Generic van der Waals equation of state and theory of diffusion coefficients: Binary mixtures of simple liquids
Bibliographic record
Abstract
A free volume theory of diffusion coefficients is formulated for binary mixtures of simple liquids. The free volume is defined by means of the generic van der Waals equation of state for mixtures, which is developed in this work, and computed in terms of the pair correlation function obtained by means of Monte Carlo simulations with a square-well potential model. The free volume thus computed is used to investigate the composition and temperature dependence of the binary diffusion coefficient of argon–krypton mixtures as well as the tracer diffusion coefficients of argon in liquid nitrogen and krypton in liquid argon. The present theoretical predictions compare very well with the experimental or simulation results available in the literature. The size and mass dependence of the ratio of the tracer diffusion to the solvent self-diffusion coefficients is also presented. This ratio is found to be almost independent of temperature and density. It therefore can be used to calculate the tracer diffusion coefficient from the self-diffusion coefficient and vice versa.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".