Effect of Strontium Contaminants upon the Size and Solubility of Calcite Crystals Precipitated by the Bacterial Hydrolysis of Urea
Bibliographic record
Abstract
The nucleation and growth of calcite precipitates induced by the bacterial hydrolysis of urea (ureolysis) from a Sr-contaminant inclusive, and a Sr-free artificial groundwater (AGW) mimicking the composition of the 90Sr contaminated Snake River Plain aquifer were investigated. Sr-free experiments exhibited a gradual increase in mean calcite crystal diameter (<1000 nm) from day (D) 1 to 6, while in the Sr-inclusive experiments, daily diameters were approximately constant from D1 to D6, and crystals were smaller (mean <840 nm). These data demonstrate a steady state had been attained early in the Sr-inclusive experiments from growth inhibition by Sr. Modeling of the crystal growth mechanisms on the USGS GALOPER software suggested crystal size distributions in the Sr-inclusive and Sr-free experiments were generated in the nucleation stage by a decreasing nucleation rate with surface-controlled growth, followed by supply-controlled and random growth. This occurred despite the availability of Ca2+ and HCO3-, implying crystal growth is limited bythe rate of solute advection to the crystal surface. Calculation of the solubility constant (In KsO(A)) demonstrates smaller crystals are more soluble, reflecting a higher molar surface area. The coprecipitation of Sr therefore generates smaller and thus more soluble crystals. However, this is unlikely to dramatically reduce the long-term effectiveness of Sr immobilization because when crystal growth had ceased in the Sr-inclusive AGW, > 99% of calcite precipitated and Sr coprecipitated occurred in large crystals with a low solubility.
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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 | 0.000 | 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".