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Record W3090454962 · doi:10.1016/j.jma.2020.02.023

Unloading behaviors of the rare-earth magnesium alloy ZE10 sheet

2020· article· en· W3090454962 on OpenAlexafffund
Weiqin Tang, Jeong Yeon Lee, Huamiao Wang, D. Steglich, Dayong Li, Yinghong Peng, Peidong Wu

Bibliographic record

VenueJournal of Magnesium and Alloys · 2020
Typearticle
Languageen
FieldMaterials Science
TopicMagnesium Alloys: Properties and Applications
Canadian institutionsMcMaster University
FundersProject 211Natural Sciences and Engineering Research Council of CanadaShanghai Jiao Tong UniversityNational Natural Science Foundation of ChinaUniversity of MichiganMinistry of Education of the People's Republic of ChinaUniversity of Sydney
KeywordsMaterials scienceCrystal twinningSlip (aerodynamics)Composite materialUltimate tensile strengthAnisotropyMagnesiumMagnesium alloyPlasticityDeformation mechanismAlloyMetallurgyMicrostructure

Abstract

fetched live from OpenAlex

Due to their low symmetry in crystal structure, low elastic modulus (∼45 GPa) and low yielding stress, magnesium (Mg) alloys exhibit strong inelastic behaviors during unloading. As more and more Mg alloys are developed, their unloading behaviors were less investigated, especially for rare-earth (RE) Mg alloys. In the current work, the unloading behaviors of the RE Mg alloy ZE10 sheet is carefully studied by both mechanical tests and crystal plasticity modeling. In terms of the stress–strain curves, the inelastic strain, the chord modulus, and the active deformation mechanisms, the substantial anisotropy and the loading path dependency of the unloading behaviors of ZE10 sheets are characterized. The inelastic strains are generally larger under compressive Loading–UnLoading (L–UL) than under tensile L–UL, along the transverse direction (TD) than along the rolling direction (RD) under tensile L–UL, and along RD than along TD under compressive L–UL. The basal slip, twinning and de-twinning are found to be responsible for the unloading behaviors of ZE10 sheets.

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 categoriesInsufficient payload (model declined to judge)
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 score0.122
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.017
GPT teacher head0.220
Teacher spread0.203 · 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.

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

Citations21
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Magnesium and AlloysSame topicMagnesium Alloys: Properties and ApplicationsFrench-language works237,207