Mechanism of Alkali‐Activated Copper‐Nickel Slag Material
Bibliographic record
Abstract
A copper‐nickel slag‐based alkali‐activated cementing material (CNSCM) for backfilling was prepared using copper‐nickel slag as a raw material and sodium silicate (SS) as an activating agent. The effects of SS content (6%, 8%, and 10%) and curing humidity on the compressive strength of CNSCM were investigated using an electronic universal testing machine. Types of hydration products and microstructures were analyzed by X‐ray diffraction, Fourier transform infrared spectroscopy, and scanning electron microscopy. The results indicated that by increasing the SS content, the compressive strength of the CNSCM exhibited an increasing trend, followed by a decreasing trend. The optimal content was 8%. Humidity was identified as another factor affecting compressive strength, which reached 17 MPa after curing for 28 d under standard conditions. A decrease in humidity could improve the compressive strength of the material. The main hydration reaction products of the CNSCM were C‐S‐H gel, Fe (OH) 2 or Fe (OH) 3 gel, and CaCO 3 .
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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) | 0.003 | 0.001 |
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".