Perovskite–Gold Nanorod Hybrid Photodetector with High Responsivity and Low Driving Voltage
Bibliographic record
Abstract
Abstract The optical and electronic properties of noble metallic nanoparticles can be exploited to enhance the performance of inorganic/organic photodetectors. In this work, a uniformly distributed layer of Au nanorods (AuNRs) is integrated into vertically structured perovskite photoconductive photodetectors and, as a result, perovskite–AuNR hybrid photodetectors that exhibit significant photocurrent enhancements are reported. Ultimately it achieves a responsivity of ≈320 A W−1 at a low driving voltage of −1 V. This is an improvement of 60% compared to the responsivity of pristine devices (≈200 A W−1). The high responsivity and low driving voltage place this device among the highest performing perovskite‐based thin‐film photoconductive photodetectors reported. The stability and linearity of the photoresponse following repeated light/dark cycles are characterized. The hybrid device also shows a fast response (with the decay time of ≈95 ns) compared to pristine devices (≈230 ns). The improvements in photodetection performance are attributed to plasmon‐enhanced optical absorption, as well as advances in charge extraction and transport.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".