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Record W4404198015 · doi:10.1002/mawe.202300416

Investigating the influence of ferric oxide grade alumino‐silicate cenosphere particulates and heat treatment on the microstructural evolution and mechanical properties of Al6061/ferric oxide alumino‐silicate cenosphere (x weight %) composite

2024· article· en· W4404198015 on OpenAlexaff
A. Anand, Sanjiv Kumar Tiwari, Ved Prakash, Subodh K. Gautam, A. Khalkho, Ritesh Kumar Singh

Bibliographic record

VenueMaterialwissenschaft und Werkstofftechnik · 2024
Typearticle
Languageen
FieldEngineering
TopicAluminum Alloys Composites Properties
Canadian institutionsSaskatchewan Polytechnic
FundersCentral Mechanical Engineering Research Institute, Council of Scientific and Industrial Research
KeywordsCenosphereSilicateMaterials scienceFerricHematiteOxideComposite numberComposite materialMetallurgyChemical engineeringFly ash

Abstract

fetched live from OpenAlex

Abstract The main aim of this investigation is to fabricate aluminum 6061 composites with three different weight percentages of ferric oxide grade alumino silicate cenosphere (1 wt.%, 3 wt.%, and wt.%) by the stir‐casting process. The fabricated cast composite and T6 heat‐treated composite is used to obtain a fundamental understanding of various weight percentages of the cenosphere and the influence of heat treatment on the microstructural changes, mechanical characteristics, the mechanism of fracture, and the interface between the aluminum‐matrix and ferric oxide grade alumino‐silicate cenosphere particulates. Tensile and compressive tests with a constant strain rate (0.5 mm ⋅ min −1 ) were carried out to study the strength and to find a correlation between the various weight fractions of cenosphere and heat treatment. Investigations of the changes in the microstructure of the aluminum ferric oxide grade alumino silicate cenosphere composite and the fractography of the fracture surface are investigated using optical and scanning electron microscope. X‐ray diffraction was utilized to confirm the results obtained from optical and scanning electron microscope analyses for phase characterization validation. A maximum of 30 % increase in hardness value, 20 % increase in tensile strength value, 33 % increase in maximum compressive strength value, and 2 % increase in elongation values are observed in heat‐treated composite when compared to cast composite.

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 categoriesMeta-epidemiology (narrow)
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 score0.029
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.012
GPT teacher head0.207
Teacher spread0.195 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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