Temperature Hypersensitive Organic Electroluminescence in a Reverse Biased, Frozen Polymer P–I–N Junction
Bibliographic record
Abstract
Abstract Semiconductor junctions are among the most important material interfaces in modern technology. The solid polymer light‐emitting electrochemical cell (PLEC) possesses a semiconducting polymer homojunction that is reminiscent of a conventional p–n junction but also exhibits distinct features that are profoundly intriguing. The PLEC junction is formed under bias when the propagating p‐ and n‐doping fronts make contact. The PLEC junction can be immobilized by cooling after the initial junction formation. Further, the resulting frozen junction can be relaxed, or partially de‐doped into a p–i–n junction by controlled heating/cooling cycles. It is on such a frozen polymer p–i–n junction that the authors observed one of the most puzzling phenomena in organic electroluminescence (EL). The frozen p–i–n junction displays the brightest reverse bias (RB) EL ever imaged in a polymer junction and a large photovoltage. Moreover, the RB EL exhibits hypersensitivity to temperature, increasing in intensity by 22.6% K−1 when the de‐doped cell is cooled from 250 to 200 K. A model based on the tunnel injection of charge carriers with fast transit time across the intrinsic region explains the RB EL's hypersensitivity to temperature and super‐linear dependence on cell current.
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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".