Predictive modeling of microbial biomineralization across scales
Abstract
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.
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BibTeX
@misc{ahmadi2026predictive,
title = {{Predictive modeling of microbial biomineralization across scales}},
author = {Atiyeh Ahmadi and Maria Dittrich},
howpublished = {EarthArXiv},
year = {2026},
month = nov,
doi = {10.31223/x53z5w},
url = {https://eartharxiv.org/repository/view/15928/},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Predictive modeling of microbial biomineralization across scales
AU - Atiyeh Ahmadi
AU - Maria Dittrich
PY - 2026
DA - 2026/11/03
PB - EarthArXiv
DO - 10.31223/x53z5w
UR - https://eartharxiv.org/repository/view/15928/
AB - 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.
ER -