Degradation mechanisms of magnesia-carbon refractories in radiation heat-affected wall of steel electric arc furnace
Bibliographic record
Abstract
This study investigates the mechanisms underlying microstructural deterioration in processed MgO-C refractories from the radiation heat-affected wall of a steel EAF. X-ray tomography and scanning electron microscopy with energy-dispersive spectroscopy were employed to identify the thermally activated chemical, physical, and mechanical degradation phenomena and to evaluate their impact on microstructural evolution during the process. The results reveal that degradation is primarily driven by the development of a porous network surrounding coarse MgO grains (> ∼3 mm), with a strong correlation observed between MgO grain size and damage evolution. Larger grains tend to promote more extensive porous networks, which in turn facilitate oxygen ingress and accelerate carbon oxidation. The pronounced mismatch in thermal expansion coefficients between MgO grains and the carbon matrix contributes to crack formation and grain detachment. These findings provide deeper insight into the failure mechanisms of MgO-C refractories and inform strategies for optimizing refractory design to extend service life and enhance performance.
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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".