Asphaltene Molecular Representation: Impact on Aggregation Evaluation
Bibliographic record
Abstract
Molecular dynamics simulations were used to evaluate the effect of the asphaltene molecular representation on calculations of the aggregate size and aggregation behavior of asphaltene/solvent systems.Three different asphaltene representations were studied, namely, a mixture of four molecules, an island-type molecule and an archipelago-type molecule.Calculations were conducted for pure asphaltene systems and in solutions of n-heptane and toluene.For pure asphaltene systems, the island-type representation allows for the formation of extremely large aggregates, whereas for the mixture and archipelago representations, the aggregates contained up to four molecules.For asphaltene/solvent systems, the mixture representation was consistent with the expected solubility behavior of asphaltenes in both n-heptane and toluene.With this representation, the final configuration in n-heptane consisted of up to fourmolecule aggregates, whereas in toluene, the observed aggregates were dimers, at most.The structural configuration of the island-type molecule misrepresented the aggregation behavior of the asphaltenic phase.The representation of the asphaltene phase, exclusively with the archipelago architecture, also fails to correctly describe the asphaltene aggregation since almost no aggregation was observed.In n-heptane, the asphaltene aggregates were compact and stable with time, and their behavior resembled that of solid particles suspended in a fluid phase.In toluene, the aggregates were of a porous nature, forming viscoelastic networks and reducing the mobility of the fluid phase.The results indicate that the mixture representation is a more appropriate choice for the evaluation of asphaltenic system behavior.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".