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Record W2050333117 · doi:10.1063/1.4776236

The effective g-factor in In0.53Ga0.47As/In0.52Al0.48As quantum well investigated by magnetotransport measurement

2013· article· en· W2050333117 on OpenAlexaff
X. Z. Liu, Yonggang Xu, Guohui Yu, Laiming Wei, Tie Lin, S. L. Guo, J Chu, W. Z. Zhou, Yonggang Zhang, D. J. Lockwood

Bibliographic record

VenueJournal of Applied Physics · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSemiconductor Quantum Structures and Devices
Canadian institutionsNational Research Council Canada
FundersNational Natural Science Foundation of China
KeywordsDephasingCondensed matter physicsZeeman effectScatteringQuantum wellShubnikov–de Haas effectMagnetic fieldMagnetoresistanceScattering rateTilt (camera)Weak localizationMaterials sciencePhysicsFermi surfaceQuantum oscillationsOptics

Abstract

fetched live from OpenAlex

The magneotransport properties of a high carrier concentration and high mobility 20-nm thick In0.53Ga0.47As/In0.52Al0.48As quantum well (QW) are investigated by tilt angle dependent Shubnikov-de Haas oscillations and by weak antilocalization (WAL) in an in-plane magnetic field. The effective g-factor g* and zero field spin splitting Δ0 are extracted from tilt angle dependent beating pattern. We found that g* shows a dramatic reduction with increasing carrier density due to the increased effective band gap. Furthermore, an anomalously rapid suppression of the WAL effect with increasing in-plane magnetic field B|| is observed. This reveals that the total dephasing rate is not solely contributed by Zeeman splitting. The microroughness scattering in the QW is proposed to be another factor to cause the dephasing and thus responsible for this effect.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.357
Threshold uncertainty score0.923

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 integrity0.0000.001
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 head0.011
GPT teacher head0.214
Teacher spread0.203 · 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

Citations5
Published2013
Admission routes1
Has abstractyes

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