Superior Noise Suppression, Response Time, and Device Stability of Non‐Fullerene System over Fullerene Counterpart in Organic Photodiode
Bibliographic record
Abstract
Abstract Herein, non‐fullerene acceptor‐based organic photodiodes are compared with fullerene acceptor‐based organic photodiodes. The non‐fullerene acceptor, ethylhexyl‐rhodanine‐benzothiadiazole‐coupled indacenodithiophene (eh‐IDTBR)‐based organic photodiodes show a higher detectivity (1.61 × 1013 cm Hz1/2 W−1) and a faster response time (≈2.7 µs) than the fullerene acceptor, [6,6]‐phenyl C71 butyric acid methyl ester (PC71BM)‐based organic photodiodes (3.25 × 1012 cm Hz1/2 W−1 and ≈6.24 µs, respectively) owing to the excellent dark current suppression of the carrier injection and the low trap density of eh‐IDTBR. Moreover, the eh‐IDTBR‐based photodetector shows better operational device stability than the fullerene counterpart under electrical and thermal stress. This is corroborated by the morphology and crystallography analyses, both of which reveal that the eh‐IDTBR‐containing photo‐sensitive films remain intact after imposing an external stress. This study elucidates important key advantages of the non‐fullerene acceptor, eh‐IDTBR, and sets a milestone as it compares the non‐fullerene acceptors and fullerene acceptors in organic photodiodes for the first time. This work sets a new record for the performance and stability of solution‐processable non‐fullerene acceptor‐based organic photodiodes.
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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".