Thermal Plasma Synthesis of Different Alloys and Intermetallics from Ball Milled Al-Mo and Al-Ni Powder Systems
Bibliographic record
Abstract
Lightweight alloys have great importance for car manufacturers that aim to produce safer, lighter, and more environmentally friendly vehicles. As a result, it is essential to develop new lightweight alloys, with superior properties to conventional ones, respecting the demands of the market. Al and its alloys are good candidates for reducing the overall weight of vehicles. The objective of this research was to understand the possibility to synthesize different Al alloys and intermetallics by implementing the plasma system and using two different Al-Ni and Al-Mo powder systems. This was done by separately injecting non-reacted raw Al-Ni and Al-Mo composite powder systems into the plasma reactor. In the first step, the milling parameters were optimized to generate Al-Ni and Al-Mo composite powders, with sizes over about 30 µm, having, respectively, a homogeneous mixture of elemental Al and Ni, and Al and Mo in their particles. Each of the composite powders was then injected separately into the plasma system to provide conditions for the reaction of their elements together. The obtained Al-Ni and Al-Mo powders were then studied using different methods such as scanning electron microscopy, X-ray diffractometry, and energy dispersive X-ray analysis. Regardless of the initially used powder system, the obtained powders were consisting of large spherical particles surrounded by a cloud of fine porous particles. Different phases such as Al, AlNi3, Al3Ni2, and AlNi were detected in the particles of the Al-Ni powder system and Al, Mo, AlMo3, MoO3, and MoO2 in the Al-Mo powder system.
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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".