Reactivity of Unconventional Fly Ashes, SCMs, and Fillers: Effects of Sulfates, Carbonates, and Temperature
Bibliographic record
Abstract
ABSTRACT Reactivity information for a range of unconventional fly ashes is unavailable in literature. The objective of this study is to quantify the reactivity of numerous unconventional fly ashes using the R3 test (ASTM C1897-20, Standard Test Methods for Measuring the Reactivity of Supplementary Cementitious Materials by Isothermal Calorimetry and Bound Water Measurements) and the modified R3 test and to determine how sulfates, carbonates, and temperature affect the measured reactivity. A small set of other supplementary cementitious materials and fillers was used to benchmark the fly ash results. Heat release, calcium hydroxide consumption, and bound water were measured for the different materials. For siliceous materials with relatively low calcium oxide (CaO) + aluminum oxide (Al2O3) contents, temperature had a dominant effect on the heat release. On the other hand, for materials with higher CaO + Al2O3 contents, the effects of sulfates and carbonates dominated the effect of temperature. The slow but sustained reactivity of Class F fly ashes highlighted the importance of kinetic corrections or extrapolations to the reactivity measured in the R3 test. However, when testing at 50°C, the heat release curves of all tested materials plateaued at the end of 10 days, indicating that kinetic corrections were not required. Correlations between reactivity and early- and later-age paste properties are discussed.
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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 | 0.001 | 0.001 |
| 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".