Mechanical and barrier properties of carbon nanotube reinforced PCL‐based composite films: Effect of gamma radiation
Bibliographic record
Abstract
Abstract Carbon nanotube (CNT) reinforced (0.05–0.5% by wt) polycaprolactone (PCL)‐based composites were prepared by compression molding. Addition of 0.2% CNT caused a 131% improvement of tensile strength (TS) of PCL films. The tensile modulus (TM) and elongation at break (Eb) of PCL were also significantly improved with the addition of CNT. The water vapor permeability of PCL was 1.51 g·mm/m2·day but 0.2% CNT containing PCL films showed 1.08 g·mm/m2·day. Similarly, the oxygen transmission rate (OTR) of PCL films was found to decrease with the addition of CNT. But, carbon dioxide transmission rate (CO2TR) of PCL film was improved due to incorporation of CNT. Effect of gamma radiation on PCL films and CNT reinforced PCL‐based composites were also studied. The TS of the irradiated (10 kGy) PCL films gained to 75% higher than control sample. The TS of the 0.2% CNT reinforced composite film was reached to 41 MPa at 15 kGy dose. The barrier properties of non‐irradiated and irradiated (10 kGy) PCL films and composites (0.2% CNT reinforced) were also measured. Both PCL films and composites showed lower values of WVP upon irradiation and indicated better water vapor barrier. The OTR and CO2TR of the irradiated (10 kGy) PCL films and composites were decreased compared to their counterparts. Surface and interface morphologies of the composites were studied by scanning electron microscopy. © 2012 Wiley Periodicals, Inc. J. Appl. Polym. Sci., 2013
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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".