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Record W3092478957 · doi:10.1016/j.jma.2020.07.007

Microstructure and corrosion resistance of a duplex structured Mg–7.5Li–3Al–1Zn

2020· article· en· W3092478957 on OpenAlexaff
Anna Dobkowska, Bogusława Adamczyk‐Cieślak, Jiří Kubásek, Dalibor Vojtěch, D. Kuc, E. Hadasik, J. Mizera

Bibliographic record

VenueJournal of Magnesium and Alloys · 2020
Typearticle
Languageen
FieldMaterials Science
TopicMagnesium Alloys: Properties and Applications
Canadian institutionsWestern University
Fundersnot available
KeywordsMaterials scienceMicrostructureAlloyCorrosionExtrusionMetallurgyAnnealing (glass)Cathodic protectionRecrystallization (geology)Dissolution6111 aluminium alloyMagnesium alloyAnodeChemical engineeringElectrode

Abstract

fetched live from OpenAlex

This study describes the corrosion resistance of extruded, and extruded with post-processing annealing, Mg–7.5Li–3Al–1Zn alloys. The results demonstrate that extrusion at 350 °C with an extrusion speed 0.5 s−1 does not lead to the full recrystallization of the alloy, and the material still exhibits a dendritic microstructure. The post-processing annealing triggers the microstructure transformation, and the relative composition of the alloy changes. The ratio of β(Li) to α(Mg) in the extruded alloy was 29–71%; after annealing amount of β(Li) increased, and the ratio of β(Li) to α(Mg) in the annealed alloy was 35–65%. Corrosion testing shows that in 3.5 wt% NaCl the extruded alloys immediately undergo strong dissolution. As a result of the subsequent annealing, an improvement of corrosion resistance is observed. The higher amount of β(Li) in the annealed alloy reduces the area ratio of cathodic to anodic sites of corrosion, and this makes the annealed alloy more resistive under the analyzed 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)0.000
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 score0.148
Threshold uncertainty score0.521

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 head0.011
GPT teacher head0.212
Teacher spread0.201 · 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

Citations57
Published2020
Admission routes1
Has abstractyes

Explore more

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