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Record W2081314612 · doi:10.1063/1.4761970

Lattice-registered growth of GaSb on Si (211) with molecular beam epitaxy

2012· article· en· W2081314612 on OpenAlexafffund
S. Hosseini Vajargah, Shahram Ghanad-Tavakoli, J. S. Prestón, Gianluigi A. Botton, R. N. Kleiman

Bibliographic record

VenueJournal of Applied Physics · 2012
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSemiconductor Quantum Structures and Devices
Canadian institutionsMcMaster UniversityBrockhouse Institute for Materials Research
FundersNatural Sciences and Engineering Research Council of CanadaMcMaster UniversityOntario Centres of Excellence
KeywordsMolecular beam epitaxyMaterials scienceEpitaxyCrystal twinningCrystallographyCondensed matter physicsLattice (music)Transmission electron microscopyPerpendicularDislocationChemistryMicrostructureNanotechnologyGeometryPhysics

Abstract

fetched live from OpenAlex

A GaSb film was grown on a Si(211) substrate using molecular beam epitaxy indicating full lattice relaxation as well as full lattice registration and dislocation-free growth in the plane perpendicular to the [01 − 1]-direction. Heteroepitaxy of GaSb on a Si(211) substrate is dominated by numerous first order and multiple higher order micro-twins. The atomic-resolved structural study of GaSb films by high-angle annular dark-field scanning transmission electron microscopy reveals that slight tilt, along with twinning, favors the lattice registry to Si(211) substrates. Preferential bonding of impinging Ga and Sb atoms at the interface due to two distinctive bonding sites on the Si(211) surface enables growth that is sublattice-ordered and free of anti-phase boundaries. The role of the substrate orientation on the strain distribution of GaSb epilayers is further elucidated by investigating the local change in the lattice parameter using the geometric phase analysis method and hence effectiveness of the lattice tilting in reducing the interfacial strain was confirmed further.

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 score0.662
Threshold uncertainty score0.581

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 integrity0.0000.000
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 head0.015
GPT teacher head0.242
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

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
Published2012
Admission routes2
Has abstractyes

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