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Record W2064447523 · doi:10.1063/1.2709615

Strain relaxation in (100) and (311) GaP∕GaAs thin films

2007· article· en· W2064447523 on OpenAlexaff
Y. Li, M. Niewczas

Bibliographic record

VenueJournal of Applied Physics · 2007
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSemiconductor Quantum Structures and Devices
Canadian institutionsMcMaster UniversityBrockhouse Institute for Materials Research
Fundersnot available
KeywordsMaterials scienceCondensed matter physicsTransmission electron microscopyCrystal twinningRelaxation (psychology)DislocationThin filmBand gapStress relaxationMolecular beam epitaxyEpitaxySurface energyAnisotropySubstrate (aquarium)CrystallographyOpticsNanotechnologyComposite materialOptoelectronicsChemistryMicrostructureCreepPhysics

Abstract

fetched live from OpenAlex

The nature of strain relaxation in GaP films grown on (100), (311)A, and (311)B GaAs by molecular beam epitaxy has been studied by transmission electron microscopy and atomic force microscopy. It is found that (100) GaP∕GaAs films develop surface undulations with twinning and cracking. (311)A GaAs provides good growth orientation for GaP films, producing flat surfaces and crack-free films. Similarly, (311)B GaP∕GaAs films do not develop cracks, however, the surface is rough. The anisotropy of cracking observed in GaP films has been discussed in terms of a lattice trapping theory. Twinning is an effective form of stress relaxation in GaP films. The features of the dislocation structure produced during relaxation have been discussed in terms of energy considerations. The data suggest that the equilibrium position of misfit dislocations is located in the softer substrate where the total energy of the system is a minimum. During relaxation, those dislocations which acquire larger kinetic energy can move over the small energy well and penetrate deeper into the substrate, in agreement with transmission electron microscope observations.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.234
Threshold uncertainty score0.421

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 head0.017
GPT teacher head0.264
Teacher spread0.247 · 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 designTheoretical or conceptual
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

Citations12
Published2007
Admission routes1
Has abstractyes

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