Probing the Gate−Voltage-Dependent Surface Potential of Individual InAs Nanowires Using Random Telegraph Signals
Bibliographic record
Abstract
We report a novel method for probing the gate-voltage dependence of the surface potential of individual semiconductor nanowires. The statistics of electronic occupation of a single defect on the surface of the nanowire, determined from a random telegraph signal, is used as a measure for the local potential. The method is demonstrated for the case of one or two switching defects in indium arsenide (InAs) nanowire field effect transistors at temperatures T=25-77 K. Comparison with a self-consistent model shows that surface potential variation is retarded in the conducting regime due to screening by surface states with density Dss≈10(12) cm(-2) eV(-1). Temperature-dependent dynamics of electron capture and emission producing the random telegraph signals are also analyzed, and multiphonon emission is identified as the process responsible for capture and emission of electrons from the surface traps. Two defects studied in detail had capture activation energies of EB≈50 meV and EB≈110 meV and cross sections of σ∞≈3×10(-19) cm2 and σ∞≈2×10(-17) cm2, respectively. A lattice relaxation energy of Sℏω=187±15 meV was found for the first defect.
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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) | 0.000 | 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".