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Record W2004080884 · doi:10.1116/1.2723761

Study of intersubband transitions of ZnxCd1−xSe∕Znx′Cdy′Mg1−x′−y′Se multiple quantum wells grown by molecular beam epitaxy for midinfrared device applications

2007· article· en· W2004080884 on OpenAlexaff
Hong Lü, Aidong Shen, M. C. Tamargo, William Charles, I. Yokomizo, Manuel Muñoz, Yinyan Gong, G. F. Neumark, Kale J. Franz, Claire Gmachl, C. Y. Song, H. C. Liu

Bibliographic record

VenueJournal of Vacuum Science & Technology B Microelectronics and Nanometer Structures Processing Measurement and Phenomena · 2007
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSemiconductor Quantum Structures and Devices
Canadian institutionsInstitute for Microstructural Sciences
Fundersnot available
KeywordsMolecular beam epitaxyQuantum wellFourier transform infrared spectroscopySpectroscopyInfraredMaterials scienceInfrared spectroscopyAbsorption spectroscopyAbsorption edgeAbsorption (acoustics)OptoelectronicsChemistryAnalytical Chemistry (journal)Band gapEpitaxyOpticsLayer (electronics)PhysicsNanotechnologyLaser

Abstract

fetched live from OpenAlex

Two ZnxCd1−xSe∕Znx′Cdy′Mg1−x′−y′Se multiple quantum well structures were grown by molecular beam epitaxy. The quantum well layer thickness of the multiple quantum well region was varied in order to tune the intersubband transition energy. The high crystalline quality of the material was demonstrated by high resolution x-ray diffraction. Contactless electroreflectance (CER) spectroscopy and Fourier transform infrared (FTIR) spectroscopy were used to characterize the intersubband transitions. Excellent agreement between the estimated value obtained by CER and the value measured by FTIR was achieved. Intersubband absorption at 6.89 and 5.37μm was observed demonstrating the ability to tune the properties of these wide band gap II-VI materials for mid-IR intersubband device 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 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 score0.041
Threshold uncertainty score0.908

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 head0.018
GPT teacher head0.272
Teacher spread0.254 · 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

Citations6
Published2007
Admission routes1
Has abstractyes

Explore more

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