Supramolecular Assembly Model for Aggregation of Petroleum Asphaltenes
Bibliographic record
Abstract
The components of petroleum asphaltenes exhibit complex bridged structures comprising sulfur, nitrogen, aromatic, and naphthenic groups linked by alkyl chains. These components aggregate in crude oil and toluene over a wide range of concentrations and temperatures, exhibit strong adhesion to a wide range of surfaces, occlude components that are otherwise soluble, are porous to solvents, and are elastic under tension. None of these properties is consistent with an architecture dominated only by aromatic stacking by electrostatic and/or van der Waals forces, often called π–π stacking. We propose an alternate paradigm based on supramolecular assembly of molecules, combining cooperative binding by Brønsted acid–base interactions, hydrogen bonding, metal coordination complexes, and interactions between cylcoalkyl and alkyl groups to form hydrophobic pockets, in addition to aromatic π–π stacking. A range of architectures are suggested, which almost certainly occur simultaneously, including porous networks and host–guest complexes. The latter may include organic clathrates, in which occluded guest molecules stabilize the assembly of a cage, as methane does in gas hydrates. This model has a number of implications for analysis of asphaltene mixtures and predicting asphaltene phase behavior and transport properties.
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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 | 0.000 |
| 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 | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".