Graphene/hBN–based valley transistor: Dynamic control of valley current in synchronized nonzero voltages within the time-dependent regime
Bibliographic record
Abstract
Graphene/hexagonal boron nitride (hBN) heterostructures represent a promising class of metal--insulator--semiconductor systems widely explored for multifunctional digital device applications. In this work, we demonstrate that graphene, when influenced by carrier-dependent trapping in the hBN spacer, triggered by a localized potential from Kelvin probe force microscopy (KPFM), can exhibit the behavior of a valley transistor under specific conditions. We employ a tight-binding model that self-consistently incorporates a Gaussian-shaped potential to represent the effect of the tip gate. Crucially, we show that the heterostructure can function as a field-effect transistor (FET), with its operation governed by the bias gate (which shifts the Fermi level) and the tip-induced potential (which breaks electron--hole symmetry by selectively trapping electron or hole quasiparticles). Our results reveal that, under specific conditions involving lattice geometry, pulse frequency, and gate voltages, the device exhibits valley transistor functionality. The valley current $({I}_{{K}_{1}=\ensuremath{-}K} \text{or} {I}_{{K}_{2}=+K})$ can be selectively controlled by synchronizing the frequencies and polarities of the tip and bias gate voltages. Notably, when both gates are driven with the same polarity, the graphene channel outputs a periodically modulated, pure valley-polarized current. This enables the device to switch between distinct ON/OFF valley current states even at finite bias. Interestingly, when the ${I}_{{K}_{1}=\ensuremath{-}K}$ current is in the ON (forward current) state, the ${I}_{{K}_{2}=+K}$ current is OFF. Reversing the gate polarity inverts this behavior: ${I}_{{K}_{1}=\ensuremath{-}K}$ becomes OFF, while ${I}_{{K}_{2}=+K}$) turns ON (reversed-current). These findings pave the way toward realizing low-voltage valley transistors within metal--insulator--semiconductor architectures, offering avenues for multifunctional applications in valleytronics and advanced gating technologies.
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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".