MétaCan
Menu
Back to cohort
Record W2054122668 · doi:10.1116/1.1650852

Low-temperature Si growth on Si (001): Impurity incorporation and limiting thickness for epitaxy

2004· article· en· W2054122668 on OpenAlexaff
J.‐M. Baribeau, Xiaohua Wu, D. J. Lockwood, Li‐Lin Tay, G. I. Sproule

Bibliographic record

VenueJournal of Vacuum Science & Technology B Microelectronics and Nanometer Structures Processing Measurement and Phenomena · 2004
Typearticle
Languageen
FieldEngineering
TopicThin-Film Transistor Technologies
Canadian institutionsNational Research Council CanadaInstitute for Microstructural Sciences
Fundersnot available
KeywordsImpurityAmorphous solidEpitaxyMaterials scienceCrystallinityMolecular beam epitaxyRaman scatteringWaferAnalytical Chemistry (journal)Activation energySiliconRaman spectroscopyCrystallographyChemistryNanotechnologyOptoelectronicsOpticsPhysical chemistryComposite material

Abstract

fetched live from OpenAlex

We present a structural and chemical analysis of high-vacuum deposited Si films grown on clean or oxidized Si (001) wafers by low-temperature molecular-beam epitaxy. For growth on clean Si, we observed a limiting thickness for epitaxy that decreases with decreasing temperature with an activation energy of 0.47 eV. The onset of defect formation is correlated to a peak in the H impurity concentration. The transition to an amorphous phase is, however, observed beyond the depth where impurities are first observed pointing to surface disorder/roughening as a source of epitaxy breakdown. The O and C content in these films remains low until the film crystallinity has strongly deteriorated and reaches a saturation concentration of 2–4 at. % in the fully amorphous regions. The impurity profiles in amorphous-Si films grown on oxidized Si are similar to those obtained on clean Si when grown at the same temperature and indicate that the impurity uptake depends primarily on residual gas and surface condition. Raman scattering results show the structural changes and evolution of the Si bond configuration.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.143
Threshold uncertainty score0.960

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.010
GPT teacher head0.207
Teacher spread0.197 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations19
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Vacuum Science & Technology B Microelectronics and Nanometer Structures Processing Measurement and PhenomenaSame topicThin-Film Transistor TechnologiesFrench-language works237,207