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Record W4416879901 · doi:10.37665/jsmtqgquw57724

Strain Rate and Cyclic Dependencies of PCBA Pad Crater Susceptibility

2014· article· W4416879901 on OpenAlexaff
John McMahon, Brian Standing, M. Thomson, Jim Wilcox, Matt Kelly

Bibliographic record

VenueJournal of Surface Mount Technology · 2014
Typearticle
Language
FieldEngineering
TopicElectronic Packaging and Soldering Technologies
Canadian institutionsIBM (Canada)
Fundersnot available
KeywordsStrain rateDeformation (meteorology)Strain (injury)Failure mode and effects analysisPrinted circuit boardSolderingRange (aeronautics)Surface-mount technology

Abstract

fetched live from OpenAlex

ABSTRACT Pad cratering has been widely recognized as a dominant mechanical failure mode in printed circuit board assemblies (PCBAs) that are subjected to SnAgCu solder alloy processing temperatures. This susceptibility is especially noted in cost competitive, phenolic-cured epoxy based composites, filled with ceramic particles or microclays. A Spherical Bend Test (SBT) program developed by the authors has identified a relationship between the principal rising strain rate associated with PCBA mechanical deformation and the maximum survivable strain for PBGA components. In this work, those results are compared to a similar new experiment using varied design parameters and multiple board materials with the intent of identifying a material independent descriptive equation. On one typical laminate material the experimentation is expanded beyond a single deformation excursion to failure in an attempt to define a surface of safe working strain over a range of cyclic exposures. The scope of this experiment covers a range of strain excursions bounded by strain rate on one axis and SBT cycle count on the other. The limits of this test parameter range are intended to represent strain rate excursions and cycle counts that might reasonably be expected to occur in normal manufacturing environments. This paper describes the theory and practice of material selection, test vehicle design, assembly, and test methods used to generate data. Selected test results, meaningful relationships and the particulars of the failure modes determined by physical failure analysis are discussed.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.008
GPT teacher head0.219
Teacher spread0.210 · 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 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

Citations0
Published2014
Admission routes1
Has abstractyes

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