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Record W2074208849 · doi:10.1063/1.4796104

Investigation of cross-hatch in In0.3Ga0.7As pseudo-substrates

2013· article· en· W2074208849 on OpenAlexaff
Sudip Saha, Daniel T. Cassidy, D. A. Thompson

Bibliographic record

VenueJournal of Applied Physics · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSemiconductor Quantum Structures and Devices
Canadian institutionsMcMaster University
Fundersnot available
KeywordsNucleationMaterials sciencePhotoluminescenceSubstrate (aquarium)Atomic force microscopyCrystallographyCondensed matter physicsMetamorphic rockPolarization MicroscopyLattice constantMicroscopyChemistryOpticsNanotechnologyDiffractionGeologyOptoelectronicsPhysics

Abstract

fetched live from OpenAlex

Metamorphic buffer layers offer a wide variety of lattice constants for substrate on which devices can be grown. However, almost in all cases, the surface of the pseudo-substrate contains striations which are known as “cross-hatch.” Although, it is accepted that this surface undulation is related with the underlying gridlike misfit dislocations (MDs), the exact correlation is still to be determined. In this article, degree of polarization of photoluminescence maps and atomic force microscopy were used to analyze the correlation between surface undulation and the underlying strain field of the pseudo-substrate. From the correlation, it can be said that the surface undulation is not formed after MD nucleation, but MDs form in some of the troughs of the undulation.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.019
GPT teacher head0.262
Teacher spread0.243 · 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 source (direct Gemma or distilled Codex), 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

Citations14
Published2013
Admission routes1
Has abstractyes

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