Effect of Cr <sub>2</sub> O <sub>3</sub> Pickup on Dissolution of Lime in Converter Slag
Bibliographic record
Abstract
Abstract Application of low-nickel laterite ore containing chromium as charging material for ironmaking can reduce raw material costs, but result in an increase of chromium content in the hot metal and hence, Cr 2 O 3 content in the steelmaking slag, which subsequently causes many problems related to lime dissolution for the steelmaking operation. In this work, a rotating cylinder method was employed to study the effect of Cr 2 O 3 on lime dissolution in steelmaking slag. The lime dissolution mechanism, rate control step and affecting factors, including slag basicity, FeO x and B 2 O 3 content, and the formation of phases at reacted layer, were discussed. It was found that mass transfer was the rate control step in slag phase, increase of Cr 2 O 3 and slag basicity delayed lime dissolution due to the formation of high-melting temperature phases of FeO · Cr 2 O 3 spinel and 2CaO · SiO 2 at the slag/lime reacted interface. Addition of B 2 O 3 promoted lime dissolution and suppressed formation of FeO · Cr 2 O 3 spinel.
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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".