Urease active bioslurry: a novel soil improvement approach based on microbially induced carbonate precipitation
Bibliographic record
Abstract
This paper presents a novel approach for soil stabilization by microbially induced carbonate precipitation (MICP) using a new urease active catalyzer, named herein as “bioslurry”. The bioslurry, which was produced from the reaction between bacterial culture and 400 mmol/L of CaCl2 and urea, is pre-formed urease active crystals consisting of CaCO3 plus imbedded urease active bacterial cells. By mixing the bioslurry with sand, more than 95% of the bioslurry was retained in the soil matrix as a result of the mechanical trapping mechanism, leading to high resistance to flushing with a low-salinity solution. The retained urease activity of bioslurry was uniformly distributed along the sand matrix, resulting in a rather uniform CaCO3 precipitation. Through repeated treatments with a cementation solution, the unconfined compressive strength of bioslurry treated sand was significantly improved due to the effective CaCO3 precipitation at the contact points of soil grains. Scanning electron microscopy analysis carried out on the bioslurry treated sand revealed that the induced large rhombohedral CaCO3 crystals were localized around the bioslurry spherical fine crystals. The overall outcome of this work is that soil biocementation using the new bioslurry approach is controllable, reproducible, and homogeneous.
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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 | 0.000 |
| 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".