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Record W1967723137 · doi:10.1063/1.2826284

Multilayered coatings with alternate ZrN and TiAlN superlattices

2007· article· en· W1967723137 on OpenAlexaff
D. J. Li, Meng Cao, Xiangyun Deng, Xueliang Sun, Wei-En Chang, Woon‐Ming Lau

Bibliographic record

VenueApplied Physics Letters · 2007
Typearticle
Languageen
FieldEngineering
TopicMetal and Thin Film Mechanics
Canadian institutionsWestern University
Fundersnot available
KeywordsMaterials scienceAuger electron spectroscopySuperlatticeCrystallinityNanoscopic scaleModulation (music)NanolithographyComposite materialLayer (electronics)Ion beam-assisted depositionAnalytical Chemistry (journal)MetallurgyIonOptoelectronicsNanotechnologyIon beamChemistry

Abstract

fetched live from OpenAlex

Zr N ∕ Ti Al N multilayers with various modulation periods and ratios were grown by ion beam assisted deposition. The nanoscale multilayered modulation was confirmed by Auger electron spectroscopy. All multilayers possess higher hardness than the rule-of-mixture value of monolithic coatings. These properties critically depend on both modulation period and ratio. The multilayer with modulation period of 6.5nm and ratio of 2:3 displays the highest hardness (>30GPa) and critical fracture load (53.3mN). These improvements in properties are likely the result of nanoscale strain optimization as the evolution of layer crystallinity finally reaches the formation of (111) textures in all layers.

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 score0.024
Threshold uncertainty score0.575

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 head0.009
GPT teacher head0.190
Teacher spread0.181 · 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

Citations47
Published2007
Admission routes1
Has abstractyes

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