Predictive modeling of microbial biomineralization across scales

Microorganisms influence mineral formation and transformation in natural and engineered environments, with consequences for element cycling, contaminant mobility, and mineral records. Predicting these processes remains difficult because microbial activity, local aqueous chemistry, interfacial reactions, and mineral formation operate across different spatial and temporal scales. Here, we review molecular, geochemical, reaction–transport, biofilm- and cell-based, and data-driven models, focusing on what each can predict and how those predictions are tested experimentally. We explain the quantities that may connect models across scales, including ion binding, microbial activity, local chemical conditions, mineralization kinetics, and transport properties. Existing studies show stronger predictive development in geochemical and reactive-transport approaches than in connections between molecular interactions, microbial microenvironments, and mineral formation. We identify unresolved cross-scale relationships and discuss how spatially resolved measurements and independent experimental tests can strengthen predictive modeling of microbial biomineralization across scales.