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Record W2129009260 · doi:10.1117/12.910701

Surface and interface study of SiO2-x coated InP/InGaAs/InGaAsP semiconductor laser microstructures processed in the soft KrF laser irradiation regime

2011· article· en· W2129009260 on OpenAlexaff
Neng Liu, Sonia Blais, Jan J. Dubowski

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2011
Typearticle
Languageen
FieldEngineering
TopicLaser Material Processing Techniques
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsMaterials scienceExcimer laserLaserIrradiationX-ray photoelectron spectroscopyOptoelectronicsGallium arsenideMicrostructureLayer (electronics)DiffusionSemiconductorOpticsNanotechnologyComposite material

Abstract

fetched live from OpenAlex

The ability of a UV laser to modify surface properties of quantum well (QW) microstructures that would lead to formation of a "defective layer" is of particular interest to the process of QW intermixing (QWI). We discuss the results of surface and interface study of InGaAs/InGaAsP QW microstructures capped with InP and a 243-nm thick layer of SiO<sub>2-x</sub> that were irradiated with a KrF excimer laser delivering up to 25 pulses at 124 mJ/cm<sup>2</sup>. The optical quality of SiO<sub>2</sub> films remains relatively unaffected by the irradiation with the KrF laser operating in the investigated window of parameters. The x-ray photoelectron spectroscopy experiments point out the negligible role of SiO<sub>2-x</sub> in out-diffusion of matrix atoms that would enhance the QWI process. However, the KrF laser was found to significantly modify the interface between UV transparent SiO<sub>2-x</sub> and the InP layer. Our results suggest that the resulting layer of the altered material promotes out-diffusion of atoms and intermixing in the QW region.

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 categoriesMeta-epidemiology (narrow)
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 score0.014
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.233
Teacher spread0.216 · 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.

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

Citations4
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicLaser Material Processing TechniquesFrench-language works237,207