Aromaticity in pericondensed cyclopenta-fused polycyclic aromatic hydrocarbons determined by density functional theory nucleus-independent chemical shifts and the Y-rule — Implications in oil asphaltene stability
Bibliographic record
Abstract
The characterization of the stability of the fused aromatic region (FAR) in oil asphaltenes in terms of kinetic and thermodynamic stability is primary. Such an understanding is important if we are to get the optimal use from the heavy fraction of any crude oil. The FAR region is composed of pericondensed cyclopenta-fused polycyclic aromatic hydrocarbon compounds (CPPAHs) with N, S, and O heteroatoms. The Clar model, which states that the most important representation of a PAH is one having the maximum number of disjoint π-sextets, depicted by inscribed circles, and a minimum number of fixed double bonds, captures the essence of the kinetic and thermodynamic stability arguments. This model is readily employed for complex aromatics of the sort to be considered for asphaltenes. In the present research we prove that the aromaticity of CPPAHs can be assessed by using the qualitative easy-to-apply Y-rule. In the literature, it is proven that the Y-rule is applicable to elucidate the aromaticity of benzenoid PAHs and it has been validated for pericondensed benzenoid PAHs but not for pericondensed CPPAHs. Here, we verify that it is applicable for CPPAHs. The applicability of the Y-rule has been theoretically proven by comparing the π-electronic distribution obtained with it with the one obtained from nucleus-independent chemical shift (NICS) calculations at the density functional theory (DFT) level. The importance of doing this is that due to the polydispersity in the composition of the oil asphaltenes, and to understand their aromatic core structure, it is necessary to be able to asses the aromaticity of many cyclopenta-fused PAHs (possibly more than 500), of different sizes (up to 15 rings between hexagons and pentagons), and different spatial rearrangements in a quick but realistic and effective way. To try to do this with NICS will be very time consuming and computationally expensive, especially in the case of big systems.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".