Anisotropic Carrier Mobility from 2H WSe<sub>2</sub>
Bibliographic record
Abstract
Abstract Transition metal dichalcogenides (TMDCs) with 2H phase are expected to be building blocks in next‐generation electronics; however, they suffer from electrical anisotropy, which is the basics for multi‐terminal artificial synaptic devices, digital inverters, and anisotropic memtransistors, which are highly desired in neuromorphic computing. Herein, the anisotropic carrier mobility from 2H WSe 2 is reported, where the anisotropic degree of carrier mobility spans from 0.16 to 0.95 for various WSe 2 field‐effect transistors under a gate voltage of −60 V. Phonon scattering, impurity ions scattering, and defect scattering are excluded for anisotropic mobility. An intrinsic screening layer is proposed and confirmed by Z ‐contrast scanning transmission electron microscopy (STEM) imaging to respond to the electrical anisotropy. Seven types of intrinsic screening layers are created and calculated by density functional theory to evaluate the modulated electronic structures, effective masses, and scattering intensities, resulting in anisotropic mobility. The discovery of anisotropic carrier mobility from 2H WSe 2 provides a degree of freedom for adjusting the physical properties of 2H TMDCs and fertile ground for exploring and integrating TMDC electronic transistors with better performance along the direction of high mobility.
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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".