Low‐Bandgap Polymers for High‐Performance Photodiodes with Maximal EQE near 1200 nm and Broad Spectral Response from 300 to 1700 nm
Bibliographic record
Abstract
Abstract Polymer photodiodes with broad spectral response above 1500 nm can be used for imaging in the near‐infrared window of the atmosphere. Three low‐bandgap polymers based on 3,6‐dithiophen‐2‐yl‐2,5‐dihydropyrrolo[3,4‐c]pyrrole‐1,4‐dione (DPP), [1,2,5]thiadiazolo[3,4‐g]quinoxaline (TQ), benzobisthiadiazole (BBT), and dithienopyrrole (DTP) are designed and synthesized. No‐gain and gain polymer photodiodes with polymers:PC71BM as active layer materials and with aluminum doped ZnO nanoparticles:2,9‐bis(3‐(dimethylamino)propyl)anthra[2,1,9‐def:6,5,10‐d′e′f′]diisoquinoline‐1,3,8,10(2H,9H)‐tetraone (AZO:PDIN), MoO3, and 2,9‐dimethyl‐4,7‐diphenyl‐1,10‐phenanthroline (BCP) as interlayer materials are prepared. No‐gain photodiodes based on polymer P1 exhibit the external quantum efficiency (EQE) of 7.8% at 1200 nm, which is among the best values of polymer photodiodes known to date. Gain photodiodes based on P1 and P3 also exhibit a maximal EQE near 1200 nm. In addition, gain photodiodes based on P1 have a specific detectivity over 1013 Jones in 300–1360 nm and spectral response in the region of 300–1700 nm.
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) | 0.002 | 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".