MétaCan
Menu
Back to cohort
Record W3114441867 · doi:10.1149/ma2020-02121262mtgabs

(Invited) Elucidating the Role of Mo during the Passivation of Ni-Cr-Mo Alloys: Real Time Analysis of Elemental Dissolution and Surface Enrichment

2020· article· en· W3114441867 on OpenAlexaff
Xuejie Li, Jeffrey D. Henderson, David W. Shoesmith, James J. Noël, Kévin Ogle

Bibliographic record

VenueECS Meeting Abstracts · 2020
Typearticle
Languageen
FieldEngineering
TopicAdvanced Materials Characterization Techniques
Canadian institutionsWestern University
Fundersnot available
KeywordsPassivationDissolutionX-ray photoelectron spectroscopyMolybdenumAlloyTernary operationMaterials scienceElectrochemistryOxidation stateInorganic chemistryMetallurgyChemistryChemical engineeringElectrodeLayer (electronics)MetalPhysical chemistryNanotechnology

Abstract

fetched live from OpenAlex

Molybdenum is a common alloying element used in Ni-Cr and Fe-Cr alloys to improve their passive properties. Despite its ubiquity, the precise role Mo plays during passivation remains poorly understood. Recently we have investigated the role of Mo in commercial allows during both passive film formation [1] in acidic solution and during transpassive dissolution and repassivation in neutral chloride solution [2] using atomic emission spectroelectrochemistry (AESEC). In this work we refine the conclusions of the previous studies by working with pure binary and ternary alloys, Ni22Cr wt.% and Ni22Cr10Mo wt.%, the simplicity of which permits a clearer picture of the underlying mechanisms. The dissolution rates of Ni, Cr, and Mo and the surface enrichments of Cr and Mo were determined as a function of time during electrochemical experiments and film composition and oxidation state information was obtained by X-ray photoelectron spectroscopy (XPS). For both alloys, following cathodic removal of the passive film (activation), a spontaneous open circuit passivation was observed at ≈-0.25 V vs. SCE which involved the enrichment of both Cr and Mo. Stepping the potential further into the passive domain (+0.3 V vs. SCE) lead to a further enhancement of the Cr enrichment but a partial dissolution of the Mo enrichment. The XPS results suggest that Mo dissolution may be attributed to the oxidation of the less soluble Mo(IV) to more soluble Mo(VI) species as suggested in our previous work with a commercial Ni alloy [1]. The suggestion is that Mo enriches on the surface only during a certain domain of potential and this suggests the hypothesis that Mo facilitates the initial growth of the passive film. “The Passivation of Ni-Cr-Mo Alloys: Time Resolved Enrichment and Dissolution of Cr and Mo during Passive-Active Cycles”, X Li, K Ogle, J. Electrochem. Soc. 166 (2019)C3179-C3185. “Molybdenum surface enrichment and release during transpassive dissolution of Ni-based alloys”, JD Henderson, X Li, DW Shoesmith, JJ Noël, K Ogle, Corrosion Science 147(2019)32-40 Figure 1

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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 communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.005
GPT teacher head0.207
Teacher spread0.201 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueECS Meeting AbstractsSame topicAdvanced Materials Characterization TechniquesFrench-language works237,207