Structural relaxation, viscosity, and network connectivity in a hydrogen bonding liquid
Bibliographic record
Abstract
In liquids, the ability of neighboring molecules to rearrange and jostle past each other is directly related to viscosity, the property which describes the propensity to flow. The presence of hydrogen bonds (H-bonds) complicates the molecular scale picture of viscosity. H-Bonds are attractive, directional interactions between molecules which, in some cases, result in transient network structures. In this work, we use experimental and computational methods to demonstrate that the timescale of H-bond network reorganization is the dominant dynamical timescale associated with viscosity for the case of the model H-bonding liquid n-methylacetamide (NMA). This molecule is a peptide analog which forms a transient linear H-bond network. Individual H-bond lifetimes and dynamical fluctuations were observed on the timescale of 1.5 ps, while collective motions and the longest lived population of H-bond partner lifetimes were observed on the order of 20 ps, in agreement with the Maxwell relaxation time. This identifies a mechanism which may aid in understanding the emergence of various complex phenomena arising from transient molecular structures, with implications ranging from the internal dynamics of proteins, to the glass transition, to better understanding the origins of the unique properties of H-bonding liquids.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".