The Prediction of Viscosity for Mixtures Using a Modified Square Well Intermolecular Potential Model
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Bibliographic record
Abstract
Abstract In the chemical and process industries, the viscosity of pure components and mixtures is a required fluid property in the areas of hydraulics, heat transfer, and mass transfer. Hence, there is a definite need for a reliable and accurate method for viscosity calculations of mixtures that is applicable over the entire density range for a wide variety of components. The Modified Square Well Intermolecular Potential viscosity model developed by Monnery et al. (1998) to predict pure component viscosities offers a good compromise between theory and applicability. In this work, the square well model is extended to mixtures. A total of 276 binary mixtures, including non‐polar and polar components, were used to regress binary interaction parameters for the mixing rules. The predicted mixture viscosities had a 10% average absolute deviation for the entire density range that included the gas, liquid, and dense phases.
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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