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Record W4413292293 · doi:10.1016/j.matdes.2025.114510

Advances in microstructural evolution and reliability-driven mechanical and corrosion properties of lead-free SAC solder alloys

2025· article· en· W4413292293 on OpenAlexaff
Amirsalar Anousheh, Maryam Soleimani

Bibliographic record

VenueMaterials & Design · 2025
Typearticle
Languageen
FieldEngineering
TopicElectronic Packaging and Soldering Technologies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMaterials scienceSolderingMetallurgyCorrosionLead (geology)Reliability (semiconductor)Thermodynamics

Abstract

fetched live from OpenAlex

Lead-free solder alloys are essential for environmentally compliant electronic packaging, replacing traditional lead-based solders. Among them, tin–silver–copper (SAC) alloys have become the most widely adopted due to their excellent wetting behavior and relatively low melting temperatures compared with conventional solders. The long-term reliability of these alloys is strongly linked to solder joint performance under mechanical and environmental stress. This review critically examines the microstructural evolution, mechanical behavior, and corrosion performance of SAC alloys. The tensile section discusses the effects of initial microstructure, thermal aging, low-temperature exposure, and strain rate–temperature sensitivity, emphasizing the predictive capabilities and cryogenic limitations of the Anand viscoplastic model. Creep behavior is addressed using appropriate constitutive models, such as the hyperbolic sine formulation, with particular attention to intermetallic morphology and dislocation interactions in time-dependent deformation. Fatigue studies, including thermal fatigue, focus on microstructural changes such as recrystallization, void nucleation, and strain localization driven by intermetallic compounds. Corrosion performance is explored with emphasis on galvanic interactions between Ag 3 Sn and Cu 6 Sn 5 phases, microstructural coarsening, and interfacial degradation during environmental and thermal exposure. Integrating these findings, this review identifies key knowledge gaps and outlines future research strategies to improve the reliability and robustness of lead-free solder systems.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.009
GPT teacher head0.207
Teacher spread0.198 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations14
Published2025
Admission routes1
Has abstractyes

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