Thiophene-Fused Borepins As Directly Functionalizable Boron-Containing π-Electron Systems
Bibliographic record
Abstract
Synthetic protocols were developed for the gram-scale preparation of two isomeric dithienoborepins (DTBs), boron-containing polycyclic aromatics featuring the fusion of borepin and thiophene rings. DTBs exhibit reversible cathodic electrochemistry and boron-centered Lewis acidity in addition to enhanced electronic delocalization relative to benzo-fused analogues. Boron's precise position within the conjugation pathway of DTBs significantly affected electronic structure, most clearly demonstrated by the variation in spectroscopic responses of each isomer to fluoride ion binding. In addition to excellent stability in the presence of air and moisture, DTBs could also be subjected to electrophilic aromatic substitution and metalation chemistry, the latter enabling the direct, regiospecific functionalization of the unsubstituted thiophene rings. Subsequent tuning of molecular properties was achieved through installation of donor and acceptor π-substituents, leading to compounds featuring multistep electrochemical reductions and polarizable electronic structures. As rare examples of directly functionalizable, π-conjugated, boron-containing polycyclic aromatics, DTBs are promising building blocks for the next generation of organoboron π-electron materials whose development will demand broad scope for molecular diversification in addition to chemical robustness.
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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 | 0.001 |
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".