Dopant depletion in the near surface region of thermally prepared silicon (100) in UHV
Bibliographic record
Abstract
Degenerately doped (arsenic) n-type hydrogen terminated silicon (100) samples were prepared using various heat treatments for ultrahigh vacuum scanning tunneling microscopy (STM) and spectroscopy (STS) analysis. Samples heat treated to 1050 °C were found to have a consistent level of doping throughout the bulk and near surface regions. STS revealed tunneling through dopant states consistent with degenerately doped samples. SIMS profiling and HREELS measurements confirmed dopant and carrier concentrations, respectively. Samples heated to 1250 °C were found to have a reduced concentration of dopants in the near surface region. STS measurements showed shifted I/V curves and the loss of tunneling through dopant states in the band gap, indicating reduced dopant concentrations. Observations were confirmed by SIMS and HREELS where depleted dopants and reduced carrier concentrations were measured. The effect of the varying surface dopant concentrations on the STM imaging characteristics of dangling bonds on hydrogen terminated surfaces was also investigated. Understanding the effect of thermal processing on near surface dopant atom concentrations will permit better control over equilibrium charge occupation and charging characteristics of dangling bond midgap states on H:silicon.
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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".