New Cured-In-Place Gasket Technology Using UV-Cured High Performance Elastomers
Bibliographic record
Abstract
Cured-In-Place Gaskets have been demonstrated as a viable, economical sealing choice for a number of automotive applications. Historically, this market has been limited by material choice, which has almost exclusively been the domain of liquid silicone (VMQ) and polyurethane (PU). New technology has been developed which expands the choices of elastomers that can be used in Cured-In-Place gaskets. Seals made with high performance elastomers such as ethylene acrylic elastomers (AEM) and fluoroelastomers (FKM) can now take advantage of this “efficient” process. These materials can be robotically dispensed using equipment similar to what is used in the “hot melt” adhesives industry and then cured with a UV-light source. These UV-cured seals exhibit mechanical properties similar to what their traditionally cured alternatives show and still maintain the excellent heat and fluid resistance of these polymers. These compounds have little or no filler and no adhesive is used, making them ideal choices for applications that require a low level of contamination. This technology has been shown to work with a number of elastomeric families of polymers. In this paper this new technology will be introduced and relevant properties of UV-cured elastomers will be reviewed.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".