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Record W4416884733 · doi:10.37665/srvoksx70825

Crack Paths and Fracture Loads of BGA Solder Joints under Bending as a Function of Strain Rate and Mode Ratio

2015· article· W4416884733 on OpenAlexaff
Saeed Akbari, J.K. Spelt

Bibliographic record

VenueSoldering and Reliability Conferences · 2015
Typearticle
Language
FieldEngineering
TopicElectronic Packaging and Soldering Technologies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBall grid arraySolderingFracture (geology)Joint (building)BendingFracture mechanicsQuasistatic processPrinted circuit board

Abstract

fetched live from OpenAlex

ABSTRACT Printed circuit boards (PCBs) populated with ball grid array (BGA) solder joints undergo various failure modes depending on the loading conditions. In this study, experiments were performed to characterize the fracture behavior of a package-on-board solder joint system without underfill as a function of the speed of loading. A piece of FR4 was bonded to the free side of the package to build a double cantilever beam (DCB) test specimen from a section of the PCB containing the package. Loading brackets were bonded to both PCB members and a servoelectric testing machine as used to apply an opening speed of either 0.002 mm/s or 4.23 mm/s. This increase in strain rate caused an obvious change in the crack path. Fracture through the PCB was observed in quasi-static loading, whereas predominantly solder joint fracture was detected at the higher strain rate. Depending on the type of PCB and the arrangement of the BGA, the crack front in quasistatic fracture was either continuous, across the entire width of the PCB including the gaps between the solder pads, or it was discontinuous, and only present as discrete sections of pad cratering. Two solder alloy compositions were examined (i.e. SAC305 and SAC0807), with SAC0807 yielding a slightly larger fracture load than SAC305 loaded at the intermediate strain rate. The results are discussed in terms of the fracture strengths of the crack paths and their sensitivity to strain rate.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.288
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.023
GPT teacher head0.256
Teacher spread0.232 · 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.

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

Citations0
Published2015
Admission routes1
Has abstractyes

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