Role of Naphthenic Acids in Controlling Self-Aggregation of a Polyaromatic Compound in Toluene
Bibliographic record
Abstract
In this work, a series of molecular dynamics simulations were performed to investigate the effect of naphthenic acids (NAs) in early stage self-assembly of polyaromatic (PA) molecules in toluene. By exploiting NA molecules of the same polar functional group but different aliphatic/cycloaliphatic nonpolar tails, it was found that irrespective of the presence of the NA molecules in the system, the dominant mode of π-π stacking is a twisted, offset parallel stacking of a slightly larger overlapping area. Unlike large NA molecules, the presence of small NA molecules enhanced the number of π-π stacked PA molecules by suppressing the hydrogen bonding interactions among the PA molecules. Smaller NA molecules were found to have a higher tendency to associate with PA molecules than larger NA molecules. Moreover, the size and distribution of π-π stacking structures were affected to different degrees by changing the size and structural features of the NA molecules in the system. It was further revealed that the association between NA and PA molecules, mainly through hydrogen bonding, creates a favorable local environment for the overlap of PA cores (i.e., π-π stacking growth) by depressing the hydrogen bonding between PA molecules, which results in the removal of some toluene molecules from the vicinity of the PA molecules.
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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".