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Record W4404176660 · doi:10.1117/12.3034223

Application-based optimization of oxide-confined VCSEL

2024· article· en· W4404176660 on OpenAlexaff
A. I. Nashed, Michel Lestrade, Zhi Qiang Li, Zhanming Simon Li

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSemiconductor Lasers and Optical Devices
Canadian institutionsCrosslight Software (Canada)
Fundersnot available
KeywordsVertical-cavity surface-emitting laserMaterials scienceComputer scienceOxideOptoelectronicsLaserOpticsPhysicsMetallurgy

Abstract

fetched live from OpenAlex

In this work, we present the simulation and analysis of an oxide-confined Vertical-Cavity Surface-Emitting Laser (VCSEL) using the Finite Difference Frequency Domain (FDFD) microcavity model, integrated within the Crosslight’s PICS3D simulation package. By utilizing a full vectorial microcavity approach, both fundamental and higher-order optical modes are accurately captured, offering detailed insights into the effects of key structural parameters of the optical cavity. This study focuses on the impact of the oxide layer’s position and thickness on mode behavior, lasing mode selection, and threshold current in large-aperture VCSELs. The optimized VCSEL design achieves a threshold current of 0.7 mA and a far-field divergence angle of approximately 8°.

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 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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.920
Threshold uncertainty score0.421

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 head0.006
GPT teacher head0.205
Teacher spread0.199 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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
Published2024
Admission routes1
Has abstractyes

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