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Record W2315068482 · doi:10.1109/nano.2014.6968140

Model for nano-scale bonding wires under thermal loading

2014· article· en· W2315068482 on OpenAlexaff
Mohamed A. Eltaher, Mahmoud Khater, Eihab Abdel‐Rahman, Mustafa Yavuz

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicNonlocal and gradient elasticity in micro/nano structures
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsBucklingMaterials scienceStiffnessNonlinear systemNano-ThermalWork (physics)Structural engineeringNanoscopic scaleBeam (structure)AmplitudeThermal stabilityComposite materialScale (ratio)MechanicsPhysicsNanotechnologyThermodynamicsEngineeringOptics

Abstract

fetched live from OpenAlex

In a companion paper, we studied the behavior of thick bonding wires under thermal loading and found good wire performance at elevated temperatures. This study extends the previous work to explore analyitcally the static stability of nano-scale bonding wires under thermal loading. Eringen nonlocal model is used to introduce nano-scale effects into Euler-Bernoulli beam theory, which is then employed to describe the wire response. Critical buckling loads and the amplitude of the static post-buckling nonlinear response are obtained. Numerical results show that taking the nano-scale effects into account leads to lower estimates of wire stiffness and buckling loads.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

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 communication0.0000.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.019
GPT teacher head0.247
Teacher spread0.228 · 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 designSimulation or modeling
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

Citations2
Published2014
Admission routes1
Has abstractyes

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