Interpreting Kelvin probe force microscopy under an applied electric field: local electronic behavior of vapor–liquid–solid Si nanowires
Bibliographic record
Abstract
Kelvin probe force microscopy (KPFM) is used to characterize the electrical characteristics of vapor-liquid-solid (VLS) Si nanowires (NWs) that are grown in-place between two predefined electrodes. KPFM measurements are performed under an applied bias. Besides contact potential differences due to differing materials, the two other primary contributions to measured variations on Si NWs between electrodes are: trapped charges at interfaces, and the parallel and serial capacitance, which are accounted for with voltage normalization and oxide normalization. These two normalization processes alongside finite-element-method simulations are necessary to characterize the bias-dependent response of Si NWs. After applying both normalization methods on open-circuit NWs, which results in a baseline of zero, we conclude that we have accounted for all the major contributions to CPDs and we can isolate effects due to applied bias such as impurity states and charged carrier flow, as well as find open connections when NWs are connected in parallel. These characterization and normalization methods can also be used to determine that the specific contact resistance of electrodes to the NWs is on the order of μΩ cm². Thus, the VLS growth method between predefined electrodes overcomes the challenge of making low-resistance contacts to nanoscale systems. Thereby, the experiments and analysis presented outline a systematic method for characterizing nanowires in parallel arrays under device operation conditions.
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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 | 0.001 | 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 teacher head, 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".