A study on the crystallization kinetics and nucleation rate models of MICP based on microfluidic experiments and numerical simulation

While microbial-induced carbonate precipitation (MICP) self-healing technology offers advantages in environmental sustainability and intelligent operation, a systematic understanding of calcite nucleation, growth, and deposition kinetics in seepage-rich environments remains lacking, and existing numerical models lack verifiable predictive tools for quantitatively estimating nucleation rates. To address these gaps, we integrated microfluidic chip experiments, time-lapse microscopy, automated image processing, and reaction–transport numerical simulations, enabling real-time monitoring of the entire crystallization sequence under seepage and quantitative extraction of kinetic parameters. We systematically examined the synergistic effects of temperature (20–40 °C), pH (6.5–9.0), calcium ion concentration (0.5–2.0 M), and bacterial density (0.1–3.0) on nucleation, growth, and deposition. Each factor exerts a non-monotonic influence on nucleation rate. Optimal nucleation conditions are 30 °C, pH 7.5, the calcium ion concentration is 1.0 M, and bacterial density is 1.5, under which precipitation efficiency reaches 65% and crystals exhibit well-developed rhombohedral calcite. Deviations lead to reduced rates, aragonite co-precipitation, or urease inactivation. Based on classical nucleation theory, we developed a multi-factor apparent nucleation rate prediction model coupling temperature, pH, bacterial concentration, and calcium ion concentration, enabling quantitative nucleation rate estimation. The reaction-transport coupled model, solved via a semi-implicit finite-difference scheme, yields simulated total precipitate mass and spatial distribution in good agreement with experiments. Collectively, this work provides a verifiable quantitative framework and predictive tools for elucidating the underlying mechanisms and offers a robust theoretical basis for the rational design and optimization of MICP-based self-healing strategies in practical engineering applications under percolation conditions.