The Effect of Bismuth, Antimony, or Indium on the Thermal Fatigue of High Reliability Pb-Free Solder Alloys
Bibliographic record
Abstract
ABSTRACT Although SnAgCu (SAC) Pb-free solder alloys typically have better fatigue life than traditional eutectic SnPb solder, their fatigue reliability is limited at higher operating temperatures. In response to the need for higher temperature performance, numerous new commercial Pb-free solder alloys are being developed and introduced. These alloys are based on the SAC system but have significant solute additions to promote solid solution strengthening at higher operating temperatures. This paper presents some of the initial thermal cycling results from a major industrial consortia project established to evaluate the thermal fatigue reliability of multiple SAC-based solder alloys containing various combinations of solid solution strengthening agents. Daisy chained ball grid array (BGA) test vehicles were fabricated with SAC305 as a performance baseline and three different developmental alloys each employing significant additions of different solution and dispersion strengthening elements, either Bi, Sb, or In. The BGA components were soldered to daisy chained test boards using matching alloy solder paste, and subsequently thermally cycled in accordance with the IPC-9701 attachment reliability guideline. Data are reported for three distinct thermal cycling profiles, 0/100°C, -40/125°C, and -55/125°C, as characteristic life (the number of cycles to achieve 63.2% failure) and slope from a two-parameter Weibull analysis. A baseline characterization was performed on representative board level assemblies from each of the experimental legs to document the basic microstructures before temperature cycling for comparison to samples removed from the temperature cycling chambers for failure analysis. Microstructural characterization and failure analysis was done using optical metallography (destructive cross-sectional analysis) and scanning electron microscopy (SEM).
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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".