Microstructure Analyses Of Reinforcement Mechanism Of Cement In Stabilizing Champlain Sea Clay
Bibliographic record
Abstract
This research investigates the strength development and the formation of microstructures in Champlain Sea clay when treated with Portland cement and other cement-based binders and the effect of salinity level in the pore fluid on the strength and the mineralogical changes of cement-treated Champlain Sea clay. Champlain Sea clay, a sensitive marine clay commonly found in St. Lawrence Lowlands in eastern Canada, can lose up to 90 % of its strength when disturbed. The unconfined compressive strength tests were used to measure the shear strength development of binder-treated samples. The results indicated that cement-treated clay samples gain the shear strength at a faster rate than other binders under short-term curing conditions up to 28 days. However, under the same cement dosage of 50 kg/m3, the samples treated with cement with an additional 17 kg/m3 slag and those treated by cement with an additional 50 kg/m3 kiln dust exceeded the performance of those treated with only cement under the 300-day curing condition. Qualitative microstructural and mineralogical characterisations of cement-treated clay samples are investigated using scanning electron microscopy and X-ray diffraction (XRD). The results confirmed the transformation of an open structure in natural clay to a flocculated and aggregated structure due to the development of cement hydration products. The XRD analysis confirmed the formation of hydration products are found to be more pronounced in clay samples with a lower salinity level.
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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".