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Record W4312538792 · doi:10.11159/ijmmme.2019.001

Investigation of High Energy Single Pulse Effect on Micro Arc Oxidation (MAO) Process on Aluminium

2019· article· en· W4312538792 on OpenAlexvenueno aff
Mustafa Safa Yılmaz, Orhan Şahin

Bibliographic record

VenueInternational Journal of Mining Materials and Metallurgical Engineering · 2019
Typearticle
Languageen
FieldEngineering
TopicMetal and Thin Film Mechanics
Canadian institutionsnot available
FundersUniversidad Nacional de LujánTürkiye Bilimsel ve Teknolojik Araştırma Kurumu
KeywordsMicro arc oxidationAluminiumArc (geometry)Materials scienceMetallurgyProcess (computing)Pulse (music)Oxidation processComputer scienceMechanical engineeringEngineeringElectrical engineeringChemical engineeringVoltageMicrostructure

Abstract

fetched live from OpenAlex

Micro Arc Oxidation (MAO) was applied by using high-energy anodic/cathodic pulses with various pulse durations. Anodic and cathodic pulse couples were kept at a constant voltage of 500 volts. Energy of each pulse increased with increasing duration of pulses. Since the aim of the present study was to investigate effect of pulse durations on MAO processing, other processing parameters such as duty cycle (8%), electrolyte temperature (255 C), electrolyte composition (KOH, Na2SiO3.5H2O), process time (20 minutes), anodic pulse voltage, cathodic pulse voltage and chemical composition of substrate were all kept constant. Five different anodic and cathodic pulse durations were applied. Scanning electron microscope (SEM), indenter, profilometer, eddy current and X-ray diffractometer were employed to investigate the microstructure, hardness, surface roughness, coating thickness and phase distribution of the coatings. Varying of pulse duration occurred significant differences among coating specifications. Coating layers with thickness between 50-90 m and surface roughness between 3.1-5.2 m were obtained. The hardness of coating layers was between 800-2000 Vickers. Coatings consist of two sub-layers, inner dense layer and outer porous layer, which were a mixture of -Al2O3 and -Al2O3.

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 score0.015
Threshold uncertainty score0.560

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 head0.196
Teacher spread0.188 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

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