Novel Field-Effect Schottky Barrier Transistors Based on Graphene-MoS2 Heterojunctions
Bibliographic record
Abstract
Recently, two-dimensional materials such as molybdenum disulphide (MoS2) have been demonstrated to realize field effect transistors (FET) with a large current on-off ratio. However, the carrier mobility in backgate MoS2 FET is rather low (typically 0.5-20 cm(2)/V · s). Here, we report a novel field-effect Schottky barrier transistors (FESBT) based on graphene-MoS2 heterojunction (GMH), where the characteristics of high mobility from graphene and high on-off ratio from MoS2 are properly balanced in the novel transistors. Large modulation on the device current (on/off ratio of 10(5)) is achieved by adjusting the backgate (through 300 nm SiO2) voltage to modulate the graphene-MoS2 Schottky barrier. Moreover, the field effective mobility of the FESBT is up to 58.7 cm(2)/V · s. Our theoretical analysis shows that if the thickness of oxide is further reduced, a subthreshold swing (SS) of 40 mV/decade can be maintained within three orders of drain current at room temperature. This provides an opportunity to overcome the limitation of 60 mV/decade for conventional CMOS devices. The FESBT implemented with a high on-off ratio, a relatively high mobility and a low subthreshold promises low-voltage and low-power applications for future 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) | 0.001 | 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".