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Record W4319864243 · doi:10.5267/j.ccl.2022.10.003

An experimental investigation on metallurgical and corrosion behavior of atmospheric plasma sprayed Stellite 6 powder on AISI 304 stainless steel

2023· article· en· W4319864243 on OpenAlexvenueno aff
Sangita Sarangi, Ajit Mishra, Seshadev Sahoo

Bibliographic record

VenueCurrent Chemistry Letters · 2023
Typearticle
Languageen
FieldEngineering
TopicHigh-Temperature Coating Behaviors
Canadian institutionsnot available
FundersInstitute of Minerals and Materials Technology
KeywordsStelliteCoatingScanning electron microscopeCorrosionMicrostructureMetallurgyIndentation hardnessMaterials scienceEnergy-dispersive X-ray spectroscopyLayer (electronics)Deposition (geology)Composite material

Abstract

fetched live from OpenAlex

An experimental investigation was undertaken to study the Cobalt-based Stellite 6, powder deposited on SS 304 stainless steel substrate without any intermittent layer using an atmospheric plasma spray deposition process by varying the thickness of coating in the range of 74 µm, 128 µm, and 215 µm. The effect of coating thickness on metallurgical properties and corrosion resistance behavior was investigated. Optical microscopy, Scanning Electron Microscopy (SEM), and Energy Dispersive X-ray Spectroscopy (EDS) were employed to study the morphology of Stellite 6 coating. X-Ray Diffraction was used for structural analysis and to identify the phase formation. It was observed that the sample with 128 µm coating thickness provides the best result concerning microhardness and microstructure characteristics whereas the sample with 215 µm coating thickness provides the best corrosion resistance property. The reasons for the deviation were investigated and the factors responsible for the deviation were assigned in this investigation.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
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
Bibliometrics0.0000.000
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 head0.022
GPT teacher head0.262
Teacher spread0.240 · 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

Citations3
Published2023
Admission routes1
Has abstractyes

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