Experiments on Remelting and Solidification of Molten Metal Droplets Deposited in Vertical Columns
Bibliographic record
Abstract
Experiments were done to determine conditions under which vertical columns could be built by metal droplets landing sequentially on top of each other. Molten tin droplets (0.6mm diameter) were deposited using a pneumatic droplet generator on an aluminum substrate. The primary parameters varied in experiments were those found to most affect bonding between droplets: droplet temperature (250-345°C), substrate temperature (60-200°C), and deposition rate (1-15Hz). At lower deposition rates the substrate cooled down too much to induce remelting whereas at higher rates the tip of the column remained liquid and surface tension forces pulled it into a spherical mass. Assuming one-dimensional conductive heat transfer in a column a simple analytical model was developed to calculate the temperature at the tips of the column. It predicts that deposition frequency should be decreased as column height increases to hold the tip temperature constant. Droplet coalescence was best achieved when the tip temperature of a column was maintained at the melting point of the metal. Columns fabricated following the deposition frequency predicted by the model show good bonding between droplets and uniform diameter.
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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".