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Record W2890601292 · doi:10.1088/2053-1591/aadeb3

Mechanical and chemical stability of super-hydrophobic coatings on SMA490BW substrate prepared by HVOF spraying

2018· article· en· W2890601292 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMaterials Research Express · 2018
Typearticle
Languageen
FieldMaterials Science
TopicSurface Modification and Superhydrophobicity
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsThermal sprayingCoatingMaterials scienceAbrasion (mechanical)AbrasiveDurabilityCorrosionSubstrate (aquarium)Composite materialLayer (electronics)BogieGrindingMetallurgyStructural engineering

Abstract

fetched live from OpenAlex

SMA490BW weathering steel is an important engineering material employed in the bogies of high-speed train. However, the bogies are also subject to ice accumulation, corrosion, sand abrasive, and heterogeneous wear or other hazard. In this paper, the superhydrophobic (SH) surface on SMA490BW steel is fabricated by using High Velocity Oxygen Fuel (HVOF) spraying technology and low surface energy modification. Self-cleaning effect, hydrophobic durability, wear resistance, the weather resistance, PH stability and electrochemical properties were discussed. The results showed that the as prepared coating possesses CA of 154.3 ± 3° and sliding angle of 4.1 ± 0.1°. The CA has no obvious fluctuations after immersing in water for different time and at PH in the range of 1 to 7. The CA is still above 150° after abrasion for 2400 mm. The SH coating possesses higher Ecorr and lower Icorr compared with SMA490BW substrate and HVOF WC-12Co coating. The SH coating has a long-term water repellency towards environmental conditions during weathering. The SH coating possesses excellent mechanical and chemical stability, which is benefit for applying this coating on the high-speed train bogies.

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.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.004
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.083
GPT teacher head0.342
Teacher spread0.259 · 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