Recent Developments in Phosphole‐Containing Oligo‐ and Polythiophene Materials
Bibliographic record
Abstract
Abstract The introduction of phosphorus‐containing moieties into π‐conjugated thiophene materials has been found to provide materials with strongly optimized and highly tunable optoelectronic features compared to their native thiophene counterparts. 2,5‐Diaryl‐ and 2,5‐bis(heteroaryl)phospholes as well as fused tricyclic dithieno[3,2‐b:2′,3′‐d]phospholes represent two very valuable building blocks for organic electronics as their intriguing features can be altered systematically by several, in part unique, methodologies. The potential scope of these modifications has been determined by comprehensive investigations of their structure–property relationships via suitable molecular model compounds. Onseveral occasions, these observations could successfully be transposed to corresponding polymers that are often difficult to characterize independently. The same is true for the first organic light‐emitting diodes (OLEDs) based on a phosphole scaffold, whose properties could also be predicted successfully. (© Wiley‐VCH Verlag GmbH & Co. KGaA, 69451 Weinheim, Germany, 2007)
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".