Exploring glass transition in polyethylene via molecular dynamics: From bulk to isolated chain
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
: In this study, we investigate the glass transition behavior of polyethylene (PE) chains in the bulk and isolated, using molecular dynamics (MD) simulations. Leveraging both simulated dilatometry, Arrhenius analysis, and a procedure based on the evolution of percentage of trans states, we identified three distinct regimes with different behaviors, proposing a glass transition domain delimited by glass transition temperatures ( and delimiting the transition domain, and extracted from dilatometry) for bulk polymers. The two latter methods were then used to characterize this domain for isolated chains, allowing us to compare with data stemming from the bulk polymer. Our findings reveal that T g s of an isolated chain are generally lower than that of the bulk except for which remains unchanged. This observation aligns with previous experimental and simulation studies. The study further investigates the dynamic and static flexibilities of the polymer, correlating the potential energy barriers associated with dihedral transitions to the observed and values. We propose that is an intrinsic property of the polymer, as it depends on the potential energy barrier required to escape from the trans state. In contrast, is influenced by more complex interactions and is lower for the isolated chain.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it