Effect of Si–H Bond on the Gas-Phase Chemistry of Trimethylsilane in the Hot Wire Chemical Vapor Deposition Process
Bibliographic record
Abstract
The effect of the Si-H bond on the gas-phase reaction chemistry of trimethylsilane in the hot-wire chemical vapor deposition (HWCVD) process has been studied by examining its decomposition on a hot tungsten filament and the secondary gas-phase reactions in a reactor using a soft laser ionization source coupled with mass spectrometry. Trimethylsilane decomposes on the hot filament via Si-H and Si-CH(3) bond cleavages. A short-chain mechanism is found to dominate in the secondary reactions in the reactor. It has been shown that the hydrogen abstractions of both Si-H and C-H occur simultaneously, with the abstraction of Si-H being favored. Tetramethylsilane and hexamethyldisilane are the two major products formed from the radical recombination reactions in the termination steps. Three methyl-substituted disilacyclobutane molecules, i.e., 1,3-dimethyl-1,3-disilacyclobutane, 1,1,3-trimethyl-1,3-disilacyclobutane, and 1,1,3,3-tetramethyl-1,3-disilacyclobutane are also produced in reactor from the cycloaddition reactions of methyl-substituted silene species. Compared to tetramethylsilane and hexamethyldisilane, a common feature with trimethylsilane is that the short-chain mechanism still dominates. However, a more active involvement of the reactive silene intermediates has been found with trimethylsilane.
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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) | 0.003 | 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".