Exclusively Gas-Phase Passivation of Native Oxide-Free Silicon(100) and Silicon(111) Surfaces
Bibliographic record
Abstract
Reactions in the gas phase are of primary technological importance for applications in nano- and microfabrication technology and in the semiconductor industry. We present exclusively gas-phase protocols to chemically passivate oxide-free Si(111) and Si(100) surfaces with short-chain alkynes. The resulting surfaces showed equal or better oxidation resistance than most existing liquid-phase-derived surfaces and rivaled the outstanding stability of a full-coverage Si(111)-propenyl surface.1,2 The most stable surface (Si(111)-ethenyl) grew one-fifth of a monolayer of oxide (0.04 nm) after 1 month of air exposure. We monitored the regrowth of oxides on passivated Si(111) and Si(100) surfaces by X-ray photoelectron spectroscopy (XPS) and observed a significant crystal-orientation dependence of initial rates when total oxide thickness was below approximately one monolayer (0.2 nm). This difference was correlated with the desorption kinetics of residual surface Si-F bonds formed during HF treatment. We discuss applications of the technology and suggest future directions for process optimization.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".