Validation of the Yen–Mullins Model of Athabasca Oil-Sands Asphaltenes using Solution-State <sup>1</sup>H NMR Relaxation and 2D HSQC Spectroscopy
Bibliographic record
Abstract
The hierarchical Yen–Mullins model of Athabasca oil-sands asphaltene is strongly supported by solution-state 1 H NMR relaxation measurements and 2D HSQC-NMR spectroscopy. For the first time, the 1 H T 1 and T 2 relaxation behaviors of specific sites in asphaltene molecules have been studied, and it is shown that the relaxation behavior is in agreement with the hierarchical molecule-nanoaggregate-cluster model proposed by Mullins ( Energy Fuels 2012, 26, 3986). The size of the asphaltene nanoaggregate clusters was determined from the biexponential T 2 relaxation behavior of the 1 H nuclei. Assignment of overlapping 1D NMR signals was made possible via HSQC methods, where elusive hallmark long-range aromatic–aliphatic heteronuclear correlations were observed. Alicyclic structures were shown to be more closely associated with the aromatic core than what has been proposed for most archipelago-type structures. The NMR parameters obtained from the deconvolution analysis indicate an average of 6–7 pericondensed aromatic rings present in each molecule, in agreement with the island model. The average molecular weight was determined at ∼720 g/mol, which would be typical for island model structures, hence lending strong support for the Yen–Mullins 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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".