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Record W2070100885 · doi:10.1063/1.4855436

Strain and composition effects on Raman vibrational modes of silicon-germanium-tin ternary alloys

2013· article· en· W2070100885 on OpenAlex
Jean-Hughes Fournier-Lupien, Samik Mukherjee, Stephan Wirths, Eckhard Pippel, Norihiko Hayazawa, Gregor Mußler, Jean‐Michel Hartmann, P. Desjardins, Dan Buca, Oussama Moutanabbir

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueApplied Physics Letters · 2013
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsRaman spectroscopySiliconTinGermaniumMaterials scienceTernary operationRaman scatteringChemical vapor depositionAnalytical Chemistry (journal)ExcitationOptoelectronicsOpticsChemistryMetallurgy

Abstract

fetched live from OpenAlex

We investigated Raman vibrational modes in silicon-germanium-tin layers grown epitaxially on germanium/silicon virtual substrates using reduced pressure chemical vapor deposition. Several excitation wavelengths were utilized to accurately analyze Raman shifts in ternary layers with uniform silicon and tin content in 4–19 and 2–12 at. % ranges, respectively. The excitation using a 633 nm laser was found to be optimal leading to a clear detection and an unambiguous identification of all first order modes in the alloy. The influence of both strain and composition on these modes is discussed. The strain in the layers is evaluated from Raman shifts and reciprocal space mapping data and the obtained results are discussed in the light of recent theoretical calculations.

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.

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)0.000
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 score0.052
Threshold uncertainty score0.434

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.181
Teacher spread0.177 · 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