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Record W3209419209 · doi:10.32920/ryerson.14645550.v1

Correlation of Printed Circuit Board Properties to Pad-Crater Defects Under Monotonic Spherical Bend

2021· preprint· en· W3209419209 on OpenAlexaff
Brian Gray

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicElectronic Packaging and Soldering Technologies
Canadian institutionsToronto Metropolitan UniversityWestern University
Fundersnot available
KeywordsPrinted circuit boardMaterials scienceComposite materialOrthotropic materialBall grid arrayImpact craterSolderingStiffnessStructural engineeringFinite element methodElectrical engineeringEngineering

Abstract

fetched live from OpenAlex

The restriction of lead in solder has caused a change in base materials used to make electronics—the result of which has been a new failure mode known as pad-crater. The susceptibility of six commercially available printed circuit board (PCB) laminates to pad-crater by spherical bend test was determined. The correlation of PCB laminate tensile properties, Vicker’s hardness (VH) of the resin, and weave dimensions showed an inverse relation between susceptibility to pad-crater and VH. Spherical bend testing of pure G10 laminate showed the orthotropic nature of laminates must be accounted for when modeling spherical bend. Comparison of bare PCB spherical bend test results showed the warp and weft direction have different strain responses for some materials. Comparison of strain energy of printed circuit board assemblies and bare PCB subjected to spherical bend showed the additional stiffness added by the ball grid array is almost identical for PCB laminates with different tensile properties.

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)0.002
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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)0.0020.001

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 head0.025
GPT teacher head0.219
Teacher spread0.194 · 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
Published2021
Admission routes1
Has abstractyes

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