Silver nanowire electrodes for transparent light emitting devices based on WS<sub>2</sub> monolayers
Bibliographic record
Abstract
Abstract Transition metal dichalcogenide (TMDC) monolayers with their direct band gap in the visible to near-infrared spectral range have emerged over the past years as highly promising semiconducting materials for optoelectronic applications. Progress in scalable fabrication methods for TMDCs like metal-organic chemical vapor deposition (MOCVD) and the ambition to exploit specific material properties, such as mechanical flexibility or high transparency, highlight the importance of suitable device concepts and processing techniques. In this work, we make use of the high transparency of TMDC monolayers to fabricate transparent light-emitting devices (LEDs). MOCVD-grown WS 2 is embedded as the active material in a scalable vertical device architecture and combined with a silver nanowire (AgNW) network as a transparent top electrode. The AgNW network was deposited onto the device by a spin-coating process, providing contacts with a sheet resistance below 10 Ω sq −1 and a transmittance of nearly 80%. As an electron transport layer we employed a continuous 40 nm thick zinc oxide (ZnO) layer, which was grown by atmospheric pressure spatial atomic layer deposition (AP-SALD), a precise tool for scalable deposition of oxides with defined thickness. With this, LEDs with an average transmittance over 60% in the visible spectral range, emissive areas of several mm 2 and a turn-on voltage of around 3 V are obtained.
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How this classification was reachedexpand
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 | 0.000 | 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 teacher head, 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".