Effect of [ <i>n</i> ]-Helicene Length on Crystal Packing
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Chiral π-conjugated organic molecules hold potential for emerging technologies as they are capable of introducing novel functionalities into electronic devices owing to their strong chiroptical properties. However, capitalizing on chiral molecules for electronic devices is reliant on their molecular packing─a factor that impacts their charge-transport properties. The solid-state behavior of molecules is sensitive to subtle differences in molecular interactions, chirality, and shape, but these relationships are not fully understood. Here, we employ crystal structure prediction (CSP) as a tool to probe the lattice-energy landscape for a family of chiral organic molecules: [ n ]helicenes, where n ranges from 3 to 12. Our results show excellent agreement between the CSP landscapes and experimentally reported structures. By analyzing the packing motifs within the polymorph landscapes, we begin to develop an understanding of how helicene length affects the shape and π–π stacking interactions seen in the polymorphs. Furthermore, we propose how helicene length can be used as a tool to design new functional organic electronics.
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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 | 0.001 | 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 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".