Additions of Salt Cake and KAlF <sub>4</sub> from Aluminum Production to Steelmaking Slags
Bibliographic record
Abstract
Abstract Fluorspar, a mineral primarily composed of CaF 2 is the most commonly used slag fluidizer in steelmaking. Due to increasing costs for fluorspar steelmakers are seeking alternative means of achieving slag fluidity. The research has concentrated on other minerals or the wastes of other high temperature operating industries. A promising alternative to fluorspar has been identified in a previous work from this laboratory which is the salt cake from secondary aluminum production such as the flux in remelting aluminum scrap and dross. This material is widely available and also considered toxic (meaning that use in steelmaking helps to reduce environmental impacts from disposal). The present work is an investigation of the viability of using mixtures of salt cake and KAlF 4 in slag-fluidizing applications by measurements of viscosity and weight loss at high temperatures (to evaluate whether large amounts of potentially harmful gases are formed). In addition, characterization of raw materials and melted slags has been performed. In terms of fluidity the mixtures of aluminum salt cake and KAlF 4 are qualified for use as fluidizers. The results of the present study will be used to design plant trials.
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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 | 0.001 | 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".