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Record W4323543661 · doi:10.21203/rs.3.rs-2649334/v1

Corrosion and catalytic properties of electrodeposited nanocrystalline molybdenum

2023· preprint· en· W4323543661 on OpenAlexaff
Siti Nur Hasan, Edouard Asselin

Bibliographic record

VenueResearch Square · 2023
Typepreprint
Languageen
FieldEngineering
TopicElectrodeposition and Electroless Coatings
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPassivationNanocrystalline materialMolybdenumMaterials scienceElectrochemistryCoatingCorrosionMicrostructureChromiumMetallurgyChemical engineeringMetalElectrodeComposite materialNanotechnologyChemistryPhysical chemistry

Abstract

fetched live from OpenAlex

Abstract Molybdenum (Mo) is a less toxic alternative to chromium for protective coatings. Mo possesses similar properties to Cr, although its electrochemical properties, particularly its passive behavior, have been less studied. We compare the passive behavior of electrodeposited Mo coatings to that of bulk metallic Mo in 3.5% sodium chloride (NaCl) solution. The results demonstrate a strong correlation between the microstructure and passive properties of the coating. Electrodeposited Mo has a higher tendency to passivate, a higher passive current density, and a larger passivation window compared to bulk Mo in 3.5% NaCl. The enhanced electrochemical behavior of the Mo coating is attributed to its nanometric structure and increased electrochemically active surface area. This study highlights the potential for the use of electrodeposited Mo as a safer and more environmentally friendly alternative to Cr coatings.

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 score0.003
Threshold uncertainty score0.005

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.048
GPT teacher head0.305
Teacher spread0.257 · 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
Published2023
Admission routes1
Has abstractyes

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