Electronic Control of Silicon Surface Atomic Structures with Two-Probe Scanning Tunneling Microscopy
Bibliographic record
Abstract
Dangling bonds (DBs) on the H-terminated Si(100) surface have stimulated much interest in exploring atomic-scale devices. Although multiprobe scanning tunneling microscope (STM) can be utilized as an ideal tool to characterize DB architectures, studying these on low conductive Si substrates remains a challenge since the effects such as large screening length and long mean-free path for carriers can emerge during measurements. Here, we report the effects of minority carrier (hole for n-type Si) injection on DBs with two-probe STM. While one STM probe was used to characterize the surfaces, another one was placed in the distance to inject holes into the Si substrates. We found that in steady state, migrating holes can negate band bending at the STM imaging areas and that the average charge states of DBs can be controlled by the amount of injected holes. We also investigated a DB island crafted on the H-terminated Si surface, which, as a result of hole injection, shows image features not ordinarily seen at the applied bias, confirming that the hole injection induces a shift of the STM apparent imaging bias and additional gap states in I – V measurements. These findings are important for understanding atomic-scale devices on low conductive substrates.
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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".