Theoretical Investigation of Thermodiffusion (Soret Effect) in Multicomponent Mixtures
Bibliographic record
Abstract
Thermodiffusion is one of the mechanisms in transport phenomena in which molecules are transported in a multicomponent mixture driven by temperature gradients. Thermodiffusion in associating mixtures presents a larger degree of complexity than non-associating mixtures, since the direction of flow in associating mixtures may change with variations in composition and temperature. In this study a new activation energy model is proposed for predicting the ratio of evaporation energy to activation energy. The new model has been implemented for prediction of thermodiffusion for acetone-water, ethanol-water and isopropanol-water mixtures. In particular, a sign change in the thermodiffusion factor for associating mixtures has been predicted, which is a major step forward in modeling of thermodiffusion for associating mixtures. In addition, a new model for the prediction of thermodiffusion coefficients for linear chain hydrocarbon binary mixtures is proposed using the theory of irreversible thermodynamics and a kinetics approach. The model predicts the net amount of heat transported based on an available volume for each molecule. This model has been found to be the most reliable and represents a significant improvement over the earlier models. Also a new approach to predicting the Soret coefficient in binary mixtures of linear chain and aromatic hydrocarbons using the thermodynamics of irreversible processes is presented. This approach is based on a free volume theory which explains the diffusivity in diffusion-limited systems. The proposed model combined with the Shukla and Firoozabadi model has been applied to predict the Soret coefficient for binary mixtures of toluene and n-hexane, and benzene and n-heptane. Comparisons of theoretical results with experimental data show a good agreement. The proposed model has also been applied to estimate thermodiffusion coefficients of binary mixtures of n-butane & carbon dioxide and n-dodecane & carbon dioxide at different temperature. The results have also been incorporated into CFD software FLUENT for 3-dimensional simulations of thermodiffusion and convection in porous media. The predictions show the thermodiffuison phenomenon is dominant at low permeabilities (0.0001 to 0.01), but as the permeability increases convection plays an important role in establishing a concentration distribution. Finally, the activation energy in Eyring’s viscosity theory is examined for associating mixtures. Several methods are used to estimate the activation energy of pure components and then extended to mixtures of linear hydrocarbon chains. The activation energy model based on alternative forms of Eyring’s viscosity theory is implemented to estimate the thermodiffusion coefficient for hydrocarbon binary mixtures. Comparisons of theoretical results with the available thermodiffusion coefficient data have shown a good performance of the activation energy model.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".