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Record W2051079774 · doi:10.1116/1.4825105

Effect of trimethylsilane pressure on hot-wire chemical vapor deposition chemistry using vacuum ultraviolet laser ionization mass spectrometry

2013· article· en· W2051079774 on OpenAlexafffund
Rim Toukabri, Yujun Shi

Bibliographic record

VenueJournal of Vacuum Science & Technology A Vacuum Surfaces and Films · 2013
Typearticle
Languageen
FieldMaterials Science
TopicCatalytic Processes in Materials Science
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Calgary
KeywordsTrimethylsilaneChemistryPropyneTetramethylsilaneMass spectrometryMethanePhotochemistryChemical ionizationAnalytical Chemistry (journal)Atmospheric pressureOrganic chemistryIonizationIon

Abstract

fetched live from OpenAlex

In this study, the authors investigated the effect of sample pressure on the reaction chemistry of trimethylsilane (TriMS) in the hot-wire chemical vapor deposition (CVD) process. The secondary gas-phase reaction products were examined in a reactor with varying TriMS pressures. The reaction products were analyzed using a laser ionization source with a vacuum ultraviolet wavelength of 118 nm, coupled with mass spectrometry. By increasing TriMS pressure, methane formation was observed. To our knowledge, this is the first successful use of either open-chain alkylsilanes or four-membered-ring (di)silacyclobutane molecules as an independent precursor gas in the hot-wire CVD reactor to achieve methane formation. Our results showed that methane was formed mainly from the radical chain reactions with minor contributions from molecular elimination. The increase in the sample pressure also led to the formation of other small hydrocarbon molecules including acetylene, ethene, propyne, and propene. The formation of hydrogen molecules was enhanced when the sample pressure was increased. In addition, the change in the sample pressure had a direct effect on the radical recombination and disproportionation reactions. This is reflected in the different behavior assumed by the main products from these two types of reactions, i.e., tetramethylsilane, hexamethyldisilane from the former, and three methyl-substituted disilacyclobutanes from the latter. The trapping of free radicals resulting from the in-situ produced ethene and propene molecules is responsible for the observed difference.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.005
GPT teacher head0.244
Teacher spread0.239 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations8
Published2013
Admission routes2
Has abstractyes

Explore more

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