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Record W2283975390 · doi:10.1149/ma2015-01/9/859

Degradation and Electronic Confinement in Exfoliated Black Phosphorus

2015· article· en· W2283975390 on OpenAlexaff
Richard Martel, Étienne Gaufrès, Alexandre Favron, Frédéric Fossard, Anne-Laurence Phaneuf, Pierre L. Lévesque, Annick Loiseau, R. Leonelli, S. Francoeur

Bibliographic record

VenueECS Meeting Abstracts · 2015
Typearticle
Languageen
FieldMaterials Science
Topic2D Materials and Applications
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsPhosphoreneRaman spectroscopyMonolayerMaterials scienceDegradation (telecommunications)GrapheneLayer (electronics)Lamellar structureChemical engineeringCrystal (programming language)Band gapOptoelectronicsNanotechnologyOpticsComposite material

Abstract

fetched live from OpenAlex

Thin layers of black phosphorus have recently raised interest for their two-dimensional (2D) semiconducting properties, such as tunable bandgap with layer thickness and high carrier mobilities. This lamellar crystal of P atoms can be exfoliated down to monolayer 2D-phosphane (also called phosphorene) using procedures similar to that for monolayer graphene. The devices are however challenging to fabricate due to fast degradation of the thin layers upon exposure to light in air. We investigated this degradation process using in-situ Raman and transmission electron spectroscopies and reported on a thickness dependent reactivity of the layers. Moreover, the degradation process was identified to be due to an ubiquitous photo-induced oxidation of the layers by adsorbed oxygen in water. Optimum experimental conditions to prepare n-layer 2D-phosphane in their pristine states were applied to determine the Raman signatures of degradation. Here, we report on the kinetics of the photo-oxidation and provide sigantures in the Raman spectra that could be used to assess the crystal quality.

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)0.001
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 score0.020
Threshold uncertainty score0.365

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.023
GPT teacher head0.258
Teacher spread0.235 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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