Optimization of Broad-Response and High-Detectivity Polymer Photodetectors by Bandgap Engineering of Weak Donor–Strong Acceptor Polymers
Bibliographic record
Abstract
A series of weak donor–strong acceptor polymers containing two different electron-deficient units (diketopyrrolopyrrole and thienoisoindigo) are synthesized and used in broad-response and high-detectivity polymer photodetectors. By adjusting the composition ratio of the two acceptors, the absorption spectra, energy levels, molecular stacking, and film morphology are affected, which in turn influence the photodetector performance. With increased thienoisoindigo component, the HOMO energy levels shift from −5.41 to −4.76 eV, and the LUMO energy levels are nearly unchanged, corresponding to reduced bandgaps and red-shifted absorption spectra. 1,8-Diiodooctane additive shows greatly impact on the film morphology, which affects the photodetector performance significantly. Going from P1 to P5, the detectivity decreases, but the response range increases. The photodetector based on P4 exhibits detectivity of greater than 10 11 Jones in a broad spectral region of 300–1200 nm, which is really promising for UV–vis–NIR light detection.
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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) | 0.001 | 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 | 0.001 |
| 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".