Selective Tuning of the Band Gap of π‐Conjugated Dithieno[3,2‐<i>b</i>:2′,3′‐<i>d</i>]phospholes toward Different Emission Colors
Bibliographic record
Abstract
The systematic extension of the pi-conjugated system of strongly blue-luminescent dithieno[3,2-b:2',3'-d]phospholes has been investigated with the goal of obtaining different emission colors. Functionalization of the 2- and 6-position of the dithienophosphole scaffold with halogen substituents provided functional building blocks for subsequent cross-coupling experiments with various homo- and heteroaryls to selectively decrease the band gap of the materials. By this strategy materials with different emission colors ranging from green via yellow to orange could be obtained. This feature supports their suitability for organic light-emitting diodes with respect to an application in full-color flat-panel displays. The experimental results were nicely supported by theoretical DFT calculations providing a deeper understanding of the electronic structure in the extended materials, and also allowing for the design of future materials based on a dithienophosphole core. Furthermore, the phosphorus center in the extended molecular materials can efficiently be fine-tuned in subsequent simple chemical functionalizations. This allows for a tailoring of the optoelectronic properties of the extended dithienophospholes to suit the requirements of potential 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".