Performance assessment of Sn-based lead-free solder composite joints based on extreme learning machine model tuned by Aquila optimizer

• Main Authors: Dele-Afolabi T.T., Ahmadipour M., Azmah Hanim M.A., Oyekanmi A.A., Ansari M.N.M., Sikiru S., Kumar N.
• Other Authors: 56225674500
• Format: Article
• Published: Elsevier Ltd 2025
• Subjects: Forecasting; Knowledge acquisition; Lead-free solders; Machine learning; Multiwalled carbon nanotubes (MWCN); Optimization; Soldered joints; Soldering; Aquila optimizer; Extreme learning machine; Intermetallic compound layer; Learning machines; Machine modelling; Multi-walled-carbon-nanotubes; Optimizers; Performance assessment; Shears strength; Sn-based solders; Tin alloys

The impact of multi-walled carbon nanotubes (MWCNTs) on the development of the intermetallic compound (IMC) at the interface of the Sn5Sb/Cu solder joint was investigated. Reflow soldering was used to produce the samples, which were subsequently isothermally aged at different temperatures. The prese...