Phenomenological Models of Diffusivities Based on Local Composition
Bibliographic record
Abstract
In phenomenological models, diffusivity is at least a function of composition and the diffusivities at infinite dilution. An additional parameter , which can be determined by diffusivity in midpoint, are specially brought forward as token of fractional friction related with the interactions of same molecules in this paper, to extrapolate a new correlative equation for the mutual Maxwell-Stefan diffusivities. Furthermore, the correlative equation can be extended to calculate diffusivities in multicomponent mixtures based on binary data alone. The rate of random motion of molecule i, which determine diffusional behavior, consider to be depended on the local composition (xji), comparatively on the average mole fraction (xi and xj), and local composition is calculated by binary thermodynamic parameters available, such as Wilson and NRTL parameters. The theoretical calculations are evaluated with published experimental data. The total average relative deviation of predicted values with respect to experimental data is 4.43% for 17 binary systems. And the M-S diffusivities in a three-component liquid system are regarded as binary coefficients, the predictive results also agree with the experimental data. Results indicate that the model with additional coefficients is superior to currently used Darken methods, especially for systems of polar organic-water and those containing associative component. Keywords： diffusivity, diffusion, phenomenological models, Maxwell-Stefan’s law
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.000 | 0.004 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".