MétaCan
Menu
Back to cohort
Record W4413515382 · doi:10.1016/j.msea.2025.149010

Strain rate-induced crystallographic texture development in tensile deformation of a rapidly solidified thin-strip cast AA5182 Al-Mg alloy

2025· article· en· W4413515382 on OpenAlexafffund
Hesam Pouraliakbar, Mohammad Reza Jandaghi, Mark Gallerneault, Andrew Howells, Johan Moverare, Vahid Fallah

Bibliographic record

VenueMaterials Science and Engineering A · 2025
Typearticle
Languageen
FieldEngineering
TopicAluminum Alloy Microstructure Properties
Canadian institutionsQueen's University
FundersMitacs
KeywordsMaterials scienceMetallurgyAlloyTexture (cosmology)Deformation (meteorology)Strain rateUltimate tensile strengthStrain (injury)Composite material

Abstract

fetched live from OpenAlex

This study investigates the evolution of ultimate crystallographic texture in AA5182 Al-Mg alloy under uniaxial tensile deformation at quasi-static strain rates (10 −3 and 10 −1 s −1 ), focusing on two casting routes of thin-strip (TS) and direct-chill (DC) casting. The TS sample, solidified at ∼10 3 K/s, exhibited an initial average grain size of 49.7 μm, significantly finer than the 114.5 μm observed in the DC counterpart solidified at a cooling rate of ∼10 1 –10 2 K/s. The fraction of intermetallic particles in the TS sample (∼2.74 %) was markedly lower than in the DC sample (∼6.07 %), contributing to enhanced solute supersaturation and reduced strain localization, which is linked to a lower frequency of low-angle misorientations within the matrix. Texture analysis revealed that TS samples experienced an approximately 28 % increase in texture index (from 1.32 to 1.69) with increasing strain rate, compared to a 15 % rise in DC samples (from 1.75 to 2.01), indicating more pronounced strain-induced texture development in the TS sample. Taylor factor (M) analysis showed a greater fraction of favorably oriented grains (M ≤ 2.5) in as-cast TS samples, increasing from 11.5 % to 14.0 % after deformation, compared to an increase from 7.5 % to 14.6 % in the DC samples. However, the DC sample exhibited greater strain localization and a higher kernel average misorientation (KAM, 0.83 vs. 0.67), consistent with its higher density of intergranular/interdendritic intermetallic particles and coarser structure. It was demonstrated that in the TS sample, strain accommodation primarily occurred through grain rotation and dislocation annihilation, facilitated by lower particle density and higher solute supersaturation. By contrast, the DC sample accommodated strain mainly through dislocation pile-ups and boundary-mediated mechanisms, resulting in more constrained deformation behavior. The unique microstructure in the TS sample enabled a broader range of grain rotation trajectories, resulting in a higher number of distinct texture evolution pathways. These findings underscore the critical role of casting routes in governing texture development and highlight the superior potential of the TS sample for enhanced ductility and formability under dynamic loading 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)0.001
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 score0.040
Threshold uncertainty score0.753

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.008
GPT teacher head0.197
Teacher spread0.189 · 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

Citations14
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueMaterials Science and Engineering ASame topicAluminum Alloy Microstructure PropertiesFrench-language works237,207