Quasi p-i-n Organic Photodetectors for Self-Powered Dual-Wavelength Sensing
Bibliographic record
Abstract
We report a simple quasi p-i-n organic photodetector (OPD) enabled by p-type (P3HT: BCF) and n-type (ZY-4CI: N-DMBI) doped transport layers flanking a P3HT: ZY-4Cl bulk heterojunction. Targeted p- and n-type doping in the transport layers establishes a strong internal electric field, enabling dual-wavelength self-powered detection. Mott-Schottky analysis reveals effective carrier concentration with doping, achieving$\sim 2.9 \times 10^{17} \text{cm}^{-3}$for holes and$\sim 1.7 \times 10^{17} \text{cm}^{-3}$for electrons. Thin doped layers (10 nm for p-type, 20 nm for n-type) maintain$>90 \%$optical transmission. Compared to conventional BHJ OPDs, the quasi p-i-n design reduces dark current by a factor of 10 and enhances photocurrent by$\sim 3 \times$under green and$\sim 4.3 \times$under red illumination. Depletion width calculations confirm the extended electric field into the intrinsic layer of the proposed OPD, enabling efficient charge extraction and reliable self-powered operation. The proposed quasi p-i-n OPD will have potentials for low power photodetector-based wearables and sensors.
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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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".