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Record W4402592757 · doi:10.1109/led.2024.3462949

80 Gbps PAM-4 Data Transmission With 940 nm VCSELs Grown on a 330 μm Ge Substrate

2024· article· en· W4402592757 on OpenAlexaff
Yun-Cheng Yang, Zeyu Wan, Chih-Chuan Chiu, I-Chi Liu, Guangrui Xia, Chao‐Hsin Wu

Bibliographic record

VenueIEEE Electron Device Letters · 2024
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsUniversity of British Columbia
FundersNational Chung-Shan Institute of Science and TechnologyNational Science and Technology CouncilTaiwan Semiconductor Manufacturing Company
KeywordsOptoelectronicsSubstrate (aquarium)Materials scienceTransmission (telecommunications)Gallium arsenideOpticsPhysicsComputer scienceTelecommunications

Abstract

fetched live from OpenAlex

940 nm oxide-confined vertical-cavity surface-emitting lasers (VCSELs) on$330~\mu $m thick Ge bulk substrates were fabricated and characterized, presenting a novel approach to VCSEL manufacturing. The wafer surfaces demonstrated high smoothness and flatness, with a peak-to-valley wafer distortion of$50.3~\mu $m, a root mean square roughness (Rq) of 1.34 nm, and an average wafer bow-warp of$3.77~\mu $m. The Fabry-Pérot dip precisely aligned with the target wavelength, while stopband center mapping exhibited excellent uniformity across the wafer, with a 1.937 nm (0.206%) standard deviation. At 300 K, the Ge-based VCSEL with a$6~\mu $m oxide aperture achieved an optical peak power of 5.5 mW and a maximum modulation bandwidth of 19.8 GHz, with a roll-over current surpassing 16 mA. Furthermore, the device demonstrated successful data transmission at 53.125 Gbps and 80 Gbps using PAM-4 modulation, achieving transmitter and dispersion eye closure quaternary (TDECQ) penalties of 1.36 dB and 4.70 dB, respectively. These results underscore the potential of thin Ge substrates in advancing VCSEL technology for high-speed optical communication applications.

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 score0.003
Threshold uncertainty score0.011

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.016
GPT teacher head0.235
Teacher spread0.220 · 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

Citations5
Published2024
Admission routes1
Has abstractyes

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