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Record W4387004877 · doi:10.1016/j.jmrt.2023.09.231

Electron microscopic investigation of precipitation hardening in Al-Si based alloys

2023· article· en· W4387004877 on OpenAlexafffund
E. Isaac Samuel, A. M. Samuel, F. H. Samuel

Bibliographic record

VenueJournal of Materials Research and Technology · 2023
Typearticle
Languageen
FieldEngineering
TopicAluminum Alloy Microstructure Properties
Canadian institutionsUniversité du Québec à Chicoutimi
FundersUniversité du Québec à Chicoutimi
KeywordsMaterials scienceAlloyTransmission electron microscopyPrecipitationPhase (matter)Precipitation hardeningDissolutionElectron microscopeAnalytical Chemistry (journal)MetallurgyCrystallographyChemical engineeringNanotechnologyOpticsChemistry

Abstract

fetched live from OpenAlex

The present work was performed on Al-8.5%Si-1.75%Cu-0.55%Mg-0.2%Ti-0.32%Zr-0.015%Sr alloy (coded as 354 alloy) following T6 (at 160 °C) and T7 (at 240 °C) artificial aging conditions using high resolution transmission electron microscopy (HR-TEM). The main results inferred from the present study are the precipitation of GP zones in samples aged for 20h at 160 °C along with S-Al2CuMg phase particles. Aging at 240 °C was carried out for different times, ranging between 30 min and 200h. The quenched structures revealed a series of precipitations mainly GP zones at low aging times to Θ’-Al2Cu after 200h together with the S-phase. No coherency was observed between the S-phase and the aluminum (Al) matrix. The growth of the S- phase takes place by precipitation of S2 type phase on the advancing S1-type phase. Mismatching was clearly observed at particle/matrix interfaces. High magnification images indicated the dissolution of some of the Θ’’ and Θ’ particles to enrich the nearby particles (coarsening).The start of incoherency is observed when the alloy is aged at 240 °C for 200h.

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 score0.006
Threshold uncertainty score0.240

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 head0.024
GPT teacher head0.291
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

Citations0
Published2023
Admission routes2
Has abstractyes

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