Properties investigation of recycled polylactic acid reinforced by cellulose nanofibrils isolated from bagasse
Bibliographic record
Abstract
In this research, an industrial‐scale approach was developed for preparing bio‐nanocomposites from recycled polylactic acid (rPLA) and cellulose nanofibrils (CNFs). In this regard, several steps were conducted consisting of extracting CNFs, preparing CNF/rPLA master batch, and melt compounding which was finally followed by compression molding. The influence of adding CNFs on rPLA properties was investigated by morphological, mechanical, thermo‐mechanical, and degradability studies. Images from scanning electron microscopy (SEM) revealed an increase in the fracture surface roughness of rPLA after adding CNFs. In addition, compared to unreinforced rPLA, the modulus and strength of bio‐nanocomposites containing 3 wt% CNFs were enhanced from 527.5 and 23.9 MPa to 716.5 and 32.6 MPa, respectively. Other mechanical properties including elongation at break and work of fracture were decreased by 35.5 and 33% at this CNF percentage. Furthermore, the storage modulus, obtained from dynamic mechanical analysis (DMA), was significantly improved from 1,024 to 8,214 MPa after adding 3 wt % CNF. Similarly, at this CNF percentage, glass transition temperature ( T g ) was enhanced from 59.5 to 64°C. According to biodegradation study, the highest biodegradability resistance was also obtained for bio‐nanocomposite containing 3 wt % CNF. POLYM. COMPOS., 39:3740–3749, 2018. © 2017 Society of Plastics Engineers
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 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".