Investigation of the density dependence of the shear relaxation time of dense fluids
Bibliographic record
Abstract
The shear relaxation time, a key quantity in the theory of viscosity, is calculated for the LennardJones fluid and fluid krypton. The shear relaxation time is initially calculated by the ZwanzigMountain method, which defines this quantity as the ratio of the shear viscosity coefficient to the infinite shear modulus. The shear modulus is calculated from highly accurate radial distribution functions obtained from molecular dynamics simulations of the LennardJones potential and a realistic potential for krypton. This calculation shows that the density dependence of the shear relaxation time isotherms of the LennardJones fluid and Kr pass through a minimum. The minimum in the shear relaxation times is also obtained from calculations using the different approach originally proposed by van der Gulik. In this approach, the relaxation time is determined as the ratio of shear viscosity coefficient to the thermal pressure. The density of the minimum of the shear relaxation time is about twice the critical density and is equal to the common density, which was previously reported for supercritical gases where the viscosity of the gas becomes independent of temperature. It is shown that this common point occurs in both gas and liquid phases. At densities lower than this common density, even in the liquid state, the viscosity increases with increasing temperature.Key words: dense fluids, radial distribution function, shear modulus, shear relaxation time, shear viscosity.
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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 | 0.001 | 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 | 0.001 |
| 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".