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Record W2996818948 · doi:10.1002/smll.201906540

2D Antimony–Arsenic Alloys

2019· article· en· W2996818948 on OpenAlexafffund
Matthieu Fortin‐Deschênes, Olga Waller, Qi An, Maureen J. Lagos, Gianluigi A. Botton, Hong Guo, Oussama Moutanabbir

Bibliographic record

VenueSmall · 2019
Typearticle
Languageen
FieldMaterials Science
Topic2D Materials and Applications
Canadian institutionsMcMaster UniversityMcGill UniversityPolytechnique Montréal
FundersPRIMA QuébecNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsCanada Foundation for Innovation
KeywordsAntimonyArsenicRaman spectroscopyX-ray photoelectron spectroscopyMaterials scienceAlloyArsenideGrapheneArsineHeterojunctionMolecular beam epitaxySemiconductorEpitaxyChemical engineeringNanotechnologyMetallurgyChemistryGallium arsenideOptoelectronicsCatalysis

Abstract

fetched live from OpenAlex

Abstract Alloying in group V 2D materials and heterostructures is an effective degree of freedom to tailor and enhance their physical properties. Up to date, black arsenic‐phosphorus is the only 2D group V alloy that has been experimentally achieved by exfoliation, leaving all other possible alloys in the realm of theoretical predictions. Herein, the existence of an additional alloy consisting of 2D antimony arsenide (2D‐As x Sb 1− x ) grown by molecular beam epitaxy on group IV semiconductor substrates and graphene is demonstrated. The atomic mixing of As and Sb in the lattice of the grown 2D layers is confirmed by low‐energy electron diffraction, Raman spectroscopy, and X‐ray photoelectron spectroscopy. The As content in 2D‐As x Sb 1− x is shown to depend linearly on the As 4 /Sb 4 deposition rate ratio and As concentrations up to 15 at% are reached. The grown 2D alloys are found to be stable in ambient conditions in a timescale of weeks but to oxidize after longer exposure to air. This study lays the groundwork for a better control of the growth and alloying of group V 2D materials, which is critical to study their basic physical properties and integrate them in novel applications.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.120
Threshold uncertainty score0.997

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)0.0040.014

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 head0.234
Teacher spread0.217 · 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; both teacher heads agree on what is shown here.

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

Citations11
Published2019
Admission routes2
Has abstractyes

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