Experimental and Theoretical Studies of Trimethylene Sulfide-Derived Nanostructures on p- and n-Type H-Silicon(100)-2 × 1
Bibliographic record
Abstract
The nanoscale structuring of molecules on silicon surfaces is one approach for combining the tuneable properties of chemical species with the functionality of semiconductor materials. In this study, we report on the growth characteristics of trimethylene sulfide (TMS) on p- and n-type H−Si(100)-2 × 1. The nanostructures formed by TMS on either surface are indistinguishable by scanning tunneling microscopy (STM). However, high-resolution electron energy loss spectroscopy (HREELS) and modeling by density functional theory indicate that the molecular attachment mechanism differs with dopant type. Our results show that TMS adds to a surface silicon dangling bond through the formation of a Si−S bond on p-type silicon and through the formation of a Si−C bond on n-type silicon. In both cases, the added TMS undergoes ring opening following covalent bond formation with the surface. The different ring-opened radicals are able to abstract a hydrogen atom from one of two neighboring silicon dimers. The overall reaction produces TMS-derived nanostructures that grow via a square-wave pattern on the neighboring edges of two dimer rows.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".