Comparing Soft Semicrystalline Polymer Nanocomposites Reinforced with Cellulose Nanocrystals and Fumed Silica
Bibliographic record
Abstract
This work compares solvent-cast poly(ethylene oxide) (PEO) nanocomposites reinforced with cellulose nanocrystals (CNCs) and fumed silica. Mechanical properties and crystallization behavior were investigated over a range of polymer molecular weights (10 000–100 000 g/mol) and particle loadings (1–10 wt %). Polymer adsorption to CNCs and fumed silica was found to alter PEO undercooling and inhibit crystal nucleation. Atomic force microscopy revealed PEO adsorbs to CNCs in a shish-kebab morphology that is readily incorporated into the crystalline domains of the polymer. Tensile testing and nanoindentation showed that Young’s modulus increased by more than 60% for CNC reinforced nanocomposites, and that the Halpin–Kardos model could effectively describe the mechanical properties. Fumed silica reinforced nanocomposites were fit to the Guth–Gold micromechanical model using effective particle volume fractions. Although only solvent-cast nanocomposites were investigated, this work provides new insight into the interactions that control dispersion, crystallization, and mechanical reinforcement.
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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".