Effect of thermal annealing on the mechanical and thermal properties of polylactic acid–cellulosic fiber biocomposites
Bibliographic record
Abstract
ABSTRACT Polylactic acid (PLA) biocomposites were produced by a combination of extrusion and injection molding with three cellulosic reinforcements (agave, coir, and pine) and contents (10, 20, and 30%). In particular, some samples were subjected to thermal annealing (105 °C for 1 h) to modify the crystallinity of the materials. In all cases, morphological (scanning electron microscopy) and thermal (differential scanning calorimetry, dynamical mechanical thermal analysis) characterizations were related to the mechanical properties (Charpy impact, tensile and flexural tests). The results showed that annealing increased the crystallinity for all the materials produced, but different mechanical behaviors were observed depending on fiber type and content. For example, annealing increased the impact strength and flexural modulus of PLA and PLA biocomposites (agave, coir, and pine), while decreasing their flexural strength. But the main conclusion is that fiber addition combined with thermal annealing can substantially increase the thermal stability of the studied materials. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016, 133, 43750.
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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".