Polarization‐Sensitive and Self‐Driven Pyro‐Phototronic Photodetectors Based on MoS<sub>2</sub>‐Water Heterojunctions
Bibliographic record
Abstract
Abstract Polarization‐sensitive and self‐driven pyroelectric‐based photodetectors have recently gained interest due to their potential application in artificial electronic eyes, biomedical imaging, and optical switches. Here, a photodetector based on light modulation‐induced polarization and depolarization of water molecules on the surface of a 2D MoS 2 crystal is reported. The MoS 2 ‐water heterostructure photodetector serves as a self‐driven pyro‐phototronic device that converts light‐induced thermal energy to electrical signals, leading to a transient photoresponsivity as high as 24.6 mA W −1 and a specific detectivity of 2.85 × 10 8 Jones under 470 nm wavelength at zero bias. Due to the formation of a built‐in electric field at the MoS 2 ‐water interface, this structure also has a high steady–state responsivity of 3.62 A W −1 and detectivity of 9.18 × 10 8 Jones at 3 V bias, along with a fast response time of ≈0.74 ms. Moreover, due to the rearrangement of the hydrogen bond network in the liquid water upon visible light illumination, the MoS 2 ‐water photodetector is light polarization‐sensitive. The simple fabrication process, low cost, polarization sensitivity, and high performance of the MoS 2 ‐water structure make it an excellent candidate for liquid‐compatible 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) | 0.001 | 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".