Research on inclusion control in saw wire steel through top slag refining
Bibliographic record
Abstract
Saw wire steel, a high-cost, quality-determining solar wafer consumable, has seen surging demand with China’s booming photovoltaic industry. However, its ultra-fine diameter and higher strength than tire cord steel greatly increases inclusion sensitivity and subsequent wire breakage, creating an urgent need for better inclusion control. This study investigated the evolution mechanisms of inclusions during its refining and the effects of top slag composition on molten steel and inclusions, using simulated top slag experiments and FactSage thermodynamic calculations. It shows that only Al2O3 content in inclusions remains stable while other components vary significantly, which makes simulated steel-slag experiments only applicable for guiding Al2O3 control in industry production. Increasing basicity or Al2O3 in slag raises [Al]s content in steel, which in turn leads to an augmentation in the Al2O3 content within inclusions. As the Al2O3 content in the inclusions increases, the proportion of low-melting-point inclusions first rises and then falls. Additionally, the deformability of the inclusions shows a distinct positive correlation with the proportion of low-melting-point inclusions. Under laboratory conditions, maintaining a slag basicity of 1 and an Al2O3 content of approximately 2% results in refined inclusions that exhibit the lowest melting points and optimal deformability.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".