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Record W2274526623 · doi:10.4071/isom-2012-ta42

Pb-free PBGA Design Points to Improve Handling Robustness

2012· article· en· W2274526623 on OpenAlexaff
Isabel de Sousa, Brian Roggeman, Oswaldo Chacon, Niki Spencer, Mamoru Ueno

Bibliographic record

VenueIMAPSource Proceedings · 2012
Typearticle
Languageen
FieldEngineering
TopicElectronic Packaging and Soldering Technologies
Canadian institutionsIBM (Canada)
Fundersnot available
KeywordsMaterials scienceBall grid arrayBrittlenessSolderingTemperature cyclingComposite materialShear stressShear (geology)Structural engineeringMetallurgyThermalEngineering

Abstract

fetched live from OpenAlex

Pb-Free BGA solder joints are more brittle and more susceptible to interfacial fails than the leaded versions. These brittle failures typically occur if the modules are subjected to high strain rates through module handling impacts or PCB flexural stress. The high speed ball shear technique is a useful method to submit solder joints to high strain rates in a controlled manner to emulate the levels of strain the BGAs may see in handling. This measurement technique was used to evaluate different laminate design and process variables on organic laminate substrates to create a more robust Pb-Free solder joint. Experiments were conducted to evaluate the effects and interactions of laminate, module assembly process, SAC alloy composition, and thermal treatments. Modulations of shear speed and shear angle made it possible to observe transitions from ductile to brittle solder fractures. The high speed ball shear method was successful to differentiate subtle effects resulting from different design points and process variables. The copper composition in the PbFree solder alloy, thermal history, and geometric factors such as solder volume, solder resist opening and solder resist thickness all had measurable impacts on the shear strength and transition point of ductile to brittle failure. Some BGA configurations have also been tested in reliability, namely in thermal cycling, and were shown to meet application requirements. Optimal design points can therefore be applied to enhance handling robustness without compromising on reliability.

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)0.001
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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.014
GPT teacher head0.213
Teacher spread0.199 · 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

Citations1
Published2012
Admission routes1
Has abstractyes

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