Insights on chemical and physical chloride binding in blended cement pastes
Bibliographic record
Abstract
This study investigates chloride binding in blended cement pastes exposed to 0.5 M NaCl solutions (with and without pH adjustment) using X-ray diffraction and energy-dispersive X-ray spectroscopy image analysis (edxia). The aim is to better understand the effects of the binder type, the water-to-binder ratio and the pH on the chemical binding in AFm phases and the physical binding on C-A-S-H. Results show that the binding cannot be predicted from AFm and C-A-S-H contents alone because competing ions in the system affect both the Friedel's salt solid solution chemistry and the C-A-S-H binding capacity. Notably, the high content of aluminous hydrates in LC3 systems leads to a high chemical binding even if Friedel's salt solid solutions have relatively low chloride contents (particularly at a higher pH). On the contrary, the CEMIII/A paste showed low binding because of relatively high sulfate and magnesium contents which compete for incorporation/adsorption in aluminous hydrates (AFm, ettringite and hydrotalcite).
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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".