Contribution of bacterial cells as nucleation centers in microbiologically induced CaCO₃ precipitation—A mathematical modeling approach

Abstract

The microbiologically induced calcite precipitation (MICP) has been extensively studied for geotechnical engineering through simultaneous action of natural phenomena and engineering processes. The focus of bacterial contribution to the MICP has been directed to calcium carbonate productivity, while the additional bacterial role as a crystal nucleation center was not explained especially from a mathematical prediction modeling point of view. Therefore, this study provides explanations and a mathematical modeling approach of bacterial influence on the MICP induced by newly-isolated ureolytic Bacillus strains and Sporosarcina pasteurii DSM 33. Using the obtained results of low-cost, rapid, and simple assays, artificial neural network modeling was applied for cell surface predispositions, pH changes as well as calcium-involved function in biofilm formation during the MICP, for the first time. Based on the obtained contribution of the alkalophilic/alkaloresistant bacteria, calcite precipitation can be significantly directed by the presence, of ureolytic bacterial cells as nucleation centers during CaCO 3 precipitation as well as their morphology, surface characteristics, potential to form a biofilm, and/or generate pH changes.

Modification of Surfaces with Vaterite CaCO3 Particles

“…Some studies have indicated that microbiologically induced CaCO 3 precipitation, with some changes in surface characteristics and pH, can lead to the formation of biofilms [ 90 ]. Researchers have found that nanomechanical and morphological properties of CaCO 3 can be tailored if they are precipitated via bacteria.…”

Relationship between Bacterial Contribution and Self-Healing Effect of Cement-Based Materials

“…In particular, this role of bacterial cells in the SH effect is strongly associated with the potential of active cells to be CaCO 3 nucleation centres. The connection between the physical contribution of cells and the SH effect can be based on: Cell geometric compatibility (cell size, specific surface area, and volume) and motility; Cell−surface electronegativity and hydrophobicity (affinity, types, and amount of chemical bonds on the cell surface); Cell membrane permeability (in a function of extracellular carbonate production rate); Biofilm production (possibility and rate of adhesion on inorganic surfaces) [ 88 ]; The cell size can be a crucial parameter for bacterial activity in view of variable concrete porosity during dry/wet cycles in material [ 7 ]. Figure 3 also showed a correlation between average cells and pore sizes during hydration and volumetric changes in concrete.…”

“…Besides water availability, pore size changes can also be a limiting parameter for spore activation and cell proliferation. Based on cell size, cell−specific area and volume of active bacteria that are involved in BICP are between 2.6 and 8.55 µm 2 and between 0.3 and 1.64 µm 3 , respectively [ 88 ]. Considering that bacteria require availability in space, pore volume can influence bacterial activity, and as a result, CaCO 3 precipitation.…”

An artificial neural network as a tool for kombucha fermentation improvement

“…The numerical verification of the developed model was tested using the coefficient of determination (r 2 ), reduced chi-square (χ 2 ), mean bias error (MBE), root mean square error (RMSE), and mean percentage error (MPE). These commonly used parameters can be calculated as follows [35]:…”