Cryogenic Abrasive Jet Machining of Polydimethylsiloxane and Polytetrafluoroethylene at Different Temperatures
Bibliographic record
Abstract
The temperature dependence of the solid particle erosion of polydimethylsiloxane (PDMS), polytetrafluoroethylene (PTFE) and high carbon steel using aluminum oxide particles was investigated. The most efficient machining of PDMS occurred at approximately -178°C, at angles of attack between 30° and 60°. Although it was demonstrated that PDMS could be machined at temperatures above its glass transition, the erosion rate increased by a factor of more than 10 when the machining temperature was below this point. The maximum erosion in PTFE occurred at the coldest temperature of -177°C between the angles of 30 and 90°. This scenario improved the erosion rate by more than a factor of five. The erosion rate in high carbon steel was increased approximately twofold when lowering the temperature from 17°C to -177°C. The surface evolution results presented can be used to predict feature shapes both polymers while minimizing cooling costs, minimizing mask wear or maximizing substrate erosion.
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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".