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Record W1998925907 · doi:10.1021/ac701796u

Analyzing the Influence of Alloying Elements and Impurities on the Localized Reactivity of Titanium Grade-7 by Scanning Electrochemical Microscopy

2008· article· en· W1998925907 on OpenAlexafffund
Renkang Zhu, Ziqiang Qin, James J. Noël, David W. Shoesmith, Zhifeng Ding

Bibliographic record

VenueAnalytical Chemistry · 2008
Typearticle
Languageen
FieldChemistry
TopicElectrochemical Analysis and Applications
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of CanadaU.S. Department of Energy
KeywordsScanning electrochemical microscopyGrain boundaryPassivationScanning electron microscopeChemistryReactivity (psychology)OxideTitaniumImpurityAnalytical Chemistry (journal)ElectrochemistryMetallurgyChemical engineeringMaterials scienceComposite materialMicrostructureLayer (electronics)ElectrodeCrystallographyPhysical chemistry

Abstract

fetched live from OpenAlex

Scanning electron microscopy/energy dispersive X-ray analysis (SEM/EDX) was applied to investigate the grain boundaries on ASTM grade-7 titanium (Ti-7) with a freshly polished surface, and the results showed that the alloying element, Pd, and the impurity, Fe, cosegregated to grain boundaries. Scanning electrochemical microscopy (SECM) was used to study the variations in reactivity on Ti-7 exposed to an aerated neutral solution of 0.1 M NaCl. Locations that possessed an enhanced reactivity compared to the oxide-covered (TiO(2)) surface of the grains on SECM images were proposed to be the boundaries. These areas were further activated by the application of a cathodic bias, and interconnection of the active locations allowed the construction of "grain boundary maps". Variations in surface reactivity were quantitatively analyzed by fitting probe approach curves (PACs) to curves simulated with a model based on finite element analyses using the platform of COMSOL multiphysics software. The difference in reactivity between active grain boundaries and oxide-covered grains was up to a factor of 100 on freshly polished surfaces. This difference decreased to a factor of 10-15 after longer-term exposure of the Ti-7 to the aerated solution, indicating partial passivation of the Pd/Fe-stabilized beta-phase in the grain boundaries. PAC analyses of oxide-covered grains showed that the reactivity increased logarithmically as the bias potential to the Ti-7 was decreased, consistent with reduction of the insulating TiO(2) layer to a more conductive TiOOH layer.

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 score0.005
Threshold uncertainty score0.540

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 studies0.0000.001
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 head0.010
GPT teacher head0.254
Teacher spread0.244 · 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

Citations61
Published2008
Admission routes2
Has abstractyes

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