Active pixel image sensor array for dual vision using large‐area bilayer <scp>WS<sub>2</sub></scp>
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Transition metal dichalcogenides (TMDs) are a promising candidate for developing advanced sensors, particularly for day and night vision systems in vehicles, drones, and security surveillance. While traditional systems rely on separate sensors for different lighting conditions, TMDs can absorb light across a broad‐spectrum range. In this study, a dual vision active pixel image sensor array based on bilayer WS 2 phototransistors was implemented. The bilayer WS 2 film was synthesized using a combined process of radio‐frequency sputtering and chemical vapor deposition. The WS 2 ‐based thin‐film transistors (TFTs) exhibit high average mobility, excellent I on / I off , and uniform electrical properties. The optoelectronic properties of the TFTs array exhibited consistent behavior and can detect visible to near‐infrared light with the highest responsivity of 1821 A W −1 (at a wavelength of 405 nm) owing to the photogating effect. Finally, red, green, blue, and near‐infrared image sensing capabilities of active pixel image sensor array utilizing light stencil projection were demonstrated. The proposed image sensor array utilizing WS 2 phototransistors has the potential to revolutionize the field of vision sensing, which could lead to a range of new opportunities in various applications, including night vision, pedestrian detection, various surveillance, and security systems. image
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it