The Effect of Sulfur Concentration in the Metal on the Mass Transfer of Phosphorus in Bloated Metal Droplets
Bibliographic record
Abstract
In Basic Oxygen Steelmaking, metal droplets created by the impact of the oxygen jet will swell due to internal decarburization when they react with oxidizing slag in the emulsion zone. In this study, the dephosphorization behavior of bloated metal droplets containing different sulfur concentrations is investigated in the temperature range from 1813 to 1913 K using X‐ray fluoroscopy coupled with constant volume pressure change measurements and chemical analysis of quenched samples. The results show that higher sulfur droplets (>0.017 wt%) have a much longer incubation period for swelling than those with lower sulfur (<0.017 wt%). Due to this different swelling behavior, the dephosphorization rate for high sulfur droplets is found to be not heavily affected by the experimental temperature compared to the case of lower sulfur droplets. Employing a mixed control model including mass transfer and chemical reaction, the effect of temperature on dephosphorization kinetics is further discussed. The mass transfer coefficient in the metal, km, is found to increase slightly with increasing temperature for droplets with 0.021 wt% sulfur. It is also found that lower rates of CO formation result in less stirring in the droplet and lower mass transfer rates of phosphorus for high sulfur droplets.
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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".