Influence of nucleation and growth mechanisms on the heat deflection temperature of a reactively processed polypropylene nanocomposite
Bibliographic record
Abstract
Abstract The development of a reactively processed polypropylene nanocomposite (PPNC) with consequential improvements in the heat deflection temperature (HDT), Vicat softening temperature (VST), and crystallization peak temperature ( T c ) is reported herein. Neat PP without nanoclay was also reactively processed to elucidate the effects of fillers on the improvement in physical properties. The results show a considerable improvement in the HDT of PPNC (77.9 °C) compared to those of neat PP (62.6 °C) and reactively processed branched PP (BPP; 69.2 °C). Moreover, the T c of PP in PPNC improved by ~14% compared to that of neat PP. Various models of nonisothermal crystallization kinetics were employed to elucidate the nucleation and crystal growth mechanisms, and to correlate them with the observed HDT improvement in PPNC. Thermal transitions investigated by modulated differential scanning calorimetry explained the changes observed in the VSTs of all the samples. To the best of our knowledge, this is the first report on a significant improvement in HDT along with a marked increase in Tc . Such simultaneous improvements in HDT, VST, and T c are highly desirable for applications involving the use of PP‐based materials in rigid packaging.
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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".