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Record W2053503250 · doi:10.1063/1.1785867

Optimized GaAs∕AlGaAs light-emitting diodes and high efficiency wafer-fused optical up-conversion devices

2004· article· en· W2053503250 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Applied Physics · 2004
Typearticle
Languageen
FieldEngineering
TopicSemiconductor Lasers and Optical Devices
Canadian institutionsInstitute for Microstructural Sciences
FundersMinistère de la Défense Nationale
KeywordsOptoelectronicsLight-emitting diodeQuantum efficiencyMaterials scienceWaferDiodePhotodetectorDopingCurrent densityGallium arsenideQuantum wellOpticsLaserPhysics

Abstract

fetched live from OpenAlex

Achieving a high internal quantum efficiency in GaAs∕AlGaAs based light-emitting diodes (LEDs) for room-temperature operation at low current-density injection is crucial for applications such as optical up-converters based on the integration of LEDs and photodetectros. We report the experimental results as well as the theoretical analyses of the internal quantum efficiency of GaAs∕AlGaAs LEDs as a function of the p-doping concentration of the active region for low current injection operation. By optimizing the doping concentration, we have achieved a close to 100% internal quantum efficiency for room-temperature operation of LEDs in the low injection current-density range, i.e., around 0.1A∕cm2. An optical up-converter was fabricated using wafer-fusion technology by integrating the optimized GaAs∕AlGaAs LED with an InGaAs∕InP photodetector. The internal up-conversion quantum efficiency was measured to be 76%.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.571
Threshold uncertainty score0.761

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 head0.008
GPT teacher head0.203
Teacher spread0.195 · 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