2D Oxides Realized via Confinement Heteroepitaxy
Bibliographic record
Abstract
Abstract Novel confinement techniques facilitate the formation of non‐layered 2D materials. Here it is demonstrated that the formation and properties of 2D oxides (GaO x , InO x , SnO x ) at the epitaxial graphene (EG)/silicon carbide (SiC) interface is dependent on the EG buffer layer properties prior to element intercalation. Using 2D Ga, it is demonstrated that defects in the EG buffer layer lead to Ga transforming to GaO x with non‐periodic oxygen in a crystalline Ga matrix via air oxidation at room temperature. However, crystalline monolayer GaO 2 and bilayer Ga 2 O 3 with ferroelectric wurtzite structure(FE‐WZ') can then be formed via subsequent high‐temperature O 2 annealing. Furthermore, the graphene/X/SiC (X = 2D Ga or Ga 2 O 3 ) junction is tunable from Ohmic to a Schottky or tunnel barrier depending on the interface species. Finally, using vertical transport measurements and electron energy loss spectroscopy analysis, the bandgap of 2D gallium oxide is identified as 6.6 ± 0.6 eV, significantly larger than that of bulk β‐Ga 2 O 3 (≈4.8 eV), suggesting strong quantum confinement effects at the 2D limit. The study presented here is foundational for development of atomic‐scale, vertical 2D/3D heterostructure for applications requiring short transit times, such as GHz and THz devices.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".