Solder Joint Formation with Sn-Ag-Cu and Sn-Pb Solder Balls and Pastes
Bibliographic record
Abstract
ABSTRACT In the transition period from Lead-bearing solder to Lead-Free solder, four metallurgical combinations will be in use: Lead-Free solder with Lead-Free components, Lead-bearing solder with Lead-bearing components, Lead-Free solder with Lead-bearing components, and Lead-bearing solder with Lead-Free components. It is necessary to characterize the joints resulting from these metallurgical combinations in order to optimize process parameters and insure reliable joints. In this study, BGA locations on electroless Ni/ immersion Au (ENIG)-finished boards were reflowed with Sn-3.8Ag-0.7Cu or Sn-37Pb solder balls using Sn-3.8Ag-0.7Cu or eutectic Sn-Pb solder pastes. Some boards were aged at 150°C for 310 hr, 480 hr, and 2160 hr. The four metallurgically different types of solder joints, both as-reflowed and after aging, were shear tested and examined using transmissive X-ray, optical microscopy, scanning electron microscopy, and dispersive X-ray spectroscopy. Some as-reflowed joints were analyzed with Differential Scanning Calorimetry. Solder joint microstructure and composition, intermetallic formation, surface roughness, and voiding were investigated. The influence of structural parameters on shear strength and fracture modes was shown. The differences and similarities between the four different joint metallurgies are discussed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".