Investigation of the physico-technological features of the hydro-vacuum cleaning process for the high-entropy alloy CoCrFeNiMn produced from industrial ferroalloys
Bibliographic record
Abstract
This study reveals the hydro physical mechanism of hydro-vacuum, shockwave and cavitation-pulsation counter gravity flotational extraction of non-metallic micro inclusions inherent in the liquid high-entropy alloy CoCrFeNiMn (HEA) obtained by an original method of combined induction remelting of low- and carbon-free ferroalloys with an elevated content of target metals. The effectiveness of the hydro-vacuum technology of vertical suction, confuser-convective acceleration, and diffusion-hydro mechanical dispersion of an upward flow of molten metal superheated by 100–150 °C is theoretically substantiated and experimentally proven. It has been established that vortex-like radial twisting of tangentially directed cavitation currents in the thrust-forming high-speed annular flow of water-liquid-metal pulp formed in the process of counter-gravity acceleration, with subsequent asymmetric slamming of the caverns formed in it, is the main conditioning factor for generation of ultra-frequency shock waves of rarefaction and flotational supplanting of relatively light nonmetallic inclusions from atomised drop-liquid particles of HEA. The powder obtained by the proposed method, by its purity 98.7–99.4% and hardness 250–300 HV0.5, is practically identical to similar high-entropy materials synthesis,ed from pure metals. The findings can contribute to stimulating the development of the proposed cost-effective and easily scalable approach to the production and cleaning of HEAs of different systems.
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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 | 0.000 | 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".