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Record W3130816166 · doi:10.1515/corrrev-2020-0062

Effect of interaction between two single-particle-impingements on the repassivation behavior of 304 stainless steel in a simulated groundwater

2021· article· en· W3130816166 on OpenAlexaff
Xingguo Feng, Yang Zhao, Xiangyu Lu, Vahidoddin Fattahpour, Morteza Roostaei, Mahdi Mahmoudi, Hongbo Zeng, Jing‐Li Luo

Bibliographic record

VenueCorrosion Reviews · 2021
Typearticle
Languageen
FieldMaterials Science
TopicHydrogen embrittlement and corrosion behaviors in metals
Canadian institutionsUniversity of Alberta
FundersFundamental Research Funds for the Central Universities
KeywordsMaterials scienceImpact craterPassivationCorrosionMetallurgySubstrate (aquarium)Indentation hardnessParticle (ecology)Composite materialMicrostructureLayer (electronics)

Abstract

fetched live from OpenAlex

Abstract To investigate the effect of interaction between two single-Si 3 N 4 particle-impingements on the repassivation of 304 stainless steel in a simulated groundwater, the corrosion current peaks of the samples during the impingement were recorded, and the micro-hardness of the substrate around the crater was tested. The results indicated that significant interactions between the two impingements were observed only when the value of distance-diameter ratio ( L/d ) was less than 1.5. With L/d being less than 1.5, the corrosion current peaks and mass losses due to the second impingements were higher than those of the first ones, and the re-passivation rates of samples during the second impingements were lower than those of the first impingements. Simultaneously, the microhardness of the substrate between the two craters was higher than that of the surface around one single crater with the same distance-diameter ratio. The mechanisms of how the L/d ratio influenced the interaction between the two impingements are also discussed.

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)0.003
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 score0.044
Threshold uncertainty score0.946

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.064
GPT teacher head0.357
Teacher spread0.294 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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