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Record W2555735528 · doi:10.1080/21663831.2016.1256915

Toward edges-rich MoS<sub>2</sub> layers via chemical liquid exfoliation triggering distinctive magnetism

2016· article· en· W2555735528 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMaterials Research Letters · 2016
Typearticle
Languageen
FieldMaterials Science
Topic2D Materials and Applications
Canadian institutionsUniversité de Montréal
FundersEuskal Herriko UnibertsitateaNational Natural Science Foundation of China
KeywordsFerromagnetismMaterials scienceDiamagnetismExfoliation jointMagnetismMolybdenum disulfideCondensed matter physicsX-ray photoelectron spectroscopyGrapheneTransmission electron microscopyChemical physicsCrystallographyNanotechnologyMagnetic fieldNuclear magnetic resonanceMetallurgyChemistryPhysics

Abstract

fetched live from OpenAlex

The magnetic function of layered molybdenum disulfide (MoS2) has been investigated via simulation, but few reliable experimental results have been explored. Herein, we developed edges-rich structural MoS2 nanosheets via liquid phase exfoliation approach, triggering exceptional ferromagnetism. The magnetic measurements revealed the clear ferromagnetic property of layered MoS2, compared to the pristine MoS2 in bulk exhibiting diamagnetism. The existence of ferromagnetism mostly was attributed to the presence of grain boundaries with abundant irregular edges confirmed by the transmission electron microscopy, magnetic force microscopy and X-ray photoelectron spectroscopy, which experimentally provided reliable evidences on irregular edges-rich states engineering ferromagnetism to clarify theoretical calculation.

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient 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 score0.011
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.003

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 head0.046
GPT teacher head0.300
Teacher spread0.254 · 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