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Effect of ZrB<sub>2</sub> Functionalized Nanoparticles Growth on Microstructural and Corrosion Resistance on Mild Steel through Electrodeposition Route

2021· article· en· W3200108828 on OpenAlex
O.S.I. Fayomi, Mojisola O. Nkiko, Khadijah Tolulope Dauda, K. M. Oluwasegun

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueKey engineering materials · 2021
Typearticle
Languageen
FieldEngineering
TopicElectrodeposition and Electroless Coatings
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMaterials scienceCorrosionCrystalliteMetallurgyCoatingMetalAlloyPhase (matter)Composite numberMicrostructureNanoparticleChemical engineeringComposite materialNanotechnology

Abstract

fetched live from OpenAlex

In other to have a better performance of Ni-P-Zn multifunctional applications, crystallite-like Ni-P-Zn-ZrB 2 composite was actively fabricated by electrodeposition principle. The corrosion, structural evolution and surface active phenomena were investigated by various techniques. The influence of ZrB 2 particulate on the morphology and corrosion properties was examined. The outcomes show an inclusive flower-like doped ZrB 2 phase constituent and is uniformly distributed Ni-P-Zn-ZrB 2 improved strengthening effect. The corrosion progression of the developed metal alloy was compared with other coating matrix from 10-25 minutes interval. The integration of ZrB 2 on Ni-P-Zn phase especially for 25 min deposits significantly enhances corrosion resistance due to good grain refinement. Keywords: Ni-based composite, electrodeposition, time difference, coating, corrosion

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.

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 score0.004
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.003
GPT teacher head0.184
Teacher spread0.181 · 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