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Record W2140339262 · doi:10.1109/icept.2008.4607142

Effect of shear rate on lead free solder joint strength

2008· article· en· W2140339262 on OpenAlexaff
Zheming Zhang, Jingshen Wu, Adam R. Zbrzezny, Neil Mclellan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectronic Packaging and Soldering Technologies
Canadian institutionsAdvanced Micro Devices (Canada)
Fundersnot available
KeywordsSolderingMaterials scienceBrittlenessComposite materialJoint (building)Strain rateFailure mode and effects analysisScanning electron microscopeMetallurgyStructural engineering

Abstract

fetched live from OpenAlex

Solder joint strength at high strain rates is a critical reliability requirement for portable electronic devices. Experimental observations showed low shear rate tests of solder joints cannot be used to accurately predict the mode of deformation and failure behaviors under high speed impact condition. Due to strain rate effect, brittle failure of solder joints under dynamic loadings may not take place at low strain rates. Thus, characterization of solder joints under impact becomes critical in package design and manufacturing for high reliability. This is particularly true for lead-free solder in handholds devices. Present study focused on the deformation and failure behavior of single solder ball joints under impact conditions. With a newly designed single-ball impact tester, impact strength of ball joints of two lead-free solders, i.e. Sn-1Ag-0.5Cu (SAC105) and Sn-1.2Ag-0.5Cu-Ni (LF35), were tested at a speed varying from 0.5 to 3m/s. Peak load and fracture energy obtained at different speeds were compared. The failure modes of the joints were studied by scanning electron microscope (SEM) and correlated to the peak load and total fracture energy which were strain rate dependent and changed with solder ball composition due to different strain hardening effects of the two lead-free solders.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.506
Threshold uncertainty score0.426

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.013
GPT teacher head0.210
Teacher spread0.198 · 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.

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

Citations3
Published2008
Admission routes1
Has abstractyes

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