Bifunctional coupling agents for improved mechanical properties in fiberglass/polyethylene composites
Bibliographic record
Abstract
Abstract Two bifunctional compounds, 12‐azido‐1‐diazo‐2‐dodecanone (A) and 1‐diazo‐17‐octadecene‐2‐one (B), show an ability to act as coupling agents in fiberglass/polyethylene composites. Under appropriate conditions the diazoketone functional groups in both A and B react with hydroxyl groups on a fiberglass surface, whereas the azide group in A and the alkene group in B form bonds with the plastic matrix during processing. FTIR and NMR spectroscopy were used to study the decomposition of each of these compounds under heat and UV light. Each treatment resulted in a relatively fast decomposition of the diazoketone functional group, along with a slower reaction of the azide and alkene groups. Thus it was possible to react the diazoketone end of these compounds with a fiberglass surface, without affecting the azide or alkene functional groups on the other ends of the molecules. In samples of treated fiberglass containing compounds A or B and mixed by extrusion with polyethylene, the mechanical properties of the composites had improved properties over composites containing untreated samples of fiberglass. With A as the coupling agent, both the tensile properties and Izod impact showed changes that indicated that a bifunctional bridge was formed between the fiberglass and polyethylene phases. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 83: 2562–2578, 2002
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) | 0.001 | 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".