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Record W3189078404 · doi:10.1039/d1nr03001a

Theoretical modeling of structural superlubricity in rotated bilayer graphene, hexagonal boron nitride, molybdenum disulfide, and blue phosphorene

2021· article· en· W3189078404 on OpenAlexafffund
Tilas Kabengele, Erin R. Johnson

Bibliographic record

VenueNanoscale · 2021
Typearticle
Languageen
FieldMaterials Science
TopicGraphene research and applications
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhosphoreneMolybdenum disulfideMaterials scienceGrapheneHexagonal boron nitrideBoron nitrideBilayerDensity functional theoryNanotechnologyBoropheneHexagonal crystal systemCrystallographyChemistryComputational chemistryComposite materialMembrane

Abstract

fetched live from OpenAlex

, and the novel material blue phosphorene (b-P) using dispersion-corrected density-functional theory with periodic boundary conditions. Potential energy surfaces for interlayer sliding were computed for the standard (1 × 1) cell and three rotated, Moiré unit cells for each material. The energy barriers to form the rotated structures remain higher than the minimum-energy sliding barriers for the (1 × 1) cells. However, if the rotational barriers can be overcome, nearly barrierless interlayer sliding is observed in the rotated cells for all four materials. This is the first density-functional investigation of friction using rotated, Moiré cells, and the first prediction of structural superlubricty for b-P.

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 score0.040
Threshold uncertainty score0.594

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.262
Teacher spread0.250 · 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

Citations27
Published2021
Admission routes2
Has abstractyes

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