Effect of ultrasonic capillary dynamics on the mechanics of thermosonic ball bonding
Bibliographic record
Abstract
Microelectronic wire bonding is an essential step in today's microchip production. It is used to weld (bond) microwires to metallized pads of integrated circuits using ultrasound with hundreds of thousands of vibration cycles. Thermosonic ball bonding is the most popular variant of the wire bonding process and frequently investigated using finite element (FE) models that simplify the ultrasonic dynamics of the process with static or quasistatic boundary conditions. In this study, the ultrasonic dynamics of the bonding tool (capillary), made from Al(2)O(3), is included in a FE model. For more accuracy of the FE model, the main material parameters are measured. The density of the capillary was measured to be rho(cap) = 3552 +/- 100 kg/m(3). The elastic modulus of the capillary, E(cap) = 389 +/- 11 GPa, is found by comparing an auxiliary FE model of the free vibrating capillary with measured values. A capillary "nodding effect" is identified and found to be essential when describing the ultrasonic vibration shape. A main FE model builds on these results and adds bonded ball, pad, chip, and die attach components. There is excellent agreement between the main model and the ultrasonic force measured at the interface on a test chip with stress microsensors. Bonded ball and underpad stress results are reported. When adjusted to the same ultrasonic force, a simplified model without ultrasonic dynamics and with an infinitely stiff capillary tip is substantially off target by -40% for the maximum underpad stress. The compliance of the capillary causes a substantial inclination effect at the bonding interface between wire and pad. This oscillating inclination effect massively influences the stress fields under the pad and is studied in more detail. For more accurate results, it is therefore recommended to include ultrasonic dynamics of the bonding tool in mechanical FE models of wire bonding.
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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 | 0.001 |
| 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 | 0.000 |
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".