Effect of Thermal Treatment on the Microstructure, Properties, and Reliability of Lead-Free Bismuth Containing Solder Alloys
Bibliographic record
Abstract
ABSTRACT A major reliability concern in the SMT industry is the reduction in reliability of lead-free solder alloys such as SAC 305 (Sn-3.0Ag-0.5Cu) as a result of the coarsening of intermetallic phases over time. Recent studies have shown that the addition of bismuth (Bi) to the alloy results in superior performance over SAC and Sn-Pb in accelerated thermal cycling (ATC) and vibration testing. Furthermore, after aging, the mechanical properties of Bi-containing alloys are preserved and do not degrade. However, typical in-service temperatures lie below the alloy's solvus (the temperature above which all Bi will dissolve in β-Sn) and Bi precipitates tend to coarsen, which may reduce reliability. However, above-solvus aging allows all Bi in the alloy to diffuse through the β-Sn matrix to produce a more desirable microstructure consisting of small, uniformly sized and spaced Bi precipitates. In our previous work, the creep properties of Violet (Sn-2.25Ag-0.5Cu-6.0Bi) and SAC 305 were evaluated both before and after the application of an above-solvus thermal treatment. It was shown that the creep resistance of Violet was significantly improved after this treatment while the SAC 305 was unaffected. In this work, the aforementioned treatment (125°C for either 24h or 48h) was performed on a series of PCBs that had been assembled using SAC 305 or Violet. After the thermal treatment, boards underwent ATC at one of two thermal profiles: −55°C to 125°C or −40°C to 70°C, per the IPC 9701 specification. Statistical analysis was conducted to evaluate the efficacy of the thermal treatment on improving solder joint reliability. Physical failure analysis was also performed to investigate the evolution of the microstructure and determine the combined effects of the treatment and ATC on the failure mode.
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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".