Wave‐Interference Photonic Crystals and Space Charge Engineering Enable Efficient Broadband Faint Light Detection in Organic/Inorganic Hybrid Photodetectors
Bibliographic record
Abstract
Abstract Noise current, detectivity, quantum efficiency, and response speed are critical metrics in evaluating organic/inorganic photodiodes. Herein, these metrics are simultaneously advanced in poly(3,4‐ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS)/native SiO x /n‐Si hybrid photodetectors, achieving excellent performance in detecting broadband faint light. Wave‐interference photonic crystals, comprising periodic microstructured inverse pyramids with nanometer‐scale mesa widths, are integrated into the Si absorber to effectively couple incident light for increased absorption, thereby balancing optics and conformal contact coverage. The developed photodetector comprises a deep depletion region and interfacial SiO x layer, enabling diffusion‐mitigated broadband photocarrier transport and effective charge collection, and suppressing carrier tunneling processes for low‐noise. An ultralow reverse dark current density of ≈2.46 × 10 −8 A cm −2 at −0.4 V is realized for nanowatt‐level light detection. The photodetector showcases superlative properties among reported PEDOT:PSS–based inorganic heterojunctions, including a broadband external quantum efficiency of >≈80% from 340 to 960 nm (internal quantum efficiency of >≈90% from 380 to 840 nm), detectivity of >≈10 12 Jones from 300 to 1140 nm, and microsecond response speed. This study provides practical insight for combining high‐absorption microstructures with space charge engineering for the development of high‐performance organic/inorganic hybrid photodetectors.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".