A hybrid approach to characterization and life assessment of trilayer assemblies of dissimilar materials under thermal cycles
Bibliographic record
Abstract
The current study puts forward non-local closed-form solutions for interfacial peel and shear stress, as well as warpage deformation, of trilayer structures under thermal cycling. Based on the solution, a hybrid experimental-analytical inverse method (HEAIM) has been proposed for characterizing the constitutive behaviour of the trilayer constituents. The method is applied to optimize the correlation between the experimentally measured thermal warpage of a trilayer structure and the analytically solved warpage. Furthermore, a localized analytical and experimental method is suggested for characterizing the stress-strain relation of a joint alloy at the interfacial level in the trilayer structure. The resulted viscoelastoplastic model of the joint alloy is further employed in predicting the life of a trilayer structure that consists of a failure dominant adhesive layer made of the same joint material. A method for the thermal fatigue life prediction is proposed, which applies critical plane-energy fatigue damage parameter in combination with a modified Coffin-Manson life model. The experimental evaluation of the proposed models and approaches for the characterization of thermally induced trilayer structure deformation and stress, as well as the fatigue life prediction is conducted on several custom-made trilayer structures as well as real microelectronics. In the study if trilayer structure reliability and durability, experimental validation of numerical and analytical modeling has been rare. The current study has obtained good agreement between the measured trilayer warpage and the predicted one using the thermomechanical properties of the trilayer constituents determined by HEAIM, owing to its more accurate prediction for the creep behaviour of the joint alloy. The study of thermal fatigue of the trilayer structure follows a new method that involves the critical plane-energy fatigue damage parameter. The resulted fatigue life prediction has been promising.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".