Fracture Toughness of Winding Carbon Plastics Based on Epoxy Matrices and Reinforced by Polysulfone Film
Bibliographic record
Abstract
In this work, the fracture mechanism of winding carbon-fiber-reinforced plastics (CFRPs) based on epoxy matrices reinforced by polysulfone film was investigated. Two types of polymer matrices were used: epoxy oligomer (EO) cured by iso-methyltetrahydrophthalic anhydride (iso-MTHPA), and EO-modified polysulfone (PSU) with active diluent furfuryl glycidyl ether (FGE) cured by iso-MTHPA. At the winding stage, the reinforcing film was placed in the middle layer of the CFRP. The fracture toughness GIR of the obtained CFRP was determined by the double-cantilever beam delamination method. Additionally, the effect of cyclic loading on the fracture toughness of CFRP reinforced with polysulfone film was investigated. It was shown that heterogeneous structures arising from the dissolution of the polysulfone film in the epoxy binder during the curing process increase the fracture toughness of CFRP from 0.5 kJ/m2 to 1.2 kJ/m2. Application of cyclic loads had little effect on the fracture toughness value. As a result of this study, it was revealed that the macrocrack propagates near the reinforcement layer along the diffusion zone, which has a phase organization of the type PSU matrix–EO dispersion.
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) | 0.001 | 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".