simulation. Our findings reveal distinct effects of operational parameters on bubble behavior: the height-to-diameter ratio (h/d) determines bubble spatial distribution patterns, with an optimal range of 4.00–5.00 achieving uniform bubble dispersion. Higher stirring rates (above 600 r/min) enhance bubble breakup and improve spatial distribution, leading to increased carbonation efficiency. Gas flow rate (200–300 mL/min) affects bubble number and distribution density, while gas distributor orifice dimensions (15–30 μm) influence initial bubble size and dispersion patterns. Under these parameter ranges, the carbonation efficiency can reach up to 81.88 %, with a CO 2 fixation efficiency of 51.26 %. Through high-speed imaging analysis coupled with numerical simulation, we elucidate bubble behavior evolution and identify distinct patterns of CO 2 and H 2 CO 3 concentration gradients along the reactor axis. The developed parameter optimization framework demonstrates that enhanced stirring rates can improve bubble breakup and spatial distribution, effectively compensating for suboptimal conditions of other parameters, providing fundamental insights into parameter-mediated bubble behavior control in BCR carbonation and establishing a theoretical foundation for industrial-scale implementation.