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Record W7114808891 · doi:10.5267/j.esm.2025.10.001

Investigating interfacial fracture in alumina/silver bimaterial: A study of stress intensity factors and material behavior under mechanical, thermal, and thermo-mechanical loads

2025· article· W7114808891 on OpenAlexvenueno aff

Bibliographic record

VenueEngineering Solid Mechanics · 2025
Typearticle
Language
FieldEngineering
TopicNumerical methods in engineering
Canadian institutionsnot available
Fundersnot available
KeywordsFracture (geology)Stress intensity factorResidual stressThermalUltimate tensile strengthIntensity (physics)Thermal expansionStress (linguistics)

Abstract

fetched live from OpenAlex

This study investigates the fracture behavior of bimaterials, specifically focusing on the Alumina/Silver interface under mechanical, thermal, and thermo-mechanical loading conditions. Through the analysis of Stress Intensity Factors (SIFs) across various crack lengths, temperatures, and along multiple regions and fronts of the crack, we provide valuable insights into the distribution and the nature of stresses, shedding light on how different loading conditions influence crack propagation. Our findings show that, under mechanical loading, the tensile mode SIF (KI) exhibits a straightforward relationship with applied stress, increasing with crack length. In contrast, under thermal loading, KI generally decreases on the surface as the temperature rises, while it increases within the interface, highlighting the complex interplay of thermal expansion and the mismatch of material properties. The thermo-mechanical case combines these effects, further amplifying the role of residual stresses from manufacturing processes and thermal stresses, significantly affecting SIFs and crack growth, especially in bimaterial interfaces. These results contribute to a deeper understanding of fracture mechanisms in hybrid materials.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.361
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.002
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 head0.017
GPT teacher head0.280
Teacher spread0.263 · 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; both teacher heads agree on what is shown here.

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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