Ultrahigh<i>T</i><sub>g</sub>Epoxy Thermosets Based on Insertion Polynorbornenes
Bibliographic record
Abstract
Thermosetting materials (thermosets) are widely used organic materials derived from 3D-network forming monomers. Achieving high glass transition temperature ( T g ) thermosets is often a challenging task due to the complexity of designing efficiently and cheaply monomers which are rigid enough to prevent molecular motions within the thermoset. We report here a very simple route to prepare epoxy thermosets with T g as high as 350 °C, based on insertion polynorbornenes. The epoxy monomer (PNBE(epoxy)) is prepared by the epoxidation of poly(5-vinylnorbornene) obtained by catalytic insertion polymerization of 5-vinylnorbornene. PNBE(epoxy) can be cross-linked with simple biosourced compounds. Alternatively, polar insertion polynorbornene can also be used as cross-linker in the formulation of an epoxy resin, once again resulting in epoxy resins with T g higher than 300 °C and devoid of degradation at this temperature. Thus, this study clearly demonstrates the viability of catalytic polymerization to access epoxy thermosets with ultrahigh T g .
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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".