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Record W3046308230 · doi:10.1002/adma.202003020

Effect of Adventitious Carbon on Pit Formation of Monolayer MoS<sub>2</sub>

2020· article· en· W3046308230 on OpenAlexaff
Sangwook Park, Samira Siahrostami, Joonsuk Park, Amir Hassan Bagherzadeh Mostaghimi, Taeho Roy Kim, Lauren Vallez, Thomas Mark Gill, Woosung Park, Kenneth E. Goodson, Robert Sinclair, Xiaolin Zheng

Bibliographic record

VenueAdvanced Materials · 2020
Typearticle
Languageen
FieldMaterials Science
Topic2D Materials and Applications
Canadian institutionsUniversity of Calgary
FundersKwanjeong Educational FoundationNational Research Foundation of Korea
KeywordsMonolayerMolybdenum disulfideMaterials scienceSulfurTransmission electron microscopyOxygenCatalysisAdsorptionDensity functional theoryMolybdenumCarbon fibersNanoparticleChemical engineeringNanotechnologyPhysical chemistryChemistryComputational chemistryOrganic chemistryMetallurgyComposite material

Abstract

fetched live from OpenAlex

Abstract Forming pits on molybdenum disulfide (MoS 2 ) monolayers is desirable for (opto)electrical, catalytic, and biological applications. Thermal oxidation is a potentially scalable method to generate pits on monolayer MoS 2 , and pits are assumed to preferentially form around undercoordinated sites, such as sulfur vacancies. However, studies on thermal oxidation of MoS 2 monolayers have not considered the effect of adventitious carbon (C) that is ubiquitous and interacts with oxygen at elevated temperatures. Herein, the effect of adventitious C on the pit formation on MoS 2 monolayers during thermal oxidation is studied. The in situ environmental transmission electron microscopy measurements herein show that pit formation is preferentially initiated at the interface between adventitious C nanoparticles and MoS 2 , rather than only sulfur vacancies. Density functional theory (DFT) calculations reveal that the C/MoS 2 interface favors the sequential adsorption of oxygen atoms with facile kinetics. These results illustrate the important role of adventitious C on pit formation on monolayer MoS 2 .

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.698

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.007
GPT teacher head0.240
Teacher spread0.232 · 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

Citations17
Published2020
Admission routes1
Has abstractyes

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