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Record W4412901651 · doi:10.3390/met15080846

Passive Layer Evolution of Anodized B206 Aluminum in Seawater for Tidal Energy Applications: An Electrochemical Approach

2025· article· en· W4412901651 on OpenAlex
Ibrahim M. Gadala, Shabnam Pournazari, Davood Nakhaie, Akram Alfantazi, Daan M. Maijer, Edouard Asselin

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMetals · 2025
Typearticle
Languageen
FieldMaterials Science
TopicAnodic Oxide Films and Nanostructures
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAnodizingSeawaterAluminiumLayer (electronics)ElectrochemistryTidal powerMaterials scienceEnergy (signal processing)Environmental scienceOceanographyMetallurgyNanotechnologyMarine engineeringChemistryPhysicsGeologyEngineeringElectrode

Abstract

fetched live from OpenAlex

Aluminum–copper casting alloys are potential candidate materials for use in marine applications where high mechanical strength and superior fatigue resistance are desired. The corrosion and protection of aluminum alloy B206 in seawater through surface passivation continues to pose challenges, hampering its widespread use in marine structures. In this study, the electrochemical behavior of B206 is investigated in artificial seawater at temperatures and dissolved oxygen (DO) concentrations anticipated during service in marine environments. In particular, the influence of anodizing B206 in deaerated seawater on the subsequent corrosion behavior of the alloy is studied using potentiodynamic and potentiostatic polarization, electrochemical impedance spectroscopy (EIS), and Mott–Schottky analysis. The results showed that the effect of DO on the corrosion of B206 is more significant than the effect of temperature. In the absence of DO, results of potentiostatic polarization, EIS, and Mott–Schottky analysis at anodic potentials all indicated the development of a thicker, more protective passive layer in colder seawater. Moreover, passive layer thickness modeled using Power-Law was found to range between 3 and 9 nm, whilst decreasing in thickness with temperature. Donor densities of the n-type passive layer are on the order of 1021 cm−3 and increase with temperature. The findings presented in this study support the feasibility of implementing anodizing for B206 in marine service environments.

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 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 score0.271
Threshold uncertainty score0.359

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 head0.256
Teacher spread0.247 · 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