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Record W4324356703 · doi:10.3390/coatings13030619

Microstructure, Mechanical Properties, Wear and Erosion Performance of a Novel High Entropy Nitride (AlCrTiMoV)N Coating Produced by Cathodic Arc Evaporation

2023· article· en· W4324356703 on OpenAlexafffund
Alex Lothrop, Qi Yang, Xiao Huang

Bibliographic record

VenueCoatings · 2023
Typearticle
Languageen
FieldEngineering
TopicMetal and Thin Film Mechanics
Canadian institutionsNational Research Council CanadaCarleton University
FundersNational Research Council Canada
KeywordsMaterials scienceMicrostructureCoatingScanning electron microscopeThermal stabilityComposite materialNitrideMetallurgyLayer (electronics)Chemical engineering

Abstract

fetched live from OpenAlex

(AlCrTiMoV)N high entropy nitride film was prepared on 17-4PH stainless steel substrate using cathodic arc evaporation (CAE). The composition, microstructure, and thermal stability were investigated using scanning electron microscopy (SEM), transmission electron microscopy (TEM), and X-ray diffraction (XRD). Mechanical properties such as hardness and Young’s modulus and coating performance against wear and erosion were also evaluated. The results show that the (AlCrTiMoV)N coating assumes a single-phased solid solution B1 FCC structure. It has excellent thermal stability and retains its structure with no decomposition observed up to a temperature of 1000 °C. The hardness and elastic modulus are measured as 21.3 GPa and 304 GPa, respectively. The coating contains some metallic droplets. As a potential protective coating, the (AlCrTiMoV)N coating has a lower wear rate but a higher erosion rate when compared to the TiN baseline coating.

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 score0.162
Threshold uncertainty score0.641

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 head0.018
GPT teacher head0.199
Teacher spread0.180 · 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

Citations7
Published2023
Admission routes2
Has abstractyes

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