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Record W4319864263 · doi:10.5267/j.ccl.2022.12.008

The effect of compaction pressure, sintering time, and temperature on the characterization of an aluminum/alumina composite with rising alumina proportions

2023· article· en· W4319864263 on OpenAlexvenueno aff
Anup Choudhury, Jajneswar Nanda, Sankar Narayan Das

Bibliographic record

VenueCurrent Chemistry Letters · 2023
Typearticle
Languageen
FieldEngineering
TopicAluminum Alloys Composites Properties
Canadian institutionsnot available
Fundersnot available
KeywordsSinteringIndentation hardnessComposite numberCompactionPorosityScanning electron microscopeMicrostructureCrystalliteAluminiumPowder metallurgyMaterials scienceComposite materialChemistryMetallurgy

Abstract

fetched live from OpenAlex

The purpose of this article is to investigate the effect of various process parameters such as compaction pressure, sintering temperature, and time on the physio-mechanical properties of a powder metallurgy-fabricated composite made of pure aluminium/alumina. Temperatures (580°C, 600°C, and 630°C), periods (1.5, 2, and 2.5 hr), compacting loads (30KN-65KN), and alumina percentages (2, 4, 6, and 8weight percent) are all considered. X-ray diffraction (XRD) and X-ray fluorescence spectroscopy (XRF) studies are carried out to determine the phases present and their proportions. Crystallite size study is performed using XRD data, and the Al+4 weight % alumina composite has the smallest size of any composite tested. For optimization, sintering density, porosity, and microhardness are calculated. Scanning electron microscopy (SEM) is used to analyse the different microstructures. At 600°C, 2 hr of operating time, and 4weight% alumina additions, the highest sintering density and microhardness are found.

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 score0.034
Threshold uncertainty score0.537

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 head0.006
GPT teacher head0.201
Teacher spread0.196 · 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
Published2023
Admission routes1
Has abstractyes

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