In situ probing of the crystallization kinetics of rr-P3HT on single layer graphene as a function of temperature
Bibliographic record
Abstract
We studied the molecular packing and crystallization of a highly regio-regular semiconducting polymer poly(3-hexylthiophene) (P3HT) on both single layer graphene and silicon as a function of temperature, during cooling from the melt. The onset of crystallization, crystallites' size, orientation, and kinetics of formation were measured in situ by synchrotron grazing incidence X-ray diffraction (GIXD) during cooling and revealed a very different crystallization process on each surface. A favored crystalline orientation with out of plane π-π stacking formed at a temperature of 200 °C on graphene, whereas the first crystallites formed with an edge-on orientation at 185 °C on silicon. The crystallization of face-on lamellae revealed two surprising effects during cooling: (a) a constant low value of the π-π spacing below 60 °C; and (b) a reduction by half in the coherence length of face-on lamellae from 100 to 30 °C, which corresponded with the weakening of the 2nd or 3rd order of the in-plane (k00) diffraction peak. The final ratio of face-on to edge-on orientations was 40% on graphene, and 2% on silicon, revealing the very different crystallization mechanisms. These results provide a better understanding of how surfaces with different chemistries and intermolecular interactions with the polythiophene polymer chains lead to different crystallization processes and crystallites orientations for specific electronic applications.
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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".