The Influence of<i>Bacillus pasteurii</i>on the Nucleation and Growth of Calcium Carbonate
Bibliographic record
Abstract
Microcosm experiments were performed to identify the influence of bacterial cell surfaces on the morphology, mineralogy, size and solubility of CaCO3 precipitated in response to the enzymatic hydrolysis of urea in an artificial groundwater (AGW) by the ureolytic bacteria, Bacillus pasteurii. In each microcosm, B. pasteurii were contained within a cellulose dialysis membrane (10 K Dalton MWCO), resulting in bacteria-inclusive and bacteria-free AGW solution. Urea hydrolysis by B. pasteurii resulted in the production of ammonium and an increase in pH in the whole AGW solution. This initiated predominantly rhombohedral calcite precipitation at the same critical saturation state ( S critical = 12) in the B. pasteurii-inclusive and bacteria-free zone of the AGW, indicating the mineralogy and morphology of CaCO3 precipitation is not controlled by B. pasteurii surfaces. However, the temporal evolution of distinctly different lognormal crystal-size-distributions in the B. pasteurii-inclusive and bacteria-free zone of the AGW resulted from identical changes in bulk solution chemistry. Specifically, B. pasteurii increased the size and size variance of crystals, and led to a greater crystal growth rate throughout the experiments, relative to bacteria-free AGW. Calculated crystal solubility (ln K S0 ) was lower for crystals > 4000 nm in diameter, reflecting smaller molar surface areas. This suggests that the larger crystals generated in the presence of B. pasteurii have a lower affinity for re-dissolution than those generated in the bacteria-free AGW, which may act as a positive feedback to maintain larger crystal sizes in the presence of B. pasteurii. During ureolysis, higher bacterial concentrations may therefore generate larger and less soluble carbonate crystals. This has important implications for the adaptation of bacterial ureolysis as a method for precipitating calcium carbonate and co-precipitating metals and radionuclides in contaminated aquifers.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".