Bio-healing for micro-crack treatment in cementitious materials: Toward a quantitative assessment of bacterial efficiency
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Bibliographic record
Abstract
Bio-healing is a promising approach to enhancing natural self-healing and thus completely heal large micro-cracks (> 200 ?m) in cementitious materials. The aim of this research is to better understand bio-healing of cementitious materials in order to accelerate the healing kinetics and maximize sealing efficiency of large micro-cracks. The bio-healing approach generally consists in soaking micro-cracks in a culture medium containing a bacterial strain. However, it is difficult to precisely assess the efficiency of the bacterial-mediated precipitation in the bio-healing process with respect to the impacts of natural self-healing and precipitation induced by the culture medium. The aim of this work is to study the healing of well-defined micro-cracks on mortars subjected to more and more complex healing mechanisms. First, cracked mortars were subjected to natural self-healing, then to a precursor solution (calcium lactate), and finally, to a culture medium containing a bacterial strain. However, before this last step, an important part of this study focused on assessing the growth kinetics of a bacterial strain: Bacillus cohnii. Mortars specimens (W/C = 0.485) were submitted to controlled cracking at 28 days (under sustained load) using a mechanical expansive core. Two micro-crack categories were created (100 ± 5 ?m and 195 ± 30 ?m). The healing kinetics was evaluated from air-flow measurements that were used to compute the evolution, over time, of the apparent crack opening (1, 3 and 6 months of conservation at 23°C and 100% R.H.) Overall, self-healing was faster and more complete when cracks were soaked in calcium lactate solutions compared to natural healing. Thus, precursor solutions significantly improved the healing kinetics of the larger micro-cracks (> 150 ?m). On the other hand, the optimum growth conditions for Bacillus cohnii were evaluated at different nutrient concentrations and pH values. Finally, a method was developed in order to evaluate the bacterial activity semi-quantitatively.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it