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Record W2898911377 · doi:10.3390/ma11112182

Comparison of Microstructure and Properties of In-Situ TiN- and WC-Reinforced NiCrBSi Composite Coatings Prepared by Plasma Spraying

2018· article· en· W2898911377 on OpenAlexaff
Linlin Zhu, Jing Wang, Xianqiang Deng, Yanchun Dong, Yong Yang, Dongyang Li

Bibliographic record

VenueMaterials · 2018
Typearticle
Languageen
FieldEngineering
TopicMetal and Thin Film Mechanics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMaterials scienceMicrostructureCoatingComposite numberScanning electron microscopeIndentation hardnessTinComposite materialTransmission electron microscopyMetallurgyNanotechnology

Abstract

fetched live from OpenAlex

In this study, NiCrBSi-30 wt.% TiN composite (NTC) coating was produced on carbon steel via plasma spraying, with NiCrBSi-30 wt.% WC composite (NWC) coating as the comparison object. The microstructure and phase constituents of the composite coatings were characterized using scanning electron microscopy (SEM) coupled with energy dispersive spectroscopy (EDS) techniques, transmission electron microscopy (TEM) and x-ray diffraction (XRD). Atomic force microscopy (AFM) was used to measure electronic work functions. The microhardness and wear performance of coatings were also investigated. The average microhardness of the NTC and NWC coatings was 1000 HV and 850 HV, respectively. In addition, the NTC coating had a wear volume loss of 0.8118 mm³, less than 1.4772 mm³, the volume loss of the NWC coating. This was due to the presence of TiN in the form of nanograins in the composite coating and tighter binding to the matrix.

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 score0.002
Threshold uncertainty score0.394

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.015
GPT teacher head0.224
Teacher spread0.209 · 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

Citations13
Published2018
Admission routes1
Has abstractyes

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