Evaluation of Thermal Stress in a Flip Chip Package by Hybrid Experimental-Analytical Method
Bibliographic record
Abstract
ABSTRACT This article presents an application of a Hybrid Experimental-Analytical Inverse Method (HEAIM) to the evaluation of thermo-mechanical behavior of a flip-chip package. The method is recently developed and is generally applicable to tri-material adhesively bonded beam type plates in design for package reliability. The assembly induced interconnect residual stresses (peeling and shear stresses) are major concerns since they are directly responsible for the manufacturing induced interconnect defects and failure in such packages. In this particular application, measurements of thermal warpage at different temperatures of a Flip Chip (FC) Plastic Ball Grid Array (PBGA) package are obtained through a phase-shifted shadow moir’ experiment. The warpage measurement results between layers were used as inputs to the 2D- plane strain linear-elastic solution proposed earlier by Suhir. Using the inverse method, the effective thermo-mechanical behavior of layers in a tri-layer laminate was analytically assessed. The analytical solution for package warpage is validated by experimentally obtained value of thermal warpage. The solution offers a quantitative evaluation of the shearing and peeling stresses as the tri-material package cools down from the elevated temperature to the room temperature.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".