Effect of Bond Geometry on Shear Strength and HTS Reliability for Au Ball Bond on Al Pad
Bibliographic record
Abstract
The effect of bond geometry on bond strength and reliability is studied for 25-μm gold wire bonds on standard CMOS aluminum pads. An accelerated method for parameter optimization is used to produce ball bonds with optimized shear strength (SS) and bond geometry. Ball bonds have a diameter of 56.5 μm with a bond height of 12, 16, and 20 μm representing the low, medium, and high bonds, respectively. Low height bonds achieve 126.1 MPa strength and endure up to 41.9% ultrasound (US) before deformation begins, whereas high bonds achieve 109.8 MPa strength and withstand a maximum of 39.8% US. Low bonds achieve higher strengths possibly due to the higher level of US that can be used. Bond reliability is assessed in high-temperature storage tests using a shear test (a destructive method) and piezoresistive stress sensors (a nondestructive method). The bonds are aged at 200°C for ~500 h. Quantifying the reliability performance using shear test results found to be difficult due to poor time resolution. However, from features in the stress sensor signals, a characteristic time (tc) is derived during aging. The tcvalue indicates the time it takes for the bonds to severely degrade due to intermetallics and crack formation. The tc values for low, medium, and high bonds were found to be 199.9 ± 8.7, 225.9 ± 9.5, and 231.9 ± 6.8 h, respectively. The result that suggests ball bonds with higher heights are more reliable than the bonds with lower heights for a constant ball bond diameter. This result is corroborated by the SS before and after aging being the same for the high bonds, whereas SS dropped by 3% for the low bonds. The nondestructive method was demonstrated to have an estimated time resolution better than 10 h, which allows for precise comparisons of the reliability of various processes.
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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 | 0.001 |
| 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) | 0.002 | 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".