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Record W4361006200 · doi:10.3390/met13040656

Investigation of Mechanical Properties and Wear Resistance of A2/B2 Type Medium-Entropy Alloy Matrix Reinforced with Tungsten Particles by In-Situ Reaction

2023· article· en· W4361006200 on OpenAlexafffund
Mingyu Wu, Guijiang Diao, Zhen Xu, Ruiken Sim, Wengang Chen, D.L. Chen, Dongyang Li

Bibliographic record

VenueMetals · 2023
Typearticle
Languageen
FieldEngineering
TopicHigh Entropy Alloys Studies
Canadian institutionsToronto Metropolitan UniversityUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaAlberta Innovates
KeywordsMaterials scienceMicrostructureAlloyTungstenMetallurgyCorrosionDuctility (Earth science)PrecipitationPassivationSolid solutionComposite materialCreepLayer (electronics)

Abstract

fetched live from OpenAlex

Microstructure, mechanical properties, wear resistance, corrosion and corrosive wear resistance of AlCrFeNiWx (x = 0, 0.1, 0.2, 0.3 and 0.4) medium-entropy alloys (MEAs) prepared by vacuum arc melting process were investigated. Results of the study show that the microstructure of as-cast AlCrFeNiWx alloys is composed of one disordered Fe-Cr rich BCC phase (A2) and one ordered NiAl-rich (B2) phase when x = 0 and 0.1; W particles appear when x ≥ 0.2. Hardness and strength of AlCrFeNi alloy are markedly increased by the W addition. The strengthening mechanisms include solid-solution strengthening, nano-sized precipitation strengthening and second phase strengthening. The excellent ductility of AlCrFeNi is retained with minor W addition (x ≤ 0.2) but it considerably declines as more W is added, resulting from the precipitation of excessive large-sized W particles. W addition improves the pitting resistance and passivation property of AlCrFeNi HEA in 3.5 wt. % NaCl solution. It is shown that AlCrFeNiW0.3 possesses the highest corrosion resistance, as reflected by the highest Ecorr and the lowest Icorr. Tungsten notably enhances the resistance of this HEA to wear and corrosive wear. AlCrFeNiW0.4 with the highest strength and hardness exhibits the lowest wear volume loss under both dry and corrosive wear conditions.

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 score0.006
Threshold uncertainty score0.332

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 head0.024
GPT teacher head0.218
Teacher spread0.194 · 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

Citations9
Published2023
Admission routes2
Has abstractyes

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