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Record W2026820422 · doi:10.1115/1.4000281

Finite Element Modeling of Simultaneous Ultrasonic Bumping With Au Balls

2009· article· en· W2026820422 on OpenAlexafffund
Wan Ho Song, Ali Karimi, Yan Huang, M. Mayer, Y. Zhou, Jae Pil Jung

Bibliographic record

VenueJournal of Electronic Packaging · 2009
Typearticle
Languageen
FieldEngineering
TopicElectronic Packaging and Soldering Technologies
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaOntario Centres of Excellence
KeywordsBumpingMicroelectronicsFinite element methodMaterials scienceInterconnectionDisplacement (psychology)Stress (linguistics)ModulusUltrasonic sensorStructural engineeringMechanical engineeringComposite materialEngineeringAcousticsOptoelectronics

Abstract

fetched live from OpenAlex

Bumping of microcircuits and substrates establishes interconnect points required for subsequent bonding of microelectronic components, allowing for power and data distribution. Simultaneous ultrasonic bonding of individual Au balls promises to accelerate bumping processes and is studied using a finite element model. The model covers the static forces at the end of a successful bonding operation and analyzes the interfacial stresses between bumps and substrate. The modeling shows the vertical forces acting on the bumps when a lateral displacement of the bonding tool is applied. When designing a practical bonding application, the control of such vertical forces is recommended. A sensitivity analysis is conducted to study the effect of the main factors on the model responses. This analysis reveals that variations in bump height and bonding tool elastic modulus are the major factors affecting the forces on the bumps.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0040.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.007
GPT teacher head0.215
Teacher spread0.207 · 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
Published2009
Admission routes2
Has abstractyes

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