Role of chain dynamics and topological confinements in cold crystallization of <scp>PLA</scp>‐clay nanocomposites
Bibliographic record
Abstract
The effects of the addition of organically modified nanoparticles on molecular dynamics, and subsequently, crystallization parameters were investigated using temperature modulated differential scanning calorimetry, dynamic mechanical analysis, and rheological measurements. Cold crystallization was observed to occur, at higher temperatures compared to the pure sample, due to the formation of topological constraints and the increase of the rigid fraction of amorphous chains, trapped in the polymer‐particle interphase. It was also found that in the nanocomposites, the competition between the heterogeneous nucleating role of the nanoparticles and the restricted morphology effect on crystallization kinetics depends on devitrification of the rigid amorphous chains, at the isothermal crystallization temperature, and during nonisothermal crystallization. It was illustrated that the fraction of rigid amorphous chains, extended at the crystal‐amorphous interphase, was enhanced by the increase of the overall crystallization rate. Moreover, the internal structure of the crystalline domains was revealed through small angle X‐ray scattering. A correlation function was applied to SAXS data to estimate the long period and the thickness of alternatively stacked lamellae. It was demonstrated that the long period depends on the overall crystallization rate, which was found to be influenced by nanoparticle content. In contrast, the lamellae thickness did not show a noticeable variation with the addition of the nanoparticles. POLYM. ENG. SCI., 55:1310–1320, 2015. © 2015 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 | 0.000 | 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 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".