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Record W2187369334

Effect of Strain on the Oxidation Rate of Silicon Germanium Alloys

2008· article· en· W2187369334 on OpenAlexaff
Mohamed A. Rabie, Steven Gou, Yaser M. Haddara, Andrew P. Knights, Jacek Wójcik, Peter Mascher

Bibliographic record

VenueTechConnect Briefs · 2008
Typearticle
Languageen
FieldEngineering
TopicSemiconductor materials and devices
Canadian institutionsUniversity of British ColumbiaMcMaster University
Fundersnot available
KeywordsLayer (electronics)Materials scienceSilicon-germaniumStrain (injury)GermaniumSiliconOxideStrain rateOptoelectronicsComposite materialMetallurgy
DOInot available

Abstract

fetched live from OpenAlex

We report on a series of experiments in which a strained Si 0.95 Ge 0.05 layer 600A thick was oxidized along with relaxed SiGe layers and Si samples. In this work, we observed that the oxidation rate of the strained SiGe layer is always much higher than the relaxed model expectations. We also observed that the rate is higher than that of relaxed SiGe layers with higher Ge concentration oxidized at similar temperatures. We attributed this increase in the rate of oxidation to the effect of strain in the SiGe layer. To confirm our hypothesis, we oxidized strained SiGe layers together with relaxed SiGe layers of higher concentration. We observed that the strained SiGe layer compared with relaxed sample has a thicker oxide despite the lower Ge concentration. We conclude that the strain in the SiGe layer causes a further increase in the oxidation rate.

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)0.000
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 score0.003
Threshold uncertainty score0.339

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 head0.013
GPT teacher head0.216
Teacher spread0.203 · 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

Citations0
Published2008
Admission routes1
Has abstractyes

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