High‐Detectivity All‐Polymer Photodetectors with Spectral Response from 300 to 1100 nm
Bibliographic record
Abstract
Broad‐response and high‐detectivity for all‐polymer photodetectors based on p‐ and n‐type semiconducting polymers have been achieved through optimization of polymer property and film microstructure. The electron‐donating units in the p‐type polymers affect a great deal of the polymer properties such as solubility, absorption spectra, and electronic energy levels, which in turn can influence the device performance. The polymer (P3) based on dithienopyrrole and diketopyrrolopyrrole is most promising for photodetector applications, as it possesses the suitable energy level with regard to the n‐type polymer and exhibits appropriate film morphology and molecular stacking with aid of 1,8‐diiodooctane as an additive during film processing. The photodetector based on P3/poly{[N,N′‐bis(2‐octyldodecyl)‐naphthalene‐1,4,5,8‐bis(dicarboximide)‐2,6‐diyl]‐alt‐5,5′‐(2,2′‐bithiophene)} (PNDI) exhibits good response from 300 to 1100 nm and nearly constant detectivity (D*) above 1012 Jones at 330–980 nm, rendering a great potential of all‐polymer photodetectors for practical applications. image
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".