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Record W2328373915 · doi:10.1021/jp503673k

Chemical Basis of the Tribological Properties of AgTaO<sub>3</sub> Crystal Surfaces

2014· article· en· W2328373915 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

VenueThe Journal of Physical Chemistry C · 2014
Typearticle
Languageen
FieldEngineering
TopicLubricants and Their Additives
Canadian institutionsNational Institute for Nanotechnology
FundersAir Force Office of Scientific Research
KeywordsLubricantMaterials scienceTribologyInertChemical physicsMolecular dynamicsComposite materialCrystal (programming language)Surface energySurface (topology)ThermalDensity functional theoryNanotechnologyThermodynamicsChemistryComputational chemistryGeometry

Abstract

fetched live from OpenAlex

The chemical properties of a surface determine the friction and wear behavior of a material during sliding. In this article, we study the mechanisms underlying the sliding behavior of the AgTaO 3 perovskite material, a promising high-temperature solid lubricant that presents excellent friction properties and is chemically inert. In particular, by employing a combination of molecular dynamics simulations and density-functional theory calculations, we show that the low friction of AgTaO 3 at high temperature is explained by silver aggregation on the surface, which is enabled by the low energy barriers associated with silver migration. Two different surface terminations (AgO and TaO 2 ) are studied, and we show that the migration barrier on the AgO surface is smaller, favoring silver aggregation, which affects both friction and wear. Regardless of the termination, the formation of soft silver clusters dominates the sliding behavior when enough energy (mechanical or thermal) is imparted to the surface.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.239

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 head0.007
GPT teacher head0.173
Teacher spread0.166 · 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