The effect of nanoparticle location and shape on thermal transitions observed in hydrated layer-by-layer assemblies
Bibliographic record
Abstract
Nanoparticles can have a profound effect on thermal transitions observed in polymer nanocomposites. Many layer-by-layer (LbL) assemblies contain nanoparticles for added functionality, but the resulting effects of nanoparticles on an LbL film's thermal properties are not known. Previously, we have shown that a nanoparticle-free LbL film containing strong polyelectrolytes, poly(diallyldimethylammonium chloride)/poly(styrene sulfonate) (PDAC/PSS), exhibited a single reversible thermal transition much like a glass-melt transition. In the work presented here, nanoparticles of either spherical (SiO2) or platelet (Laponite clay) shape are inserted at varying vertical locations throughout PDAC/PSS LbL films. Temperature-controlled quartz crystal microbalance (QCM-D) and modulated differential scanning calorimetry (MDSC) are applied, for which QCM-D proved to be more sensitive to the transition. All Laponite-containing films possess two thermal transitions. During growth, Laponite-containing films exhibit steady increases in dissipation, which is proposed to arise from mechanically decoupled regions separated by the Laponite nanoparticles. For SiO2-containing films, three transitions are detectable only when the SiO2 nanoparticles are placed in the middle of the film; no transitions are observed for SiO2 placed at the bottom or top, perhaps because of a weakening of the transition. The lowest transition is close in value to that of neat PDAC/PSS LbL films, and was assigned to a "bulk" response. The higher transition(s) is attributed to polymer chains in an interfacial region near the nanoparticle. We propose that nanoparticles restrict segmental mobility, thus elevating the transition temperature in the interfacial region.
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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".