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Record W4413064065 · doi:10.53063/synsint.2025.51264

Effect of different binders on microstructural evolution and strength of sol-gel bonded Al₂O₃-spinel castables

2025· article· W4413064065 on OpenAlexvenueno aff
Sahar Sajjadi Milani, Mahdi Ghassemi Kakroudi

Bibliographic record

VenueSynthesis and Sintering · 2025
Typearticle
Language
FieldMaterials Science
TopicAdvanced ceramic materials synthesis
Canadian institutionsnot available
FundersUniversity of Tabriz
KeywordsMaterials scienceSpinelCompressive strengthEutectic systemMicrostructureAluminateMulliteCementComposite materialClinker (cement)PorosityLadleMechanical strengthPhase (matter)Ground granulated blast-furnace slagMetallurgyPortland cementCeramic

Abstract

fetched live from OpenAlex

Al2O3-spinel castable refractories offer several benefits, including high refractoriness, strong resistance to chemical attack, and excellent mechanical strength. These properties make them a preferred choice for steel ladle lining below the slag line. In this study, the effect of different binders on Al2O3-spinel castable refractory was investigated. Three sol systems, including alumina, spinel, and silica sol, were separately employed as bonding agents in ultra-low cement castable formulations. Key properties, such as phase composition, microstructure, and mechanical performance of castable refractories, including bulk density (BD), apparent porosity (AP), and cold compressive strength (CCS), were evaluated. The properties of the castables with sol-gel bonding were compared with those with hydraulic bonding (calcium aluminate cement). It was observed that the castables containing silica sol resulted in higher cold compressive strength (2103 kg/cm2) and higher bulk density because of the absence of low melting or eutectic phases and synthesis of the mullite phase.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.006
GPT teacher head0.244
Teacher spread0.238 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2025
Admission routes1
Has abstractyes

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