Application of Optical Floating Zone Method to Dissolution Kinetics of Inclusions in a Steelmaking Slag
Bibliographic record
Abstract
The dissolution kinetics of micro‐particles (inclusions) in steelmaking slags is investigated using the high temperature confocal scanning laser microscope (HT ‐ CSLM). However, these studies focus on the limited type of inclusions such as Al2O3, SiO2, MgO, CaO, and MgAl2O4. To experimentally study the removability of various problematic inclusions that are not available in the market, optical floating zone and sintering techniques are presented here for the production of high purity micro‐particles. The syntheses of TiO2 and Al2TiO5 inclusions are employed to demonstrate the advantages and potential of both techniques. These inclusions are then dissolved in the steelmaking slags using CSLM at 1430 °C. In situ observation shows that there is gas evolution during the reaction between slag and Al2TiO5 particles prepared by both techniques. However, the gas evolution is more rapid during the dissolution of particles prepared by sintering and hinders in situ observations and measurements. The optical floating zone technique is capable of preparation of micro‐particles with high purity and less porosity. At 1430 °C, the Al2TiO5 particles do not dissolve at all, whereas TiO2 particles completely dissolve in 200 s.
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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".