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Record W2408256525 · doi:10.1021/acsami.5b03543

(Ag,Cu)–Ta–O Ternaries As High-Temperature Solid-Lubricant Coatings

2015· article· en· W2408256525 on OpenAlexafffund
Hongyu Gao, Alberto Otero‐de‐la‐Roza, Jingjing Gu, D. S. Stone, Samir Aouadi, Erin R. Johnson, Ashlie Martini

Bibliographic record

VenueACS Applied Materials & Interfaces · 2015
Typearticle
Languageen
FieldEngineering
TopicMetal and Thin Film Mechanics
Canadian institutionsDalhousie UniversityNational Institute for Nanotechnology
FundersMinisterio de Ciencia e InnovaciónAir Force Office of Scientific ResearchAlberta Innovates - Technology Futures
KeywordsMaterials scienceLubricantTribologyMolecular dynamicsTernary operationOxideDensity functional theoryMetalWork (physics)ThermodynamicsComposite materialChemical physicsMetallurgyComputational chemistry

Abstract

fetched live from OpenAlex

Ternary oxides have gained increasing attention due to their potential use as solid lubricants at elevated temperatures. In this work, the tribological properties of three ternary oxides-AgTaO3, CuTaO3, and CuTa2O6-were studied using a combination of density-functional theory (DFT), molecular dynamics (MD) simulations with newly developed empirical potential parameters, and experimental measurements (AgTaO3 and CuTa2O6 only). Our results show that the MD-predicted friction force follows the trend AgTaO3 < CuTaO3 < CuTa2O6, which is consistent with the experimentally measured coefficients of friction. The wear performance from both MD and experiment exhibits the opposite trend, with CuTa2O6 providing the best resistance to wear. The sliding mechanisms are investigated using experimental characterization of the film composition after sliding, quantification of Ag or Cu cluster formation at the interface during the evolution of the film in MD, and DFT energy barriers for atom migration on the material surface. All our observations are consistent with the hypothesis that the formation of metal (or metal oxide) clusters on the surface are responsible for the friction and wear behavior of these materials.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.006
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.001

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 head0.013
GPT teacher head0.221
Teacher spread0.208 · 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.

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

Citations48
Published2015
Admission routes2
Has abstractyes

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