MétaCan
Menu
Back to cohort
Record W3187433446 · doi:10.1063/5.0057614

Influence of heating on the measured friction behavior of graphene evaluated under ultra-high vacuum conditions

2021· article· en· W3187433446 on OpenAlexafffund
Peng Gong, Philip Egberts

Bibliographic record

VenueApplied Physics Letters · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicForce Microscopy Techniques and Applications
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for InnovationAlberta Innovates - Technology Futures
KeywordsMaterials scienceHysteresisTilt (camera)Composite materialGrapheneStiffnessVacuum chamberSubstrate (aquarium)OxideSiliconUltra-high vacuumNanotechnologyCondensed matter physicsMetallurgy

Abstract

fetched live from OpenAlex

Atomic scale friction measurements of exfoliated graphene on a silicon oxide substrate were conducted under ultra-high vacuum (UHV) conditions using an atomic force microscope. Two groups of samples were prepared: one that was heated for 3 h at 800 °C in the UHV chamber and one that was not heated in the UHV chamber. The heated sample showed much lower friction, a lower pull-off force during unloading, and no hysteresis between loading and unloading friction measurements on the heated sample compared with the unheated sample. Additionally, a significantly higher tilt of the friction loop was observed in the unheated sample compared with no or very little tilt of friction loops in the heated sample. Interpretation of lateral forces using the Prandtl–Tomlinson model showed a significantly higher energy corrugation on the unheated sample, but similar lateral contact stiffnesses. Furthermore, no hysteresis in either the energy corrugation or lateral contact stiffness was observed in either sample, suggesting that friction hysteresis is less likely correlated with the energy corrugation and lateral contact stiffness. These observations suggest that surface contamination was present on the unheated sample, which is removed or reduced to undetectable levels on the heated sample. Furthermore, the study distinguishes features in the friction behavior induced by surface contamination with those associated with graphene's intrinsic properties.

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 score0.231
Threshold uncertainty score0.473

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.016
GPT teacher head0.268
Teacher spread0.252 · 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

Citations6
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueApplied Physics LettersSame topicForce Microscopy Techniques and ApplicationsFrench-language works237,207