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Record W2007486265 · doi:10.1116/1.1559922

Thermal stability of polycrystalline TiN/CrN superlattice coatings

2003· article· en· W2007486265 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

VenueJournal of Vacuum Science & Technology A Vacuum Surfaces and Films · 2003
Typearticle
Languageen
FieldEngineering
TopicMetal and Thin Film Mechanics
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsMaterials scienceSuperlatticeTinCrystalliteAnnealing (glass)Sputter depositionMicrostructureThermal stabilitySputteringBilayerDiffractionMetallurgyComposite materialThin filmOpticsOptoelectronicsNanotechnologyChemistry

Abstract

fetched live from OpenAlex

This article reports the structure and hardness responses of TiN/CrN superlattice coatings to elevated-temperature annealing. Polycrystalline TiN/CrN superlattices with bilayer periods of 5.6–39 nm were deposited on a Ni-base alloy substrate by reactive unbalanced magnetron sputtering. The superlattices were subsequently annealed in vacuum at elevated temperatures for 2–100 h, followed by characterization using small-angle x-ray reflection, high-angle x-ray diffraction, and hardness testing. The superlattices can sustain their hardness up to 650 °C for 4 h or 575 °C for 100 h. A strong correlation exists between the hardness and the x-ray reflection or x-ray diffraction characteristics. A marked reduction in the high-angle satellite/Bragg peak ratio or in the small-angle reflection intensity corresponds to a rapid decrease in the hardness. This phenomenon is related to a physical transition during which the loss of hardness is caused by the structural instability resulting from accelerated interdiffusion between TiN and CrN layers, which leads to reduced compositional modulation amplitude and diffuse layer interfaces.

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)0.002
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 score0.011
Threshold uncertainty score0.667

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.012
GPT teacher head0.214
Teacher spread0.202 · 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