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Record W4307037633 · doi:10.1002/ls.1629

Flow and slip process of Santotrac 50‐based lubricant under high shear by molecular dynamic simulation

2022· article· en· W4307037633 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

VenueLubrication Science · 2022
Typearticle
Languageen
FieldChemical Engineering
TopicRheology and Fluid Dynamics Studies
Canadian institutionsUniversité Laval
FundersNational Natural Science Foundation of China
KeywordsSlip (aerodynamics)Slip line fieldMaterials scienceWettingShear rateLubricantShear (geology)Shear stressMechanicsLubricationMolecular dynamicsShear flowSlip ratioCouette flowShear velocityComposite materialCritical resolved shear stressRheologyThermodynamicsChemistryFlow (mathematics)TurbulencePhysicsComputational chemistry

Abstract

fetched live from OpenAlex

Abstract We investigate flow and slip behaviour of Santotrac 50 molecules under high shear in Couette cell by means of Molecular Dynamic simulation to understand reduced friction force. Molecular chain stretches and oriented to shear direction, and move. Slip starts on metal surface at 2 × 10 8 s −1 , and increases with shear rate. Slip length keeps scale at nanometre. Molecular conformation and occurrence of slip both indicate a reduced shear stress. Furthermore, when changing wettability, slip length increases in power law and thus decreases shear stress greatly. Occurrence of low‐density region near surface can explain slip. And thus, we extended apparent slip model, which divided lubricant into liquid layers with different viscosities, to elucidate the relationship between molecule distribution inner layer and slip on surface influenced by shear velocity and wettability. Above all, our research sheds light on flow and slip behaviour of complex fluid and can be applied in improving lubrication property.

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)0.000
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.552
Threshold uncertainty score0.374

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)0.0000.000

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 head0.006
GPT teacher head0.263
Teacher spread0.256 · 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