Tunable 2D Group‐III Metal Alloys
Bibliographic record
Abstract
Abstract Chemically stable quantum‐confined 2D metals are of interest in next‐generation nanoscale quantum devices. Bottom‐up design and synthesis of such metals could enable the creation of materials with tailored, on‐demand, electronic and optical properties for applications that utilize tunable plasmonic coupling, optical nonlinearity, epsilon‐near‐zero behavior, or wavelength‐specific light trapping. In this work, it is demonstrated that the electronic, superconducting, and optical properties of air‐stable 2D metals can be controllably tuned by the formation of alloys. Environmentally robust large‐area 2D‐In x Ga 1− x alloys are synthesized byConfinement Heteroepitaxy (CHet). Near‐complete solid solubility is achieved with no evidence of phase segregation, and the composition is tunable over the full range of x by changing the relative elemental composition of the precursor. The optical and electronic properties directly correlate with alloy composition, wherein the dielectric function, band structure, superconductivity, and charge transfer from the metal to graphene are all controlled by the indium/gallium ratio in the 2D metal layer.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.006 | 0.001 |
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; both teacher heads agree on what is shown here.
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".