MétaCan
Menu
Back to cohort
Record W4295745420 · doi:10.3390/coatings12091332

Cold-Sprayed Multilayer Thermal Barrier–Catalytic Coatings for Engine Pistons: Coatings Design and Properties

2022· article· en· W4295745420 on OpenAlexaff
Roman Gr. Maev, Jimi Tjong, Eugene Leshchinsky, Mircea Pantea, Volf Leshchynsky

Bibliographic record

VenueCoatings · 2022
Typearticle
Languageen
FieldEngineering
TopicHigh-Temperature Coating Behaviors
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsMaterials scienceThermal barrier coatingComposite materialSinteringIntermetallicCubic zirconiaYttria-stabilized zirconiaMicrostructureGas dynamic cold sprayCeramicCoatingBrittlenessMetallurgy

Abstract

fetched live from OpenAlex

Yttrium-stabilized zirconia thermal barrier coatings (TBCs) of combustion chambers and piston crowns are used most frequently to increase the chamber temperature and the internal combustion engine efficiency. The development of multilayer metal matrix composite coating is of great importance to diminish the ceramic thermal barrier coating’s brittleness and susceptibility to degradation providing the similar thermal insulation. Our group is developing multilayer TBCs based on intermetallic (Fe-Al) compounds combined with alternating zirconia-based layers made by low-pressure cold spraying (LPCS) and sintering. The Fe-Al intermetallic phase was synthesized during reaction sintering of stainless steel and Al particles in the powder layer previously obtained by cold spraying. A double-nozzle low-pressure cold-spraying gun was used to deposit two layers (stainless steel and Al-YSZ) per one track. The effect of the breaking of the brittle ZrO2 particles due to impingement with the substrate results in the formation of a relatively homogeneous structure with ZrO2 particle size of 3–10 μm. Cold-spray deposition of additional Cu-Ni-Graphene catalytic layers on the TBCs is developed to improve performance and emissions of engines. The microstructure, thermal conductivity, thermal shock behavior and microhardness of TBCs were examined and 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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.028
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.022
GPT teacher head0.222
Teacher spread0.200 · 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.

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

Citations3
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueCoatingsSame topicHigh-Temperature Coating BehaviorsFrench-language works237,207