Synthesizing Nanostructured Ni<sub>75</sub>Mg<sub>16.66</sub>Y<sub>8.34</sub>(at%) Powder by Solid State Reaction and Mechanical Milling
Bibliographic record
Abstract
In this study, nanostructured Ni75Mg16.66Y8.34 (at%) catalyst powder was prepared using two methods. In method one, the pure elemental powders were subjected to high energy ball milling for 5 to 25 h with a ball to powder weight ratio of 20. In method two, the pure elemental powders were pressed, heat treated at 800°C for 8 h (solid state reaction); then, they were ball milled for 2, 7.5 and 10 h, similarly to the first method. Finally, morphology, phases, particle size, crystallite size, and lattice strain values of the prepared powder alloys were determined by X-ray diffraction (XRD) and scanning electron microscope (SEM) methods. The XRD patterns showed that the Mg2Ni9Y ternary intermetallic phase was not formed in the sample prepared by method one; however, that was formed in the samples prepared by the second method. The required milling time for preparing the samples with the same powder specifications by method two was about 50% less than the time required by method one. It was found that the Ni75Mg16.66Y8.34 (at%) powder with smaller particle size, smaller crystallite size, and higher lattice strain values could be prepared by combining solid state reaction and mechanical milling processes.
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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".