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Record W2028089314 · doi:10.1149/1.2128098

Surface and Corrosion Electrochemical Characterization of Titanium Foams for Implant Applications

2005· article· en· W2028089314 on OpenAlexaff
Richard Menini, Marie‐Josée Dion, Siu Kee Vicky So, Maxime Gauthier, Louis‐Philippe Lefebvre

Bibliographic record

VenueJournal of The Electrochemical Society · 2005
Typearticle
Languageen
FieldMaterials Science
TopicCorrosion Behavior and Inhibition
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsCorrosionTitaniumMaterials scienceDielectric spectroscopyElectrochemistryComposite materialSimulated body fluidCyclic voltammetryPenetration (warfare)Titanium oxideCharacterization (materials science)PorosityLayer (electronics)Chemical engineeringMetallurgyNanotechnologyElectrodeScanning electron microscopeChemistry

Abstract

fetched live from OpenAlex

Electrochemical impedance spectroscopy has been revealed to be a useful tool to evaluate the exposed surface area and consequently to evaluate the corrosion behavior of titanium foams intended for biomedical applications. In order to find the most accurate corrosion assessment, a new equivalent circuit involving a porous model in series with a double layer model was proposed to fit the experimental data. Although seldom used in the literature, such technique could be useful for the characterization of porous media. Determining corrosion potentials and current densities, the titanium foams have revealed to be slightly more resistant to corrosion in simulated body fluid solutions at 37°C under static mode (no stress applied to the samples) compared to dense and polished titanium. The best titanium foams exibited penetration rates around . Cyclic voltammetry experiments have shown that the titanium oxide layer stability was not affected by the fabrication process of the foams.

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 score0.138
Threshold uncertainty score0.263

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 head0.249
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.

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

Citations39
Published2005
Admission routes1
Has abstractyes

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