Thermal Preconditioning, Microstructure Restoration and Property Improvement in Bi-Containing Solder Alloys
Bibliographic record
Abstract
ABSTRACT It has been well-established that the properties of lead-free solder alloys such as SAC 305 (Sn-3.0Ag-0.5Cu) degrade over time as the result of the coarsening of the intermetallic phases such as Ag 3 Sn and Cu 6 Sn 5 . In earlier studies, it was shown that the inclusion of bismuth (Bi) in Sn, Sn-Ag, Sn-Cu, and SAC-based alloys leads to a stabilization of the as-solidified mechanical properties after aging at temperatures above the alloy's solvus (where all precipitates are allowed to dissolve into and diffuse through the β-Sn matrix, leading to a uniform, homogenous microstructure). Further, the β-Sn grain structure becomes more refined, transitioning from consisting of only a few large grains to having many smaller, randomly-oriented grains. However, most practical operating conditions lie below the solvus temperature. This results in Ostwald ripening of the Bi precipitates, which may render solder joints sufficiently brittle to be a reliability concern. This paper contains details from a recently patented process which allows for the improvement of the properties of the solder joint, either post-reflow, or after some amount of product lifetime. The treatment was analyzed by comparing the creep properties of Violet, an alloy containing 2.25% Ag, 0.5% Cu, and 6.0% Bi, with SAC 305. An above-solvus aging treatment was performed on each alloy, either after solidification, or after below-solvus aging. It was found that the creep resistance of both alloys is reduced after below-solvus aging, but the creep resistance of Violet is significantly improved after above-solvus aging (regardless of prior thermal history). These results show that this aforementioned thermal treatment is a viable method to improve the long-term reliability of solder joints in electronic assemblies.
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 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".