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Record W2137601448 · doi:10.1002/pssc.201084032

Self‐assembled silicon‐germanium nanostructures for CMOS compatible light emitters

2011· article· en· W2137601448 on OpenAlexaffabout
D. J. Lockwood, L. Tsybeskov

Bibliographic record

VenuePhysica status solidi. C, Conferences and critical reviews/Physica status solidi. C, Current topics in solid state physics · 2011
Typearticle
Languageen
FieldMaterials Science
TopicSilicon Nanostructures and Photoluminescence
Canadian institutionsInstitute for Microstructural Sciences
FundersNanjing Institute of TechnologyIntel CorporationSemiconductor Research CorporationNational Science Foundation
KeywordsOptoelectronicsMaterials scienceElectroluminescenceCMOSSiliconPhotoluminescenceQuantum dotQuantum efficiencyGermaniumLight-emitting diodeNanotechnology

Abstract

fetched live from OpenAlex

Abstract To be commercially valuable, light emitters based on SiGe nanostructures should be efficient, fast, operational at room temperature, and be compatible with the CMOS technology. Also, the emission wavelength should match the optical waveguide low‐loss spectral region of 1.3–1.6 μm. Among other approaches, epitaxially‐grown Si/SiGe quantum dot/quantum well complexes produce efficient photoluminescence and electroluminescence in the required spectral range. Until recently, the major roadblocks for practical applications of these devices were strong thermal quenching of the luminescence quantum efficiency and a long carrier radiative lifetime. The latest progress in the understanding of physics of carrier recombination in Si/SiGe nanostructures is reviewed, and a new route toward CMOS compatible light emitters for on‐chip optical interconnects is proposed. © Her Majesty the Queen in Right of Canada [2011]. Reproduced with the permission of the Minister of Industry

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.353
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.056
GPT teacher head0.340
Teacher spread0.283 · 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; both teacher heads agree on what is shown here.

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

Citations3
Published2011
Admission routes2
Has abstractyes

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