MétaCan
Menu
Back to cohort
Record W4382312339 · doi:10.1016/j.rsurfi.2023.100117

Binary and ternary lubricious oxides for high temperature tribological applications: A review

2023· review· en· W4382312339 on OpenAlex
Amit Roy, Payank Patel, Navid Sharifi, Richard R. Chromik, Pantcho Stoyanov, Christian Moreau

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueResults in Surfaces and Interfaces · 2023
Typereview
Languageen
FieldEngineering
TopicMetal and Thin Film Mechanics
Canadian institutionsConcordia UniversityMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaConsortium de Recherche et d’innovation en Aérospatiale au Québec
KeywordsTribologyMaterials scienceTernary operationOxideFriction coefficientDry lubricantMetallurgyCoefficient of frictionComposite materialComputer science

Abstract

fetched live from OpenAlex

Oxides and oxide-based coatings have been widely used as solid lubricants in demanding operating conditions to achieve low friction and wear due to their higher thermal and chemical stability. However, their tribological performance is highly dependent on the test temperatures and the surrounding environment. This article provides a comprehensive review of low-friction oxides and oxide-based coatings in relation to the influence of operating temperature on their tribological performance and their potential use as solid lubricants. Special emphasis is placed on the tribological behavior of binary and ternary oxides developed over the last few decades. Furthermore, this review summarizes the high temperature tribology, mechanisms and interfacial processes of the oxides leading to low friction coefficient and wear in high temperature applications.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.940
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
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 head0.051
GPT teacher head0.313
Teacher spread0.262 · 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