The Effect of Solution Conditions on the Driving Forces for Self‐Assembly of a Pyrene Molecule
Bibliographic record
Abstract
) (Fp-pyrene) is soluble in DMSO and THF, but insoluble in water, methanol, and ethanol. The hydrophobic force drives the molecules' assembly into vesicles in THF/water. The π-π interaction of the pyrene groups subsequently occurred within the vesicular membrane. The assembly, however, is driven by the π-π interaction in DMSO/water (water content: 40-80 vol %) into membranes, which is attributed to the relatively higher degree of de-solvation (δ) of pyrene in DMSO. Further increase in δ (DMSO/90 vol % water) suppresses the π-π interaction and spherical particles are formed. On the other hand, the supersaturated solutions were prepared via a cycle of heating and cooling of Fp-pyrene in methanol or ethanol. Fp-pyrene aggregates into particles without the π-π interaction in the solutions with a lower degree of supersaturation (σ). In contrast, a higher σ induces the π-π interaction, which drives the assembly into nanotapes. The π-π interaction is a conditional effect depending on the solution conditions, which can be adjusted for the synthesis of nanostructures assembled from the same aromatic molecule.
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".