Effects of 2 nm size added heterogeneity on non-exponential dielectric response, and the dynamic heterogeneity view of molecular liquids
Bibliographic record
Abstract
To investigate how non-exponential response could vary under different conditions, we studied the effects of adding 2 nm size polyhedral oligomeric silsesquioxane (POSS) to diglycidyl ether of bisphenol-A, whose molecules have the same terminal (epoxide) dipoles as the tentacle-like side chains attached to the silsesquioxane core of the POSS molecule. Dielectric relaxation spectra show that, on initial addition, the POSS nano-heterogeneity decreases the non-exponential response parameter β, which is consistent with the dynamic heterogeneity view, but it also decreases the relaxation time τ(m), which is inconsistent with that view. The variations in β and τ(m) with the composition have a thermal equivalence. Despite the lack of translational diffusion required for dynamic heterogeneity, plastic crystals show non-exponential response and non-Arrhenius dynamics. Measurements of β and τ(m) seem more appropriate than using probe molecules or modeling nonlinear response data as a sum of linear responses for testing the dynamic heterogeneity view. Data on molecular liquid mixtures is not generally consistent with this view, and adding a solute does not always decrease β. Studies of mixtures of different size rigid molecules with identical dipolar groups, including polymers, may be useful for comparing the relative effects of temperature and molecular size on β and τ(m).
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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 | 0.001 | 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".