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Electrical transport in InAs/GaSb superlattice: role of surface states and interface roughness

2012· article· en· W2002779682 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSemiconductor Science and Technology · 2012
Typearticle
Languageen
FieldEngineering
TopicAdvanced Semiconductor Detectors and Materials
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSuperlatticePseudopotentialCondensed matter physicsScatteringSurface finishMaterials scienceElectronThermal conductionElectron mobilityChemistryOpticsPhysics

Abstract

fetched live from OpenAlex

We have modeled electrical properties of InAs/GaSb superlattice (SL) using band structure calculations based on an atomistic empirical pseudopotential method and mobility estimates. The model quantitatively explains the experimental results obtained on a SL sample using the technique of 'quantitative mobility spectrum analysis (QMSA)'. We show that the factors that influence in-plane electrical transport in this system are different under low- and high-temperature regimes. This difference primarily arises from the location of conducting regions. At lower temperatures the electron density, emanating from the defects in a cap GaSb layer, is essentially confined to a few wells near the surface of the SL. At higher temperatures, conduction is dominated by thermally excited carriers which are more uniformly spread over the entire SL. We identify dominant scattering mechanisms that limit the electron mobility under both regimes and show that interface roughness plays a significant role in the high-temperature regime.

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.

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 score0.026
Threshold uncertainty score0.582

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.007
GPT teacher head0.233
Teacher spread0.227 · 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