Drop Test Performance Of BGA Assembly Using Sac105ti Solder Spheres
Bibliographic record
Abstract
ABSTRACT Assembled BGA/CSP devices with SnAgCu (SAC) solder joints are vulnerable when dropped due to the fragility of solder joints. Although reducing the Ag content of SAC alloy does help, the crack resistance when dropped is still considerably poorer than the eutectic SnPb system. Therefore a new alloy with improved drop test performance is greatly desired. In this work, SAC105 doped with Ti (SAC105Ti) as a BGA/CSP sphere was studied for its drop test reliability. Four different solder combinations were evaluated: 1) SnPb solder paste with SnPb balls, 2) SnPb solder paste with SAC105Ti balls, 3) SAC305 solder paste with SAC105Ti balls, and 4) SAC305 solder paste with SAC105 balls. The number of completely fractured interconnects was counted for each type of component after a total of 100 drops. The cell with the fewest number of fractured joints was the pure SnPb cell, followed closely by SAC305 solder paste/SAC105Ti ball, then SAC305 solder paste/ SAC105 ball and lastly SnPb solder paste/SAC105Ti ball. This trend is consistent with the trend observed by measuring the electrical resistance. The combination of SAC305 solder paste with SAC105Ti balls was the best solder joint structure tested in terms of the lowest number of partial interconnect fractures and outperformed the other three combinations.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
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.
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".