MétaCan
Menu
Back to cohort
Record W2800908889 · doi:10.1115/trib2004-64028

Effects of Lubricants on the Friction and Wear Properties of PTFE and POM

2004· article· en· W2800908889 on OpenAlexaff
H. S. Benabdallah, Jianjun Wei

Bibliographic record

VenueASME/STLE 2004 International Joint Tribology Conference, Parts A and B · 2004
Typearticle
Languageen
FieldEngineering
TopicTribology and Wear Analysis
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsMaterials scienceLubricationComposite materialWettingBoundary lubricationTribologyLubricityDry lubricantDry frictionHeat transferBall (mathematics)

Abstract

fetched live from OpenAlex

The friction and wear properties of PTFE and POM were investigated using a ball-on-steel ring tester under dry conditions and conditions lubricated by paraffin and 10W-30 oils. SEM, EDAX, FT-IR and surface wettability techniques were used to characterize and assess the morphology and chemical composition of the original surfaces as well as wear track, transfer film and wear debris for different loads and speeds. Although the friction was high, similar behaviours to those reported were observed. The experimentally determined surface temperature of the plastic revealed optimum loading levels for each sliding speed at which the friction and wear rates become minimal and the thermal effect stabilizes. In boundary-like lubrication using both oils, friction and wear were significantly reduced with the exception of an increase in wear rate with load when POM was lubricated with 10W-30 oil. Surface analysis revealed that the formation of lubricious protective layers on the surfaces in contact is crucial to reducing friction and more importantly wear. FT-IR results confirmed that film transfer occurs in the case of POM.

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 score0.278
Threshold uncertainty score0.290

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 head0.017
GPT teacher head0.200
Teacher spread0.183 · 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

Citations2
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueASME/STLE 2004 International Joint Tribology Conference, Parts A and BSame topicTribology and Wear AnalysisFrench-language works237,207