Exploring the Spatial Arrangement of <i>C</i><sub>s</sub>-Symmetric Boron Subphthalocyanine Hybrid Crystals by Tuning Arene–Perfluoroarene Interactions
Bibliographic record
Abstract
Manipulating the solid-state arrangements of organic electronic materials can profoundly impact the performance of the devices in which they are utilized. This study investigates how π–π interactions, notably arene-perfluoroarene (π H ···π F ) interactions, guide the crystal structures of boron subphthalocyanine (BsubPc) hybrid derivatives by leveraging the dual dipole moments inherent in F 8 BsubPcs and F 8 Bsub(Pc 2 –Nc 1 )s. We crafted a simple molecular design varying BsubPc-type hybrids by their axial moieties and number of peripheral arene sites while maintaining a consistent count of peripheral perfluoroarene (π–hole) sites. The geometric analyses revealed that solid-state arrangements of perfluorinated BsubPc-type hybrids can be purposefully altered by introducing substituents that promote π H ···π F stacking. We found that an additional fused benzene ring in the periphery introduced new stacking modes characterized by enhanced π–π overlap in F 8 Bsub(Pc 2 –Nc 1 ) hybrids compared to F 8 BsubPcs, producing one-dimensional slip-stacked columns directed by strong-to-moderate π H ···π F interactions. Incorporation of an axial phenol ligand in the F 8 Bsub(Pc 2 -Nc 1 ) architecture further directed new stacking patterns, transforming the framework of arene-perfluoroarene interactions from their axially halogenated counterparts. Long-range packing motifs, Hirshfeld surfaces, various solvent growth methods, serendipitous ring-opened structures, and halogen bonding were examined to understand these π H ···π F interactions further. This work realizes the control of BsubPc hybrid spatial arrangements through strategic π–π interactions and provides avenues for potentially improved electronic functionality via highly ordered close packing configurations.
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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".