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Consequences of N<sub>2</sub>gas flow variation on properties of zirconium oxide-nitride films

2016· article· en· W2531192552 on OpenAlexaff
Nayan N. Jariwala, Kamlesh V. Chauhan, Parth P. Pandya, Nicky P. Patel, Sushant K. Rawal

Bibliographic record

VenueIOP Conference Series Materials Science and Engineering · 2016
Typearticle
Languageen
FieldEngineering
TopicMetal and Thin Film Mechanics
Canadian institutionsMcMaster University
Fundersnot available
KeywordsZirconium nitrideMaterials scienceContact angleNitrideZirconiumSputteringOxideWettingVolumetric flow rateComposite materialSputter depositionMetallurgyAnalytical Chemistry (journal)Thin filmNanotechnologyChemistryLayer (electronics)Titanium nitride

Abstract

fetched live from OpenAlex

Zirconium oxide-nitride films was prepared by RF reactive magnetron sputtering in presence of helium, oxygen and nitrogen gases. The N2 gas flow rate was varied for each consecutive run of sputtering at values of 66, 72, 78, 84, and 90 sccm respectively. Zirconium oxide-nitride films showed structural variation in evolution of various textures as detected by X-ray diffraction. It showed good transmission values above 50% for all samples. Wettability studies of zirconium oxide-nitride films was done by contact angle goniometer. All samples depict hydrophobic behaviour as all films have contact angle values above 90° and as nitrogen gas flow rate increases, the films roughness as well as contact angle increases. Tribological test is done on zirconium oxide-nitride films coated on aluminium, brass and mild steel pins, which give excellent wear resistance compared to uncoated pins.

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)0.001
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 score0.007
Threshold uncertainty score0.521

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.017
GPT teacher head0.176
Teacher spread0.159 · 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

Citations3
Published2016
Admission routes1
Has abstractyes

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