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Record W4311499348 · doi:10.1016/j.ijrmhm.2022.106079

The effect of microstructure evolution on the wear behavior of tantalum processed by Indirect Extrusion Angular Pressing

2022· article· en· W4311499348 on OpenAlexaff
Babak Omranpour Shahreza, Jacques Huot, Maksim Antonov, Lembit Kommel, Fjodor Sergejev, F.J. Pérez, Anita Heczel, Jenő Gubicza

Bibliographic record

VenueInternational Journal of Refractory Metals and Hard Materials · 2022
Typearticle
Languageen
FieldMaterials Science
TopicMicrostructure and mechanical properties
Canadian institutionsUniversité du Québec à Trois-Rivières
FundersEesti TeadusagentuurEesti TeadusfondiEuropean Commission
KeywordsMaterials scienceMicrostructureTantalumExtrusionMetallurgyPressingAdhesive wearTribologySevere plastic deformationComposite materialTantalum carbideAdhesiveLayer (electronics)

Abstract

fetched live from OpenAlex

This article studies the evolution of microstructure and the wear resistance in tantalum processed by a newly developed Severe Plastic Deformation (SPD) technique called Indirect Extrusion Angular Pressing (IEAP). The microstructure and tribological behavior of nanostructured tantalum processed by IEAP were analyzed in this work. The samples were extruded for two, five, and twelve passes of IEAP and then exposed to ball-on-disk wear testing in dry sliding conditions. It was shown that after twelve IEAP passes, an extensive grain refinement down to 500 nm was achieved, hardness increased, and a high dislocation density formed in the material. The wear resistance of the material improved successively after each pass of IEAP, and the wear rate decreased, although the friction coefficient did not change. Evaluation of the morphology of the wear tracks showed that the dominant wear mechanisms were comprised of galling, adhesive wear, pitting and microplowing. Refinement of the microstructure by IEAP led to a reduction in adhesive wear and pitting while a slight increase in oxidation appeared. Comparison of the results of wear testing between tantalum against steel balls and tantalum against alumina balls showed that the presence of alumina generated a larger portion of adhesive wear, making the wear mechanism more complicated while the tantalum-steel pair presented milder wear.

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)0.002
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 score0.004
Threshold uncertainty score0.691

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.009
GPT teacher head0.244
Teacher spread0.235 · 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

Citations6
Published2022
Admission routes1
Has abstractyes

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