Chromium Oxide Reduction from Slag by Silicon and Magnesium
Bibliographic record
Abstract
Experimental and theoretical studies were performed in order to estimate the effect of the basicity of the slag as well as the amount of reducing agents on the reduction of chromium oxide from a slag in contact with molten steel at 1600 °C. The aim of this work was to compare the efficiency of magnesium and silicon as reducing agents of Cr 2 O 3 . The slag system contained CaO, MgO, SiO 2 , CaF 2 and Cr 2 O 3 together with Fe‐alloys (Fe‐Si or Fe‐Si‐Mg). The maximum Cr yield was about 81% with Fe‐44%Si‐9%Mg and 88% with Fe‐75%Si. That means that the reducing effect of Mg was much better than that of Si. Some experiments were conducted to study the effect of initial Cr in steel on the chromium oxide reduction reaction. Three initial Cr contents were tested (0.15, 2 and 4 mass%). It was found that chrome was partially bound into stable spinel phase MgO·Cr 2 O 3 in the final slag. Thermodynamic estimations were made to determine the effect of process temperature, slag basicity and the amount of reducing agents in the slag on the Cr recovery. The efficiency of Cr reducing agents increased in the order: Si, Al, Ca and Mg. The Cr yield increased with slag basicity and amount of reducing agents.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".