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Record W2054373437 · doi:10.1116/1.1591738

Impact of quantum well intermixing on polarization anisotropy of InGaAs/InGaAsP quantum well modulators

2003· article· en· W2054373437 on OpenAlexaff
Simon Ng, H. S. Djie, H.S. Lim, Y.L. Lam, Y.C. Chan, P. Dowd, B. S. Ooi, Vincent Aimez, Jacques Beauvais, J. Beerens

Bibliographic record

VenueJournal of Vacuum Science & Technology B Microelectronics and Nanometer Structures Processing Measurement and Phenomena · 2003
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSemiconductor Quantum Structures and Devices
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsQuantum wellMaterials sciencePolarization (electrochemistry)AnisotropyOptoelectronicsCondensed matter physicsWaferAnnealing (glass)Transverse planeGallium arsenideOpticsChemistryPhysicsLaserComposite material

Abstract

fetched live from OpenAlex

This article reports on the impact of the induced strain on the polarization anisotropy of a parallel set of electroabsorption intensity modulators on a single InGaAs/InGaAsP wafer chip. The strain build up due to the interdiffusion of atomic species across the quantum well region has been demonstrated experimentally using the gray mask-based quantum well intermixing process followed by an annealing step. A voltage swing of 5 V and an intensity modulation depth of more than −15 dB has been measured from these modulators. An interdiffusion process modeling has been developed to investigate the consequence of different interdiffusion ratios between the group III and the group V sublattices on the polarization behavior of these modulators, owing to the strain build up and the refractive index profiles for both transverse electric and transverse magnetic modes. The numerical modeling agrees with the experimental results, which indicates that the degree of intermixing on the group V sublattices is more significant compared to that of group III sublattices, hence causing a strained material system after an intermixing process and thus resulting in with polarization insensitive devices.

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)0.001
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 score0.174
Threshold uncertainty score0.973

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
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 head0.013
GPT teacher head0.259
Teacher spread0.246 · 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

Citations2
Published2003
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Vacuum Science & Technology B Microelectronics and Nanometer Structures Processing Measurement and PhenomenaSame topicSemiconductor Quantum Structures and DevicesFrench-language works237,207