Improving the strength of sandy soils via ureolytic CaCO <sub>3</sub> solidification by <i>Sporosarcina ureae</i>
Bibliographic record
Abstract
Abstract. “Microbially induced carbonate precipitation” (MICP) is a biogeochemical process that can be applied to strengthen materials. The hydrolysis of urea by microbial catalysis to form carbonate is a commonly studied example of MICP. In this study, Sporosarcina ureae, a ureolytic organism, was compared to other ureolytic and non-ureolytic organisms of Bacillus and Sporosarcina genera in the assessment of its ability to produce carbonates by ureolytic MICP for ground reinforcement. It was found that S. ureae grew optimally in alkaline (pH ∼ 9.0) conditions which favoured MICP and could degrade urea (units U mL−1 represent µmol min−1 mL OD600) at levels (30.28 U mL−1) similar to S. pasteurii (32.76 U mL−1), the model ureolytic MICP organism. When cells of S. ureae were concentrated (OD600 ∼ 15–20) and mixed with cementation medium containing 0.5 M calcium chloride (CaCl2) and urea into a model sand, repeated treatments (3 × 24 h) were able to improve the confined direct shear strength of samples from 15.77 kPa to as much as 135.80 kPa. This was more than any other organism observed in the study. Imaging of the reinforced samples with scanning electron microscopy and energy-dispersive spectroscopy confirmed the successful precipitation of calcium carbonate (CaCO3) across sand particles by S. ureae. Treated samples were also tested experimentally according to model North American climatic conditions to understand the environmental durability of MICP. No statistically significant (p < 0.05, n= 3) difference in strength was observed for samples that underwent freeze–thaw cycling or flood-like simulations. However, shear strength of samples following acid rain simulations fell to 29.2 % of control MICP samples. Overall, the species S. ureae was found to be an excellent organism for MICP by ureolysis to achieve ground strengthening. However, the feasibility of MICP as a durable reinforcement technique is limited by specific climate conditions (i.e. acid rain).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".