In situ solidification of eutectic Al-33wt%Cu droplets
Bibliographic record
Abstract
Abstract Al-33wt%Cu eutectic droplets were rapidly solidified using Impulse Atomization, a drop tube technique. The samples were then processed in situ in an SEM using an HTN-0101 MEMS heating chip manufactured by Norcada. The temperature of the chip, as well as the heating and cooling rates, can be easily set using the chip’s control software, allowing for heating and cooling rates as fast as 1000°C/second. The droplets were heated above the eutectic melting temperature. Thanks to the oxide skin, the droplets retained their spherical shape, which allowed in situ solidification experiments. The live feed of the surface of the droplet obtained with the SEM was recorded during the experiments alongside the temperature-time profile. Various cooling rates were imposed and the liquid samples were shown to undercool prior to solidification. The resulting eutectic morphologies and spacings were then analyzed as a function of the cooling rates and undercoolings.
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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) | 0.002 | 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".