Reduction of Fermi level pinning at Cu–BP interfaces by atomic passivation
Bibliographic record
Abstract
Black phosphorus (BP) is a semiconducting material with a direct finite band gap in its monolayer, attracting intense attention for its application in field-effect transistors. However, strong Fermi level pinning (FLP) has been observed for contacts between BP and high work function metals, e.g., Cu. Such FLP presents an undesirable hurdle preventing the achievement of high performance field-effect devices. In this regard, there is a crucial need to understand the FLP occurring at the metal-BP interfaces and explore the possibility to reduce it. The present work studied atomic passivation in reducing FLP for the Cu-BP system using density functional theory calculations. The passivation by H, N, F, S, and Cl atoms on the Cu(111) surface has been considered. The results showed that the passivated atoms can shield the direct contact between Cu(111) and BP, thus reducing FLP at Cu-BP interfaces. In particular, S and Cl atoms were found to be highly effective agents to achieve a significant reduction of FLP, leading to Cu-BP contacts with ultralow Schottky barrier height (SBH) and suggesting the possibility of ohmic contact formation. Our findings demonstrate surface passivation as an effective method towards depinning the Fermi level at the metal-BP interface and subsequently controlling the SBH for BP-based electronic devices.
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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".