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Record W4385619549 · doi:10.5267/j.esm.2023.7.005

Surface morphological characterization of rf-magnetron sputtering developed inconel coated titanium

2023· article· en· W4385619549 on OpenAlexvenueno aff
Kunle Babaremu, Tien‐Chien Jen, Oluseyi Philip Oladijo, Esther T. Akinlabi

Bibliographic record

VenueEngineering Solid Mechanics · 2023
Typearticle
Languageen
FieldEngineering
TopicMetal and Thin Film Mechanics
Canadian institutionsnot available
FundersUniversity of Johannesburg
KeywordsMaterials scienceInconelTitaniumScanning electron microscopeDiffractometerSputter depositionSputteringCrystalliteMetallurgyThin filmComposite materialNanotechnologyAlloy

Abstract

fetched live from OpenAlex

The interconnected usefulness of titanium grade 5 is amplified by the improved mechanical ability and sustainable applications in various industries like the aerospace, medical industry and many more. Despite the profound properties of Ti6Al4V, it is worthy of intellectual study to investigate the possible performance improvement of the material for better operational application. This study adopted the use of RF magnetron sputtering to deposit the target on the substrate material under varying temperatures and deposition power. A total of four samples and control were analyzed for a surface morphological examination and post-sputtering chemical compositional analysis via SEM (scanning electron microscope) and EDX (energy dispersive x-ray analysis). Further investigation on the samples' crystallites was done using XRD (X-ray diffractometer). The SEM images showed low agglomeration and most of the samples were void of pores, cleft and crevices, which implied homogeneous distribution of the target (Inconel thin film) on the titanium substrate. The EDX of the Inconel coated titanium samples revealed elements such as Ti, Si and C, which are beneficial to the properties of the materials. The XRD profiles of the Inconel coated titanium samples disclosed intensities of high peaks, which indicated stability, chemical and microstructural homogeneity of the thin film.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.571
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.019
GPT teacher head0.214
Teacher spread0.196 · 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.

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

Citations1
Published2023
Admission routes1
Has abstractyes

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