Hydrated aluminum powder for direct alloying of steel and alloys - challenges of the future
Why this work is in the frame
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Bibliographic record
Abstract
The presented study considers and substantiates the possibility of increasing the efficiency of the technology of out-of-furnace, direct alloying of steel and alloys, through the combined use of hydrogen - and aluminothermic methods of reducing target metals from metal-oxide ore or technogenic powdered materials. To achieve this goal, it is proposed to use hydrogenated aluminum powder (1-5% AlH3), obtained as a result of hydro-vacuum dispersion of molten secondary aluminum, as a reducing agent. The morphology of the obtained powder particles containing different allotropic modifications of aluminum hydride is shown. Chemical features and advantages of the proposed process are discussed. The practical value and perspectivity of the development of this approach are argued.
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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 it