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Record W4402171280 · doi:10.3390/ma17174364

Effects of Minor Zn Dopants in Sn-10Bi Solder on Interfacial Reaction and Shear Properties of Solder on Ni/Au Surface Finish

2024· article· en· W4402171280 on OpenAlexaff
Sijin Li, Junxian Zhu, Huiling Zhou, Mingqing Liao, Fengjiang Wang, Jian Chen

Bibliographic record

VenueMaterials · 2024
Typearticle
Languageen
FieldEngineering
TopicElectronic Packaging and Soldering Technologies
Canadian institutionsWestern University
FundersGovernment of Jiangsu ProvinceNational Natural Science Foundation of China
KeywordsMaterials scienceSolderingIntermetallicDopantMetallurgyBrittlenessShear strength (soil)AlloyComposite materialIsothermal processUltimate tensile strengthSurface finishDoping

Abstract

fetched live from OpenAlex

Sn-10Bi low-bismuth-content solder alloy provides a potential alternative to the currently used Sn-Ag-Cu series due to its lower cost, excellent ductility, and strengthening resulting from the Bi solid solution and precipitation. This study primarily investigates the interfacial evolution and shear strength characteristics of Sn-10Bi joints on a Ni/Au surface finish during the as-soldered and subsequent isothermal aging processes. To improve the joint performance, a 0.2 or 0.5 wt.% dopant of Zn was incorporated into Sn-10Bi solder. The findings demonstrated that a 0.2 or 0.5 wt.% Zn dopant altered the composition of the intermetallic compound (IMC) formed at the interface between the solder and Ni/Au surface finish from Ni3Sn4 to Ni3(Sn, Zn)4. The occurrence of this transformation is attributed to the diffusion of Zn atoms into the Ni3Sn4 lattice, resulting in the substitution of a portion of the Sn atoms by Zn atoms, thereby forming the Ni3(Sn, Zn)4 IMC during the soldering process, which was also verified by calculations based on first principles. Furthermore, a 0.2 or 0.5 wt.% Zn dopant in Sn-10Bi significantly inhibited the Ni3(Sn, Zn)4 growth after both the soldering and thermal aging processes. Zn addition can enhance the shear strength of solder joints irrespective of the as-soldered or aging condition. The fracture mode was determined by the aging durations—with the brittle mode occurring for as-soldered joints, the ductile mode occurring for aged joints after 10 days, and again the brittle mode for joints after 40 days of aging.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.510

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 head0.012
GPT teacher head0.213
Teacher spread0.201 · 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

Citations3
Published2024
Admission routes1
Has abstractyes

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