Approval of production waste application as modifiers of aluminum alloys
Bibliographic record
Abstract
The results of a study of the effect of modifying additives from production waste of microsilica and corundum (Al2O3) powders on the structure and phase composition of the AD31 aluminum alloy are presented. In the conditions of the Karaganda Industrial University, melting of the AD31 aluminum alloy was carried out with the addition of 1% of waste powder of silicon production «Silicium Kazakhstan» (now «Tau-Ken Temir») (microsilica grade MK-85) and corundum powder (abrasive waste from cutting discs) as modifiers. The positive effect of modifying additives from industrial waste on the structure and properties of the alloy is revealed - the grain is refined, the phase composition changes, and the properties of modified aluminum alloys improve. To study the samples of the obtained modified alloys, the authors used the method of electron microscopy, as the simplest and fastest way to transfer information about the microstructure, elemental composition and distribution of elements in the sample volume. The conducted studies are relevant from the point of view of recycling waste from metallurgical industries, expanding the raw material base, as well as obtaining new materials with the required complex of functional properties
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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 | 0.001 |
| 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".