Characteristics of Converter Slag Aggregates Reformed by $SiO_2$ added Reduction
Bibliographic record
Abstract
In order to maximize the recycling of converter slag to the more valuable fields, such as high quality aggregates for construction, cement industry and flux for ion making. It will be very important to control the compositions and properties of converter slag to suit the purpose of utilizastion. In this study, converter slag (STELCO, CANADA) was mixed with 5%~30% and 7% carbon, and then reduced at . After the reduction was completed, the reformed slags were cooled to room temperature in the furnace. All of the slags were then characterized using SEM-EDX, XRD and chemical analysis. Also the compressive strengths and densities of the reformed slags were measured to compare with natural aggregates. XRD analysis shows that th phases of reformed slags are changed from bredigite+merwinite mixed phases of 10% added reduction to akermanite phases of 20% and 30% added reduction. But the SEM-EDX analysis revealed that the phase distribution of the reformed slags was changed very sensitively and complicately depends on the change of slag compositions. And also the properties of reformed slags are changed very much depend on the phase distribution. About one third of Cadmium and on fifth of Vanadium are remained in reduction reformed converter slag. Another heavy metal elements such as cobalt, zinc, lead are removed up to more than 90-95% of original slag. The compressive strength and density of 25% added and reformed slag is very near to natural granite. This is superior more than 10% to Thyssen's added and oxidized converter slag aggregates.
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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) | 0.000 | 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".