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Record W4391388944 · doi:10.1364/oe.513997

Monolithically integrated 940 nm VCSELs on bulk Ge substrates

2024· article· en· W4391388944 on OpenAlex
Zeyu Wan, Yun-Cheng Yang, Wei‐Hsin Chen, Chih-Chuan Chiu, Yunlong Zhao, Markus Feifel, Lukas Chrostowski, David Lackner, Chao‐Hsin Wu, Guangrui Xia

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

VenueOptics Express · 2024
Typearticle
Languageen
FieldEngineering
TopicSemiconductor Lasers and Optical Devices
Canadian institutionsUniversity of British Columbia
FundersUniversity of British Columbia
KeywordsVertical-cavity surface-emitting laserFabricationMaterials scienceOptoelectronicsWaferSubstrate (aquarium)EpitaxyOpticsLayer (electronics)LaserGallium arsenideSurface roughnessNanotechnology

Abstract

fetched live from OpenAlex

This research successfully developed an independent Ge-based VCSEL epitaxy and fabrication technology route, which set the stage for integrating AlGaAs-based semiconductor devices on bulk Ge substrates. This is the second successful Ge-based VCSEL technology reported worldwide and the first Ge-based VCSEL technology with key details disclosed, including Ge substrate specification, transition layer structure and composition, and fabrication process. Compared with the GaAs counterparts, after epitaxy optimization, the Ge-based VCSEL wafer has a 40% lower surface root-mean-square roughness and 72% lower average bow-warp. After device fabrication, the Ge-based VCSEL has a 10% lower threshold current density and 19% higher maximum optical differential efficiency than the GaAs-based VCSEL.

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 score0.541
Threshold uncertainty score0.748

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 head0.015
GPT teacher head0.233
Teacher spread0.218 · 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