Directly Visualized Mechanical Strain Distribution in Package Interconnect Using Digital Image Correlation
Bibliographic record
Abstract
For advanced package interconnects, analyzing strain distribution within the complex three-dimensional structure is important in order to design a mechanically reliable system. Electronic packages frequently undergo various types of deformation including tension, compression, bending, and thermal treatments. Failures under these loading modes can be prevented with accurate information of distribution and degree of the mechanical strains. This information, however, is difficult to obtain using conventional methods due to the small-sized packages with complex internal structures. It is also uncertain to rely on predictive results from analytical solutions because it is hard to theoretically calculate the complex strain mechanics, especially for the heterogeneously integrated structures. Therefore, experimental methods have been recently demanded for direct evaluation of mechanical deformation in the package interconnects. In this study, a novel method that visualizes and accurately measures the internal strain distribution in package interconnects is developed. This method is based on digital image correlation (DIC), which utilizes microscopic images of the internal structure. The DIC method is adopted by taking advantage of non-contact and full-field analysis capability. Images from both optical microscopy and scanning electron microscopy are utilized for the non-contact strain evaluation method for the micro-scale deformation analysis. In order to obtain clear image of the internal structure, mechanical polish is conducted to form cross-section. For image pattern tracking, micro/ nano sized particles are deposited onto the cross-section to serve as speckle pattern of the DIC analysis. After the specimen preparation, the digital images are obtained before and after a mechanical loading at a same position. The consecutive images are then compared to execute image tracking analysis to result in the microscopic deformation contour. The results can be fully adopted in prediction of failure site or failure modes by providing essential data such as weak spot or intensity of deformation. Using the quantitative strain information, predicting the failure cycle could be also possible based on mechanics of fatigue fracture. We demonstrate that this method is effectively utilized for various package interconnects including printed circuit boards (PCBs), flexible chip packages, and through-hole stress analysis in a 3-D stacked structure. Bending strain analysis of flexible packages and composite substrates, thermal strain analysis of the PCB interconnects are shown as applications of the thermo-mechanical reliability evaluation method. We believe that this experimental method will enable to fully understand the internal stress-strain behavior of the advanced package interconnects and flexible devices that require high mechanical reliability for commercialization.
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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 | 0.001 |
| 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 | 0.001 |
| 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".