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Record W4403587402 · doi:10.1016/j.msea.2024.147429

Understanding the deformation creep and role of intermetallic compound-microstructure in Sn-Ag-Cu solders

2024· article· en· W4403587402 on OpenAlexaff
Tianhong Gu, Yilun Xu, C.M. Gourlay, Fionn P.E. Dunne, T. Ben Britton

Bibliographic record

VenueMaterials Science and Engineering A · 2024
Typearticle
Languageen
FieldEngineering
TopicElectronic Packaging and Soldering Technologies
Canadian institutionsUniversity of British Columbia
FundersEngineering and Physical Sciences Research CouncilRoyal Academy of EngineeringShell
KeywordsIntermetallicCreepMicrostructureMaterials scienceMetallurgyDeformation (meteorology)Composite materialAlloy

Abstract

fetched live from OpenAlex

Tin-based alloys are commonly used in lead-free solder joints in electronic interconnection applications, where creep can limit joint reliability. In this work, directionally solidified bulk solder alloys of different compositions (pure tin, SAC105 and SAC305) are mechanically tested under a constant load for each composition at room temperature to understand mechanical creep performance and quantify the role of different content of Ag 3 Sn and Cu 6 Sn 5 intermetallic compounds (IMCs) in terms of secondary creep strain rate, microstructural evolution , and total amount of accumulated strain. In this work, microstructures are fabricated using directional solidification to promote a systematic variation in IMC sizes, shapes, and distributions within similar crystal orientations of the primary β-Sn matrix. Analysis of creep data indicates that secondary creep is dominated by obstacle-controlled dislocation motion . This is further confirmed by electron backscatter diffraction (EBSD) analysis, which reveals that the formation of subgrains and internal structure, correlating to the initial microstructure of the sample, i.e. changes in secondary dendrite arm spacing (λ 2 ) and eutectic intermetallic spacing (λ e ). The experimental observations are supported further by crystal plasticity simulations that explicitly model the presence of IMCs within the Sn-based samples and show the dependence of the secondary creep rate upon the IMC content, and therefore be beneficial for the possible future composition design in solders.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.543
Threshold uncertainty score0.290

Codex and Gemma teacher scores by category

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 communication0.0000.000
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 head0.014
GPT teacher head0.202
Teacher spread0.188 · 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 teacher head, 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

Citations8
Published2024
Admission routes1
Has abstractyes

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