Effects of the structure of charged impurities and dielectric environment on conductivity of graphene
Bibliographic record
Abstract
We investigate the conductivity of doped single-layer graphene in the semiclassical Boltzmann limit, as well as the conductivity minimum in neutral graphene within the self-consistent transport theory, pointing up the effects due to both the structure of charged impurities near graphene and the structure of the surrounding dielectrics. Using the hard-disk model for a two-dimensional (2D) distribution of impurities allows us to investigate structures with large packing fractions, which are shown to give rise to both strong increase in the slope of conductivity at low charge carrier densities in graphene and a strongly sublinear behavior of the conductivity at high charge carrier densities when the correlation distance between the impurities is large. On the other hand, we find that a superlinear dependence of the conductivity on charge carrier density in heavily doped graphene may arise from increasing the distance of impurities from graphene or allowing their clustering into disklike islands, whereas the existence of an electric dipole polarizability of impurities may give rise to an electron-hole asymmetry in the conductivity. Using the electrostatic Green's function for a three-layer structure of dielectrics, we show that finite thickness of a dielectric layer in the top-gating configuration, as well as the existence of nonzero air gap(s) between graphene and the nearby dielectric(s), exerts strong influences on the conductivity and its minimum. While a decrease in the dielectric thickness is shown to increase the conductivity in doped graphene and even gives rise to finite conductivity in neutral graphene for a 2D distribution of impurities, we find that an increase in the dielectric thickness gives rise to a superlinear behavior of the conductivity when impurities are homogeneously distributed throughout the dielectric. Moreover, the dependence of graphene's mobility on its charge carrier density is surprisingly strongly affected, quantitatively and qualitatively, by the graphene-dielectric gap(s) when combined with the precise position of a 2D distribution of charged impurities. Finally, we show that the conductivity minimum in neutral graphene is increased by increasing the correlation distance between the impurities, reduced by increasing the graphene-dielectric gap, and increased by decreasing the dielectric thickness in a top-gated configuration, even though the corresponding residual charge carrier density is reduced by decreasing the dielectric thickness.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".