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Record W2606666070 · doi:10.1088/1361-6528/aa678d

Tunable bending stiffness of MoSe<sub>2</sub>/WSe<sub>2</sub> heterobilayers from flexural wrinkling

2017· article· en· W2606666070 on OpenAlexfundno aff
Yufeng Guo, Jiapeng Qiu, Wanlin Guo

Bibliographic record

VenueNanotechnology · 2017
Typearticle
Languageen
FieldMaterials Science
Topic2D Materials and Applications
Canadian institutionsnot available
FundersNational Key Research and Development Program of ChinaProgram for New Century Excellent Talents in UniversityFundamental Research Funds for the Central UniversitiesPriority Academic Program Development of Jiangsu Higher Education InstitutionsNanjing UniversityNanjing University of Aeronautics and AstronauticsInstitute of Nutrition, Metabolism and DiabetesState Key Laboratory of Mechanics and Control of Mechanical StructuresNational Natural Science Foundation of ChinaNational Science Foundation
KeywordsMaterials scienceWrinkleBending stiffnessBendingStiffnessComposite materialvan der Waals forceCompression (physics)Flexural strengthDeformation (meteorology)Flexural rigidity

Abstract

fetched live from OpenAlex

Abstract Understanding the mechanical behaviors of van der Waals heterogeneous 2D materials is important for their actual applications. Our extensive first-principles calculations and continuum mechanical modeling on the wrinkling of MoSe 2 /WSe 2 heterobilayers caused by compression reveal that the bending stiffness of MoSe 2 /WSe 2 wrinkles strongly depend on the wrinkle structures, which first increase and then decrease with increasing the compressive strain. The bending stiffness of MoSe 2 /WSe 2 wrinkles could be effectively mediated and tuned by adjusting the wrinkle geometry and size. The underlying mechanisms are elucidated by the differences in electronic structures and bonding states at the top, middle and bottom parts of the wrinkles, and the relevance of the changes of bond lengths to flexural deformation. Our results suggest a feasible way to develop flexible devices and nanoelectromechanical systems by utilizing the correlation and coupling between the mechanical and electronic properties in MoSe 2 /WSe 2 wrinkles.

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 categoriesMeta-epidemiology (narrow)
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 score0.011
Threshold uncertainty score1.000

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 studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.000
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 head0.018
GPT teacher head0.255
Teacher spread0.237 · 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.

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

Citations8
Published2017
Admission routes1
Has abstractyes

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