Green-Sensitive Organic Photodetectors with High Sensitivity and Spectral Selectivity Using Subphthalocyanine Derivatives
Bibliographic record
Abstract
Green-sensitive organic photodetectors (OPDs) with high sensitivity and spectral selectivity using boron subphthalocyanine chloride (SubPc) derivatives are reported. The OPDs composed of SubPc and dicyanovinyl terthiophene derivative (DCV3T) demonstrated the highest green-sensitivity with maximum external quantum efficiency (EQE) of 62.6 % at an applied voltage of -5 V, but wide full-width-at-half-maximum (FWHM) of 211 nm. The optimized performance considering spectral selectivity was achieved from the composition of N,N-dimethyl quinacridone (DMQA) and SubPc showing the high specific detectivity (D*) of 2.34 × 10(12) cm Hz(1/2)/W, the EQE value of 60.1% at -5 V, and narrow FWHM of 131 nm. In spite of the sharp absorption property of SubPc with the maximum wavelength (λmax) at 586 nm, the EQE spectrum showed favorable green-sensitivity characterized by smooth waveform with λmax at 560 nm, which is induced from the high reflectance of SubPc centered at 605 nm. The photoresponsivity of the OPD devices was found to be consistent with their absorptance. Optimized DMQA/SubPc device showed the lowest value of blue crosstalk (0.42) and moderate red crosstalk (0.37), suggesting its promising application as a green-sensitive OPD.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".