Anchored metallocene linear low‐density polyethene cellulose nanocrystal composites
Bibliographic record
Abstract
Abstract Cellulose nanocrystals (CNCs) were functionalized with different loadings of metallocene catalyst and subjected to in situ polymerization with ethene and 1‐hexene to yield linear low‐density polyethene (LLDPE) polymer matrix composites (PMCs). CNC content was determined with thermogravimetric analysis, confirming that the PMCs varied in their CNC loadings from 3.6 to 11.4 wt%. Differential scanning calorimetric, gel permeation chromatographic and NMR spectroscopic analyses revealed that the LLDPE (matrix) components of these PMCs shared similar physical properties. Dynamic mechanical analysis showed a general increase in the storage modulus of the PMCs with increasing CNC content. These relative differences in storage modulus were even more evident at higher temperatures. Uniaxial tensile testing of the PMCs found a notable increase in Young's modulus between the 3.6 wt% CNC PMC (240 ± 50 MPa) and the 11.4 wt% CNC PMC (391 ± 7 MPa), while the elongation at break decreased from the 3.6 wt% CNC PMC (400 ± 90%) to the 11.4 wt% CNC PMC (70 ± 10%). All PMCs showed similar yield strengths of ca 10 MPa. These mechanical properties showed that the method of dispersing CNCs in LLDPE reported herein affords the highest moduli reported thus far in LLDPE–CNC PMCs. The ability of the catalyst to incorporate co‐monomer olefins may allow for the incorporation of smart CNCs into ethane‐based polymers. © 2020 Society of Industrial Chemistry
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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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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; both teacher heads agree on what is shown here.
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".