Novel Structural Aspects of Heavy-Crude-Derived Asphaltene Molecules for Investigating the Crude Mix Processability in Refinery Operation
Bibliographic record
Abstract
Summary In this paper, we investigate the role of asphaltenes derived from heavy crudes, which dictates the behavior of crude mix properties for hassle-free downstream refinery operation. Combined characterization techniques such as proton nuclear magnetic resonance (1H-NMR), cross-polarization magic-angle-spinning carbon-13 (CP/MAS 13C)-NMR, heteronuclear single-quantum coherence (HSQC), Fourier transform infrared (FTIR), thermogravimetric analysis (TGA), and X-ray diffraction (XRD) are used for the detailted study of Ratwai and Ras Gharib (RG)-derived asphaltenes to validate their structural role in selecting the optimal crude mix. As per our investigation, when the polyaromatic core of asphaltene structures are less substituted, the availability of aromatic hydrogen is more; it exhibits a stable crude mix as compared to heavy crudes that have more aromatic core substitution, despite the crudes possessing similar asphaltene content and physicochemical properties. This finding is further extended to West Canadian (WC) and Belayim (BL) heavy crudes for operational suitability. In this study, the key feature is to develop a CP/MAS 13C-NMR-based robust and quick characterization technique that could potentially become a prescreening method to assess crude oil compatibility and its various blend processability in the refinery system. Other characterization techniques, such as 1H-NMR, HSQC, FTIR, TGA, and XRD, would corroborate and confirm the reliability of the data obtained by CP/MAS 13C-NMR.
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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 | 0.001 | 0.001 |
| 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".