Influence of Binder Types and Temperatures on the Mechanical Properties and Microstructure of Cemented Paste Backfill
Bibliographic record
Abstract
In order to study the influence of burial depth or fire on the core area of cemented paste backfill (CPB), the experiment of CPB with different types of binder and temperature was carried out. Three types of binders, red mud (RM), Portland cement (PC), and slag cement (SC), are used and tested at 20°C, 40°C, 60°C, and 80°C. The macroperformance and microstructural evolution of CPB are analyzed using slump, uniaxial compressive strength (UCS), X‐ray diffraction, and scanning electron microscopy (SEM). The results show that the coupled effects of binder type and temperature have a significant impact on the macroscopic performance and microstructural evolution of CPB. The CPB slump prepared with three types of binder meets the production requirement of the mine. Regardless of curing temperature and curing time, the uniaxial compressive strength of CPB samples with PC and SC is much higher than that of CPB samples with red mud. When cured for 12 hours, the uniaxial compressive strength of CPB samples containing PC and SC increases first, then decreases, and finally increases again with the increase of temperature. However, with the increase of temperature, the uniaxial compressive strength of CPB samples containing RM only increases first and then decreases. When the curing temperature is less than 40°C, the main reason for the increase in UCS was attributed to the fact that the temperature increase accelerates the hydration reaction and improves the density of the sample. When the curing temperature is 60°C, the main reason for the decrease in UCS is the formation of the expansive ettringite (AFt) which destroys the internal spatial structure of the sample. When the curing temperature is 80°C, the UCS increases again due to the fact that such high temperature can destroy the crystal structure of AFt and harden the hydration product C‐S‐H gel.
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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 | 0.001 |
| 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".