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Record W4389922054 · doi:10.1109/lpt.2023.3344355

Monolithically Integrated 940 nm Half VCSELs on Bulk Ge Substrates

2023· article· en· W4389922054 on OpenAlexaff
Yunlong Zhao, Zeyu Wan, Jia Guo, Yun-Cheng Yang, Hao-Tien Cheng, Lukas Chrostowski, David Lackner, Chao‐Hsin Wu, Guangrui Xia

Bibliographic record

VenueIEEE Photonics Technology Letters · 2023
Typearticle
Languageen
FieldEngineering
TopicSemiconductor Lasers and Optical Devices
Canadian institutionsUniversity of British Columbia
FundersHuawei Technologies
KeywordsOptoelectronicsMaterials scienceGallium arsenideIntegrated opticsOpticsPhysics

Abstract

fetched live from OpenAlex

High-quality n-type AlGaAs distributed Bragg reflectors (DBRs) and lnGaAs multiple quantum wells (MQWs) were successfully monolithically grown on 4-inch off-cut Ge (100) wafers. Even without any design and process optimization for the Ge substrates, the Ge-based half VCSELs have photoluminescence and reflectance spectra comparable to those grown on conventional GaAs wafers. Flat and sub-nm RMS surface roughness and uniform DBR and MQW growth across the wafer were achieved. These results strongly support full VCSEL growth and fabrication on larger-area Ge wafers for the mass production of AlGaAs-based VCSELs.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.220
Teacher spread0.208 · 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

Citations3
Published2023
Admission routes1
Has abstractyes

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