Effect of nanoparticle-enhanced biocementation in kaolinite clay by microbially induced calcium carbonate precipitation
Bibliographic record
Abstract
Microbially induced calcium carbonate precipitation (MICP) is a nature-based technique that has been developed over the past two decades for soil stabilization. However, the use of MICP for clay stabilization has received limited attention in the literature. On the other hand, the utilization of nanomaterials, such as nano-silica (nano-SiO2), for soil stabilization has been explored in numerous studies in the literature. This paper investigates the effect of nano-CaCO3 and nano-SiO2 on MICP stabilization in kaolinite clay. Nanoparticle-enhanced bio-cementation is introduced to effectively improve the strength of kaolinite clay at high water contents. Unconfined compressive strength (UCS) tests were conducted to evaluate the impact of the nano-bio-treatment (mixture of nano-additives and MICP) on soil strength. Additionally, the microstructure of the treated soils was examined using scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), Raman spectroscopy, and X-ray diffraction (XRD) analyses. The results indicate that the MICP stabilization method is effective in enhancing the strength of kaolinite soil through a mixing approach. The study of UCS in the treated samples revealed that the use of nano-CaCO3 and nano-SiO2 can have either detrimental or beneficial effects on the MICP method, depending on the degree of saturation of the treated samples. The highest UCS observed for the MICP method at a target water content of 0.25 was more than three times that of untreated soil at the same moisture content. Furthermore, the increase in UCS for the samples treated with MICP was 2.5 times that of the untreated soil at a 30% target water content. The most significant finding, however, is that, at a 30% target water content, the samples improved with MICP+ 1.5% nano − SiO2 exhibited UCS values that were six and fifteen times greater than those of the untreated and MIC-treated samples, respectively. SEM images illustrated that the addition of nano-SiO2 with the MICP method led to an agglomerated soil texture, and the formation of calcium carbonate attached to the clay minerals. This results in an increase in soil strength.
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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".