Crystal Engineering in Oligorylenes: The Quest for Optimized Crystal Packing and Enhanced Charge Transport
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide The crystal structures of organic semiconductors are critical when they are integrated into optoelectronic devices, such as organic field-effect transistors (OFETs). In this study, we introduce a crystal engineering approach that leverages weak, nondirectional dispersion forces and steric effects, working together to govern the molecular packing. We investigated how the substitution at the peri-position affects the crystal structure in a series of oligorylene molecules. Upon elucidation of the crystal structures, we found a distinct difference between symmetrical and unsymmetrical derivatives. The unsymmetrical derivatives are prone to forming a sandwich herringbone (SHB) motif, while symmetrical derivatives exhibit a typical herringbone (HB) motif. In most of the rylene derivatives, substitutions at the peri-position triggered an “end-to-face” orientation within the HB structure, rather than an “edge-to-face” orientation, which occurs more often. Results from the Hirschfeld surface analysis provide evidence that the “end-to-face” orientation promotes C–H–π interactions between terminal methyl groups and the π-core of the molecules. While these C–H methyl ---π interactions contribute to the overall stability of the packing structure, they remain ineffective in enhancing the charge transport properties. In contrast, a particular derivative, tetramethyl perylene ( TMP ), exhibits a HB structure with an edge-to-face orientation, promoting both C–H---π and π---π interactions. These interactions are crucial for improving the charge carrier mobility, as evidenced by mobility values. For TMP, we could obtain the mobility value of 0.05 cm 2 V –1 s –1 in OFETs, whereas a slightly higher mobility of 0.2 cm 2 V –1 s –1 was observed with Field-Induced Time-Resolved Microwave conductivity (FI-TRMC) technique.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".