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Record W4232780108 · doi:10.1149/ma2015-02/15/730

(Invited) Bright Light Emitting Silicon/Germanium Nanostructures

2015· article· en· W4232780108 on OpenAlexaffabout
D. J. Lockwood

Bibliographic record

VenueECS Meeting Abstracts · 2015
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsOptoelectronicsMaterials sciencePhotonicsSiliconPhotodetectorLight emissionGermaniumBand gapSilicon photonicsQuantum dot

Abstract

fetched live from OpenAlex

Light emission from Si and Ge nanostructures has been of great interest for some time now owing to the need for silicon-based light sources for applications in silicon opto-electronics and photonics. Optical interconnects are required now for on-chip technology as an alternative to metal wires, because of data transmission bottlenecks introduced by their unavoidable delay times, significant signal degradation, problems with power dissipation, and electromagnetic interference. Two major avenues toward optical interconnects on a chip include a hybrid approach with III-V densely packaged optoelectronic components and the all-group-IV approach (mainly Si, Ge and SiGe), where the all major components, e.g., light emitters, modulators, waveguides and photodetectors, are monolithically integrated into the CMOS environment. Both Si and Ge possess indirect band gaps, which makes them very inefficient light emitters. Band gap engineering employing quantum wells, quantum wires or quantum dots has been proposed as one way to overcome this limitation and Si/Ge or Si/SiGe-alloy thin-multilayer quantum well structures grown on Si have been produced on this principle, and although light emission with greatly improved efficiency has been obtained at low temperatures the emission at room temperature is still very weak, because of exciton dissociation. Recently, through employing novel band-gap engineering strategies, we have prepared several different entirely new bright light-emitting Si/Ge nanostructures including one possessing a direct gap. The latter structure is based on constructing a new super unit cell comprised of multiple planar epitaxial layers of Si and Ge grown on (001) Si0.4Ge0.6. Others are based on silicon-germanium layers grown epitaxially on silicon in in such a way as to form multiple layer three-dimensional nanostructures (quantum dots). Lastly, we have developed a simple and efficient electrochemical process that combines galvanic reaction and focused-ion-beam lithography to selectively synthesize gold nanoparticles that are consequently used for the growth of ordered SiGe nanowire arrays with predefined diameter (200 nm) and position. Here we report on the optical properties of such Si/Ge nanostructures, which are found to luminesce efficiently at wavelengths in the important spectral range of 1.1–1.6 μm. This work has been carried out in collaboration with J.-M. Baribeau and N.L. Rowell, National Research Council, Ottawa, Canada; L. Tsybeskov, New Jersey Institute of Technology, Newark, USA; and I. Berbezier, Institut Matériaux Microélectronique Nanosciences de Provence, Marseille, France.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.026
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

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 integrity0.0010.001
Insufficient payload (model declined to judge)0.0260.020

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 head0.012
GPT teacher head0.218
Teacher spread0.207 · 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 source (direct Gemma or distilled Codex), 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
Published2015
Admission routes2
Has abstractyes

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