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Record W4410333234 · doi:10.37934/armne.33.1.2232

Effects of Multiple Microwave Soldering Cycles on Corrosion Behavior and Conductivity of Lead-free Solder Joints

2025· article· en· W4410333234 on OpenAlexaff
Intan Syafiqah Isma Harisham, Iman Nur Sazniza Johari, Ali Ourdjini, Saliza Azlina Osman

Bibliographic record

VenueJournal of Advanced Research in Micro and Nano Engieering · 2025
Typearticle
Languageen
FieldEngineering
TopicElectronic Packaging and Soldering Technologies
Canadian institutionsUniversity of Ottawa
FundersUniversiti Tun Hussein Onn Malaysia
KeywordsSolderingMaterials scienceLead (geology)MetallurgyCorrosionMicrowaveConductivityComposite materialEngineeringChemistryTelecommunications

Abstract

fetched live from OpenAlex

Solder joints are crucial in modern electronics to ensure electrical connectivity and mechanical stability. The specific problem lies in determining how repeated reflow cycles (e.g., microwave soldering) influence intermetallic compounds (IMC) morphology and thickness, how these changes affect the electrical properties of solder joints, and how the solder joints perform under corrosive conditions. Thus, this study investigates the effects of four-cycle microwave soldering on the formation and growth of IMCs and their impact on solder joints' electrical and corrosion properties. Specifically, Sn-35Bi-0.3Ag and Sn-35Bi-1.0Ag solder alloys on ENImAg surface finishes were analysed. Key findings reveal that after four cycles of microwave soldering, IMC thickness increased from 2.85 μm to 7.11 μm for Sn-35Bi-0.3Ag and from 6.97 μm to 11.92 μm for Sn-35Bi-1.0Ag. Corrosion behaviour in a 6M KOH alkaline solution showed a rise in corrosion current for Sn-35Bi-0.3Ag from 0.2623 μA to 1.0993 μA and for Sn-35Bi-1.0Ag from 0.278 μA to 1.6627 μA, with corresponding corrosion rates of 0.6387 mm/yr and 0.9660 mm/yr, respectively. The results highlight a balance between IMC growth, electrical performance, and corrosion resistance, with Sn-35Bi-0.3Ag offering superior electrical performance despite thermal exposure. These findings provide critical insights for optimising soldering processes and enhancing the reliability of electronic assemblies with applications in advanced manufacturing and product lifecycle management.

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)0.001
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 score0.021
Threshold uncertainty score0.548

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.023
GPT teacher head0.307
Teacher spread0.285 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

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