Thermoelectric terahertz photodetectors based on selenium-doped black phosphorus flakes
Bibliographic record
Abstract
Chemical doping of bulk black phosphorus is a well-recognized way to reduce surface oxidation and degradation. Here, we report on the fabrication of terahertz frequency detectors consisting of an antenna-coupled field-effect transistor (FET) with an active channel of Se-doped black phosphorus. Our devices show a maximum room-temperature hole mobility of 1780 cm2 V-1 s-1 in a SiO2-encapsulated FET. A room-temperature responsivity of 3 V W-1 was observed, with a noise-equivalent power of 7 nW Hz-1/2 at 3.4 THz, comparable with the state-of-the-art room-temperature photodetectors operating in the same frequency range. The inclusion of Se dopants in the growth process of black phosphorus crystals enables the optimization of the transport and optical performances of FETs in the far-infrared with a high potential for the development of BP-based electro-optical devices. We also demonstrate that the flake thickness can be tuned according to the target application. Specifically, thicker flakes (>80 nm) are suitable for applications in which high mobility and high speed are essential, thinner flakes (<10 nm) are more appropriate for applications requiring high on/off current ratios, while THz photodetection is optimal with flakes 30-40 nm thick, due to the larger carrier density tunability.
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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".