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Record W4327936142 · doi:10.1117/12.2650505

Investigating the effect of energy level spacing and inhomogeneous broadening on performance of quantum dash ridge-wavelengths lasers at elevated temperatures

2023· article· en· W4327936142 on OpenAlexaff
S. Schaefer, Ras-Jeevan K. Obhi, Christopher E. Valdivia, Philip J. Poole, Pedro Barrios, Jiaren Liu, Zhenguo Lü, Karin Hinzer

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSemiconductor Quantum Structures and Devices
Canadian institutionsNational Research Council CanadaUniversity of Ottawa
Fundersnot available
KeywordsDashThermionic emissionMaterials scienceLaserOptoelectronicsWavelengthRidgeStack (abstract data type)Quantum wellQuantumAsymmetryOpticsPhysicsElectronComputer science

Abstract

fetched live from OpenAlex

Using a model developed in Crosslight PICS3D, we have compared simulated gain and device performance for InAs/InP quantum dash ridge waveguide lasers with experimental data from fabricated devices. We investigated the change in device behaviour as the energy spectrum of the dashes is varied and inhomogeneous broadening is changed to represent a distribution of dash sizes and composition. We observed a distinct asymmetry of the dash layer occupation due to inefficient thermionic emission hindering hole transport across the quantum dash layer stack. We have quantified how this effect can be utilized to achieve higher threshold current temperature stability.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.297
Threshold uncertainty score0.508

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 head0.016
GPT teacher head0.241
Teacher spread0.225 · 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 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

Citations0
Published2023
Admission routes1
Has abstractyes

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