The effects of recycling on the structure and properties of carbon nanotube‐filled polycarbonate
Bibliographic record
Abstract
Sustainable manufacturing processes are becoming more important in industrial practice. A critical part of the manufacturing process is understanding the recycling behavior of nanocomposite materials, particularly as more recycled plastic nanocomposites are entering the market for a variety of different applications. A common method to recycle thermoplastic composites is by melting and remolding, which often leads to decreased mechanical properties. This work was conducted to investigate the effect of nanofillers on the recycling behavior and structure–property relationships of carbon nanotube (CNT)‐filled polycarbonate (PC). Materials were recycled by repeated injection molding and granulating up to twenty cycles. The effect of recycling on chemical, rheological, and mechanical properties was investigated. The results indicated a general decrease in melt viscosity and mechanical properties (with the exception of Young's Modulus). The CNT‐filled PC shows less resistance to recycling compared to neat PC. POLYM. ENG. SCI., 58:1278–1284, 2018. © 2017 Society of Plastics Engineers
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 | 0.001 |
| 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) | 0.000 | 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".