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Record W4401921443 · doi:10.1016/j.jmrt.2024.08.164

Microstructure and properties of Al-4.8Cu-0.45Mn-0.19Cd-0.18Ti-0.17Zr-0.14V aluminum alloy extrusion bar

2024· article· en· W4401921443 on OpenAlexaff
Gaosong Wang, Zexi Long, Zhiyu Gao, Chenghao Liu, Xu Guo, K. Liu

Bibliographic record

VenueJournal of Materials Research and Technology · 2024
Typearticle
Languageen
FieldMaterials Science
TopicMicrostructure and mechanical properties
Canadian institutionsUniversité du Québec à Chicoutimi
FundersFundamental Research Funds for the Central UniversitiesDepartment of Science and Technology of Liaoning ProvinceNational University's Basic Research Foundation of ChinaNortheastern University
KeywordsMaterials scienceMicrostructureAlloyExtrusionBar (unit)MetallurgyAluminium

Abstract

fetched live from OpenAlex

The mechanical properties, texture transformation, and mechanism of Al–Cu–Mn alloy during annealing were studied using three-dimensional orientation distribution function (ODF), electron backscatter diffraction (EBSD), and transmission electron microscopy (TEM). The results showed that the increase in yield strength after annealing at 200 °C is due to the decrease in the proportion of P and M textures and the increase in the proportion of Goss texture. The increase in the change rate of mechanical properties observed during annealing at 250 and 350 °C can be attributed to the higher proportion of M and P textures and the reduced proportion of Goss textures. Among them, the proportion of M texture increased significantly, and the Goss texture decreased significantly after annealing at 350 °C. This is because the structural energy density (Ev) value of the Goss texture is higher than that of the M texture at 250 °C and 350 °C. The Goss texture is in an unstable state of high energy order. The deformed Goss texture is unstable at high temperatures, leading to conversion into M and other textures. The EBSD and TEM analysis revealed that the hardness is mainly related to the change in dislocation density. When the annealing temperature is increased from 250 to 350 °C, the hardness is significantly reduced from 62 HV to 52 HV, and the dislocation density is reduced from 4.0 × 10 14 ρ/m −2 to 2.4 × 10 14 ρ/m −2 .

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)0.002
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 score0.027
Threshold uncertainty score0.657

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.034
GPT teacher head0.300
Teacher spread0.266 · 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

Citations4
Published2024
Admission routes1
Has abstractyes

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