Moiré impurities in twisted bilayer black phosphorus: Effects on the carrier mobility
Bibliographic record
Abstract
Moir\'e patterns on two-dimensional van der Waals heterostructure can give rise to unique electronic and transport properties. In this work we report a theoretical investigation of Moir\'e patterns on twisted bilayer black phosphorus (tbBP). It is found that the Moir\'e pattern has extraordinary effects and leads to significant asymmetry with respect to transport direction and carrier type. The high-symmetry local stacking configurations in the Moir\'e pattern act as impurities with sizes at the Moir\'e length scale, and these ``Moir\'e impurities'' induce flatbands and localized states in tbBPs. Because both the conduction band minimum and valence band maximum are dominated by these localized states, the deformation potential limited carrier mobility is significantly affected: the electron mobility of tbBPs reduces by almost 20-fold when twisting from zero angle $(\ensuremath{\sim}2560\phantom{\rule{0.222222em}{0ex}}\phantom{\rule{4pt}{0ex}}{\mathrm{cm}}^{2}\phantom{\rule{0.16em}{0ex}}{\mathrm{V}}^{\ensuremath{-}1}\phantom{\rule{0.16em}{0ex}}{\mathrm{s}}^{\ensuremath{-}1})$ to just $1.{8}^{\ensuremath{\circ}}$ $(\ensuremath{\sim}131\phantom{\rule{0.28em}{0ex}}{\mathrm{cm}}^{2}\phantom{\rule{0.16em}{0ex}}{\mathrm{V}}^{\ensuremath{-}1}\phantom{\rule{0.16em}{0ex}}{\mathrm{s}}^{\ensuremath{-}1})$. The microscopic physics behind these effects are revealed by the real-space wave functions.
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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".