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Record W1982309666 · doi:10.1080/10402004.2010.510620

The Role of Reversible Martensitic Transformation in the Wear Process of TiNi Shape Memory Alloy

2010· article· en· W1982309666 on OpenAlexafffundabout
Zoheir Farhat, Can Zhang

Bibliographic record

VenueTribology Transactions · 2010
Typearticle
Languageen
FieldMaterials Science
TopicShape Memory Alloy Transformations
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceShape-memory alloyPseudoelasticityAlloyMetallurgyDiffusionless transformationMartensiteTribologyWear resistanceMicrostructure

Abstract

fetched live from OpenAlex

It has been established that the superelastic effect of TiNi alloy is related to a reversible martensitic transformation; that is, stress-induced transformation. The high elastic recovery of TiNi alloy has made it a potential candidate for high wear resistance applications. In the present study the tribological behavior of superelastic TiNi alloy was studied and compared to Ni, Ti, and AISI 304 stainless steel using dry sliding wear and friction tests. The effect of normal load and testing temperature on superelasticity has been investigated. It has been found that although AISI 304 stainless steel and superelastic TiNi alloy have similar hardness, TiNi exhibits superior wear resistance. The wear rate of AISI 304 stainless steel is over four times higher than TiNi. The superior wear resistance of TiNi and the effect of load and temperature on wear were discussed and related to the reversible martensitic phase transformation, as well as self-accommodation and stabilization of martensite.

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: none
Teacher disagreement score0.001
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 head0.009
GPT teacher head0.247
Teacher spread0.239 · 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

Citations42
Published2010
Admission routes3
Has abstractyes

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