MétaCan
Menu
Back to cohort
Record W4416812887 · doi:10.1016/j.wear.2025.206440

Tribocorrosion of additively manufactured and wrought Ti6Al4V in a saline environment

2025· article· en· W4416812887 on OpenAlexafffund
Saman Nikpour, René Daniel Pütz, Sina Matin, A. Igual Muñoz, Stefano Mischler, Yolanda S. Hedberg

Bibliographic record

VenueWear · 2025
Typearticle
Languageen
FieldEngineering
TopicAdditive Manufacturing Materials and Processes
Canadian institutionsWestern University
FundersWestern UniversityNatural Sciences and Engineering Research Council of CanadaMitacsCanada Research Chairs
KeywordsTribocorrosionTitanium alloyGrain boundaryAlloyIndentation hardnessCorrosion

Abstract

fetched live from OpenAlex

Laser powder bed fusion (LPBF) and wrought Ti6Al4V were compared from a tribocorrosion perspective in 0.9% NaCl, distinguishing between mechanical and chemical (oxidative) wear through potential-controlled measurements. The aim was to elucidate the manufacturing- and potential-dependent tribocorrosion mechanisms in a saline environment. While both manufacturing methods resulted in excellent corrosion resistance, the LPBF titanium alloy exhibited a finer, distinct microstructure, higher microhardness, and greater tribocorrosion resistance under applied cathodic and anodic potentials in saline than the wrought alloy. More available slip systems, lower grain boundary density, easier crack formation and propagation at the oxide-subsurface interface, and more oxidized third-body particles were responsible for the higher mechanical and chemical volume loss of wrought samples. These features were related to the microstructural differences; the wrought titanium alloy consisted of a β phase, along with α phase, and a lower grain boundary density, whereas the LPBF alloy possessed α/α′ phases and a higher grain boundary density. • Chemical and mechanical wear distinguished through applied potential control. • Laser powder bed fusion (LPBF) and wrought Ti6Al4V alloys compared. • No β phase in LPBF Ti6Al4V resulted in higher microhardness and fewer cracks. • Higher tribocorrosion resistance of LPBF than wrought Ti6Al4V in saline.

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 score0.041
Threshold uncertainty score0.283

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 head0.002
GPT teacher head0.171
Teacher spread0.169 · 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

Citations2
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueWearSame topicAdditive Manufacturing Materials and ProcessesFrench-language works237,207