The Degradation Prevention of Resin Materials for Semiconductor Manufacturing Equipment by Applying the Ultra-High Purity Gas Supply Technology
Bibliographic record
Abstract
The production (molding) guideline to realize ultraclean resin components for semiconductor equipment has been established. In this paper, we focused on the degradation behavior of resin materials for the purpose of reducing low-molecular-weight volatile contaminants concentration in resin components because the molding is carried out at high temperature and low-molecular-weight volatile contaminants are produced by thermal degradation. It was clarified that the oxygen concentration in high temperature molding environment is required to be below 1 ppm. And as the contact surface of the thermal degradation prevention for the resin material, the following surface materials are effective. 1) Passivation surface for a hydrocarbon resin. 2) Ni (nickel) surface for a fluorocarbon resin. As a result, we found the degradation prevention of the resin material can be realized until around 400 °C although the degradation was observed even under 200 °C if using current process condition. Therefore, low-molecular-weight volatile contaminants can be drastically reduced from resin components by using the guideline and ultraclean semiconductor equipment must be realized.
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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".