Comparative analysis of silt, kaolinite, and montmorillonite particle effects on bio-cementation in sandy soils
Bibliographic record
Abstract
Efficiency of microbiologically induced carbonate precipitation (MICP), an eco-friendly ground improvement method, relies heavily on soil composition, particularly the type and percentage of fine particles. Past research has predominantly focused on pure sands, with limited studies on the effects of a single type of fine, mainly silt or kaolinite clay, in spherical particle sands. Consequently, there remains a lack of fundamental knowledge regarding how different fines impact MICP differently. This study addresses this gap through a novel comparative analysis of the impacts of silt, kaolinite, and montmorillonite on MICP in two sands with spherical and angular particles. Laboratory column tests were performed on sands containing 0%, 2.5%, and 7.5% fines. All fines (up to 7.5%) improved the unconfined compressive strength (UCS) of MICP-treated samples. Silt achieved the most uniform cementation and highest UCS increase (∼7 times). Kaolinite was the least effective, causing the highest bio-cement heterogeneity. The mode of cementation—whether contact or surface—was primarily governed by the host sand properties when fine content was low (≤2.5%), but was influenced by fines’ characteristics in addition to characteristics of the host sand at higher fines content. Findings reveal that a greater cement content does not guarantee higher strength in MICP-treated sandy soils, highlighting the critical role of fines properties and other governing factors in strength development.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".