Monitoring the Fermi-level position within the bandgap on a single nanowire: A tool for local investigations of doping
Bibliographic record
Abstract
The control of the doping in nanowires (NWs) is of fundamental importance for the implementation of NW-based devices. A method is presented to obtain local information about doping by monitoring the Fermi-energy position within the bandgap at the surface along single NWs through spatially resolved x-ray photoemission spectroscopy. The experimental results are complemented by theoretical simulations of the carrier profile, taking into account the presence of electronic surface states and quantifying the impact of carrier depletion at the NW surface. This combined approach allows to determine the effect of the incorporation of Si dopants in GaAs NWs following different growth protocols, such as vapor-liquid-solid axial growth or vapor-solid radial growth, and in the resulting core-shell structures and axial junctions. The method also revelaed the strong dependence of the resulting doping on the morphology of the single NW (orientation, shell thickness). This approach can be easily applied to other nanoscale objects, allowing the direct observation of how doping (or junctions, or adsorbates,…) may locally affect the position of the Fermi level at the surface, which is a crucial factor in several application fields, such as photovoltaic and photocatalysis.
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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".