Synthesis and Aggregation Behavior of Chiral Naphthoquinoline Petroporphyrin Asphaltene Model Compounds
Bibliographic record
Abstract
Abstract The synthesis of structurally relevant compounds that model the chemical behavior and supramolecular aggregation of the asphaltenes, the most polar and metal‐rich fraction of heavy petroleum, has been extended to include fusions of important petroleum biomarkers. The synthetic protocol features a multicomponent reaction to form a dyad composed of a fused steroidal naphthoquinoline, followed by a pyrrole cyclocondensation reaction to incorporate the dyad into a chiral triad containing a NiII‐porphyrin substituent. This synthetic protocol has been used to prepare large molecules that represent both “continental” and “archipelago” models of asphaltene composition. The steroid–naphthoquinoline–porphyrin triads have been studied by UV/Vis and circular dichroism (CD) spectroscopies, and the results suggest that the naphthoquinoline core, a tetrahydro[4]helicene, adopts a helical conformation, producing a CD signal electronically related to the characteristic Soret absorption band of the porphyrin subunit. Finally, supramolecular aspects of asphaltene aggregation have been examined on a molecular level through analysis of axial coordination of pyridine to the Ni‐porphyrin. The relative affinity of pyridine for binding to the Ni center of the porphyrin is evaluated by comparing binding propensities in a series of sterically differentiated substituted porphyrins.
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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) | 0.000 | 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) | 0.001 | 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".