Layer speciation and electronic structure investigation of freestanding hexagonal boron nitride nanosheets
Bibliographic record
Abstract
Chemical imaging, thickness mapping, layer speciation and polarization dependence have been performed on single and multilayered (up to three layers and trilayered nanosheets overlapping to form 6 and 9 layers) hexagonal boron nitride (hBN) nanosheets by scanning transmission X-ray microscopy. Spatially-resolved XANES directly from freestanding regions of different layers has been extracted and compared with sample normal and 30° tilted configurations. Notably a double feature σ* excitonic state and a stable high energy σ* state were observed at the boron site in addition to the intense π* excitonic state. The boron projected σ* DOS, especially the first σ* exciton, is sensitive to surface modification, particularly in the single layered hBN nanosheet which shows more significant detectable contaminants and defects such as tri-coordinated boron/nitrogen oxide. The nitrogen site has shown very weak or no excitonic character. The distinct excitonic effect on boron and nitrogen was interpreted to the partly ionic state of hBN. Bulk XANES of hBN nanosheets was also measured to confirm the spectro-microscopic STXM result. Finally, the unoccupied electronic structures of hBN and graphene were compared.
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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".