Two-dimensional tellurium-based diodes for RF applications
Bibliographic record
Abstract
Abstract The research of two-dimensional (2D) Tellurium (Te) or tellurene is thriving to address current challenges in emerging thin-film electronic and optoelectronic devices. However, the study of 2D-Te-based devices for high-frequency applications is still lacking in the literature. This work presents a comprehensive study of two types of radio frequency (RF) diodes based on 2D-Te flakes and exploits their distinct properties in two RF applications. First, a metal-insulator-semiconductor (MIS) structure is employed as a nonlinear device in a passive RF mixer, where the achieved conversion loss at 2.5 GHz and 5 GHz is as low as 24 dB and 29 dB, respectively. Then, a metal-semiconductor (MS) diode is tested as a zero-bias millimeter-wave power detector and reaches an outstanding linear-in-dB dynamic range over 40 dB, while having voltage responsivities as high as 257 V ⋅ W−1at 1 GHz (up to 1 V detected output voltage) and 47 V ⋅ W−1at 2.5 GHz (up to 0.26 V detected output voltage). These results show superior performance compared to other 2D material-based devices in a much more mature technological phase. Thus, the authors believe that this work demonstrates the potential of 2D-Te as a promising material for devices in emerging high-frequency electronics.
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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) | 0.002 | 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".