Insights into the functionalities of cellulose acetate and microcrystalline cellulose on water absorption, crystallization, and thermal degradation kinetics of a ternary polybutylene succinate-based hybrid composite
Bibliographic record
Abstract
The kinetic behavior of a polymer material filled with natural and/or functionalized reinforcement can evolve regarding water absorption, crystallization, and thermal degradation (TD) processes. This study investigates the separate and combined influence of microcrystalline cellulose (MCC) and cellulose acetate (CA) on changes in the water absorption percentage (WAP), crystallization, and TD kinetics of polybutylene succinate (PBS) based materials. Disc-shaped neat PBS (n-PBS), binary (PBS/CA, PBS/MCC), and ternary hybrid (PBS/CA/MCC) specimens were produced via extrusion and injection. SEM observations of the hybrid micrographs revealed that MCC was whitish-coated by a CA layer that forms an "amphiphilic"-like co-continuous interphase between PBS and fibers. The CA encapsulation activity limited the hybrid’s WAP in the first week of water conditioning tests. In contrast, in the second immersion period, the WAP was increased by 19 % compared to that for PBS/MCC due to the synergistic activities of plasticized fillers. Avrami outcomes at 80°C showed that the hybrid’s half-crystallization time (t 0.5 ) increased by 64 % and 104 % compared to n-PBS and PBS/MCC, respectively, indicating that the enrobing CA layer restrained the slight nucleating effect of MCC fibers . The hybrid activation energy (E a ) values determined at lower conversion rates (α≤0.25) following the Flynn–Wall–Ozawa (F–W–O) model showed that they were up to 14 % higher than those for PBS/MCC, evidencing that CA delayed the TD of MCC fibers . For higher conversion rates (α≥0.5), the synergy of both fillers postponed the TD of PBS. The E a values obtained from the Kissinger method confirmed previous findings.
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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".