Carbon fibre functionalization by plasma treatment for adhesion enhancement on polymers
Bibliographic record
Abstract
Current technological demands are increasingly stretching the properties of advanced materials to allow them to make them suitable for more severe or extreme conditions, whilst simultaneously seeking cost-effective production processes and final products. Composites based on carbon fibre (CF) are a hot topic in this field. In order to increase the CF adhesion to polymers, surface functionalization is needed. However different techniques can lead to different behavior of the treated surfaces. In the framework of the EU MODCOMP project (contract 685844), aimed to develop novel fibre-based materials for technical, high value, high performance products for nonclothing applications, CF plasma functionalization is identified as a critical step in order to increase polymer adhesion in final products. Here we show the effect of different plasma functionalization on CF. XPS, Raman and FESEM investigation will highlight the difference between these plasma treatments. The impact of these differences on the final products will be thoroughly discussed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".