Reliability testing of wire bonds using pad resistance with van der Pauw method
Bibliographic record
Abstract
In microelectronic wire bonding, a reliable electrical connection is of utmost importance. With the advent of advanced bonding wire materials such as Cu, Pd coated Cu, and Ag alloys, there are substantial ongoing efforts in process development and reliability characterization with these materials. To measure bond quality and especially bond reliability is limited with respect to sample size and number of different conditions that can be covered with available resources. Methods that apply non-destructive bond quality measurements during thermal aging could be useful to increase characterization throughput while keeping the need for resources under control. A non-destructive pad resistance method based on the well known van der Pauw method is introduced that indicates bond aging more conveniently than previously reported bond resistance methods. With four connection lines designed at each corner of a standard square bonding pad, the pad resistance was monitored at various stages during reliability testing by high temperature storage at 250 °C of a Au ball bond ≈50 μm in diameter and ≈15 μm high on a standard Al pad. The pad resistance increased during aging up to 30.8 h due to intermetallics (IMCs) formation, then dropped ≈5 % during 14 h down to 50.1 mΩ, and then rose again to reach a plateau above 55 mΩ after 76 h that remain unchanged for the remainder of the aging which lasted 150 h. To explain the unexpected resistance drop a number of finite element (FE) models was developed to simulate various IMC distributions in the bond zone and their effect on the pad resistance. It was found that the resistance drop can be explained by the occurrence of Al-rich IMCs at the periphery of the bond in later stages of bond aging. Compared to the earlier Au-rich IMCs, Al-rich IMCs have lower resistivity. Therefore, the time of the pad resistance drop can indicate the beginning of a late stage of bond deterioration of the Au/Al system and effectively serve as a non-destructive reliability indicator.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".