Modeling and Prediction of Asphaltene Adsorption Isotherms Using Polanyi’s Modified Theory
Bibliographic record
Abstract
The deposition of asphaltenes is one of the most difficult problems to overcome in crude oil production and processing. The presence of asphaltenes in crude oil and, consequently, the adsorption and deposition of asphaltenes on rock surfaces, affects rock properties such as porosity, permeability, and wettability. In this study, a novel model for modeling and predicting adsorption isotherms of asphaltenes based on Polany’s modified theory is proposed. This approach enables prediction of adsorption isotherms at different temperatures (usually corresponding to reservoir temperatures), thereby improving our understanding of adsorption–equilibrium behavior at reservoir conditions, which should lead to reductions in experimental/analytical time and operation costs. The theoretical predictions of isotherms were validated successfully by determining the root-mean-square errors (RSM%) between data obtained from published literature and values predicted for asphaltenes and surfaces with differing chemical natures. The RSM% value is below 5% for all predictions. Additionally, the Dubinin–Astakhov model is used to correlate adsorption characteristic curves, resulting in RSM% values lower than 10%.
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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 | 0.000 | 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 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".