Carded Recycled Carbon Fiber Mats for the Production of Thermoset Composites via Infusion/Compression Molding
Bibliographic record
Abstract
The use of carbon fiber reinforced thermoset composites has doubled in the last decade raising questions about the waste generated from manufacturing and at end-of-life, especially in the aircraft industry. In this study, 2.5 cm long carbon fibers were recovered from thermoset composite waste using a commercial scale pyrolysis process. Scanning electron microscopy, density measurements, single filament tensile testing as well as micro-droplet testing were performed to characterize the morphology, mechanical properties, and surface adhesion of the fibers. The recycled fibers appeared to be mostly undamaged and clean, exhibiting comparable mechanical properties to virgin carbon fibers. A carding process followed by an ultrasound treatment produced randomly aligned recycled fiber mats. These mats were used to fabricate composite plates, with fiber volume fractions up to 40 %, by infusion / compression molding. The mechanical properties of the plates were evaluated by tensile and flexural testing, and were found to be comparable to an equivalent containing virgin carbon fibers.
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".