MétaCan
Menu
Back to cohort
Record W3112925505 · doi:10.1073/pnas.2017086117

Nanoscale morphological evolution of monocrystalline Pt surfaces during cathodic corrosion

2020· article· en· W3112925505 on OpenAlexfundno aff
Nakkiran Arulmozhi, Thomas J. P. Hersbach, Marc T. M. Koper

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2020
Typearticle
Languageen
FieldChemistry
TopicElectrochemical Analysis and Applications
Canadian institutionsnot available
FundersQueen's University
KeywordsCorrosionMaterials scienceCathodic protectionPlatinumMetallurgyFacet (psychology)Monocrystalline siliconElectrochemistryCrystallographyElectrodeChemistrySilicon

Abstract

fetched live from OpenAlex

This paper studies the cathodic corrosion of a spherical single crystal of platinum in an aqueous alkaline electrolyte, to map out the detailed facet dependence of the corrosion structures forming during this still largely unexplored electrochemical phenomenon. We find that anisotropic corrosion of the platinum electrode takes place in different stages. Initially, corrosion etch pits are formed, which reflect the local symmetry of the surface: square pits on (100) facets, triangular pits on (111) facets, and rectangular pits on (110) facets. We hypothesize that these etch pits are formed through a ternary metal hydride corrosion intermediate. In contrast to anodic corrosion, the (111) facet corrodes the fastest, and the (110) facet corrodes the slowest. For cathodic corrosion on the (100) facet and on higher-index surfaces close to the (100) plane, the etch pit destabilizes in a second growth stage, by etching faster in the (111) direction, leading to arms in the etch pit, yielding a concave octagon-shaped pit. In a third growth stage, these arms develop side arms, leading to a structure that strongly resembles a self-similar diffusion-limited growth pattern, with strongly preferred growth directions.

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 score0.006
Threshold uncertainty score0.189

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.031
GPT teacher head0.273
Teacher spread0.241 · 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

Citations35
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the National Academy of SciencesSame topicElectrochemical Analysis and ApplicationsFrench-language works237,207