Numerical Characterization of the Mechanical Performance of SAC105 Tin-Silver-Copper Solder Interconnections After Aging
Bibliographic record
Abstract
The evolution of mechanical properties and failure mechanisms in leadless solder interconnects, specifically 98.5Sn1.0Ag0.5Cu(SAC105), are continually influenced by isothermal aging and thermal loading over time.Accurate prediction of electronic assembly reliability necessitates the integration of these aging effects within the finite element analysis framework for solder thermal fatigue.This paper endeavors to elucidate the effects of pre-isothermal aging on the mechanical behavior of SAC105 interconnects under thermal cycling.Utilizing the finite element method coupled with material constitutive parameters from existing literature, the investigation examines two pivotal constitutive models-Anand and Garofalo.Creep behavior, characterized by Anand and Garofalo constants, is assimilated into the models to evaluate the aged SAC105's mechanical response during thermal cycling.Findings indicate that isothermal aging significantly alters the thermomechanical performance of SAC105 solder, particularly after brief aging periods, with diminishing impact over extended durations.Numerical analysis confirms the predominance of secondary creep in the mechanical response of SAC105, as opposed to isotropic hardening or viscoplasticity.Additionally, this study provides a comprehensive assessment of thermal fatigue in pre-aged solders, employing both strain-based and energy-based fatigue models.The insights reveal a reduced lifespan for aged solders compared to their unaged counterparts, with extended aging correlating with exacerbated thermal fatigue degradation.These outcomes furnish critical understanding for enhancing the reliability predictions of solder interconnects in electronic assemblies, post-isothermal aging.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".