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High-Performance Ceramic Coatings Sprayed via Novel Supersonic Plasma Spraying System

2007· article· en· W2060474516 on OpenAlexaboutno aff
Sheng Zhu, Bin Xu

Bibliographic record

VenueKey engineering materials · 2007
Typearticle
Languageen
FieldEngineering
TopicHigh-Temperature Coating Behaviors
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsSupersonic speedMaterials scienceCeramicPlasmaGas dynamic cold sprayMicrostructurePlasma torchNozzleCoatingComposite materialMetallurgyParticle (ecology)Thermal sprayingAerospace engineering

Abstract

fetched live from OpenAlex

A novel supersonic plasma spraying system was developed with a maximum power of 80 kW and a maximum working gas flow of 6 m3/h, at which gas and particle velocities of 2400 and 600 m/s can be achieved respectively. This paper deals with novel supersonic plasma spraying system design, the structure of novel supersonic plasma gun includes a special Laval nozzle as the single anode and inner powder supply, and the mechanisms of supersonic plasma jet as well as the effects on the sprayed particles. The spraying process parameters of several ceramic powders such as Al2O3, Cr2O3, ZrO2, Cr3C2 and Co-WC were optimized. The properties and microstructure of the sprayed ceramic coatings were investigated. Nano Al2O3-TiO2 ceramic coating sprayed by using novel supersonic plasma spraying was also studied. Novel supersonic plasma spraying improves greatly ceramic coatings quality compared with conventional air plasma spraying (Metco 9M), as well as it has lower energy and gas exhaustion compared with high power supersonic plasma spraying (Plazjet), which can spray high-performance ceramic coatings at low cost.

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 score0.002
Threshold uncertainty score0.003

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 head0.006
GPT teacher head0.185
Teacher spread0.179 · 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

Citations12
Published2007
Admission routes1
Has abstractyes

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