Bibliographic record
Abstract
Abstract Electron‐beam (E‐Beam) curing of an epoxy polymer matrix and its composite (reinforced with IM7 Carbon fibers) was studied using a cationic photoinitiator. Photoinitiator concentration, dose, and process temperature were varied to understand their influence on E‐beam curing. Optimal photoinitiator concentration was found to be 5 phr. The curing was due to a primary α reaction with a strong dependence on dose, and a secondary β reaction with a weak dependence on dose and a strong dependence on initiator concentration. The extent of cure increased rapidly with dose until 100 kGy and it approached a plateau value beyond 100 kGy. This plateau value corresponded to incomplete curing by 27% for resin and 22% for composite at a process‐temperature of 22°C. The causes for incomplete curing appear to be the secondary β reaction and diffusional limitation. Increase in process temperature resulted in higher extent of cure at a dose level. The material used in this study was also found to be thermally curable and the reaction onset temperature (measured in a DSC ramp experiment) reduced from about 150°C at 0 kGy to about 50°C at 30 kGy. This indicates that simultaneous thermal curing during E‐beam curing of resin and composite is possible. After thermal post‐curing, the T g of the E‐beam cured resin increased from 130°C at 200 kGy to a value greater than 370°C and the modulus decreased by 10%. The service temperature and the modulus of the 100% thermally cured resin and the thermally post‐cured (after E‐Beam irradiation) resin were comparable.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.003 | 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".