Application of artificial neural networks for the optimisation of wetting contact angle for lead free Bi-Ag soldering alloys

In the recent years, electronic packaging provides significant research and development challenges across multiple disciplines such as performance, materials, reliability, thermals and interconnections. New technologies and techniques frequently adopted can be implemented in soldering alloys of semiconductor sectors in terms of optimisation. Wetting contact angle or wettability of solder alloys is one of the important factors which has got the attention of scholars. Hence in this study, due to the remarkable similarity over classical solder alloys (Pb-Sn), Bi-Ag solder was investigated. Data were collected through the effects of aging time variation and different weight percentages of Ag in solder alloys. The contact angle of the alloys with Cu plate was measured by optical microscopy. Artificial neural networks (ANNs) were applied on the measured datasets to develop a numerical model for further simulation. Results of the experiments and simulations showed that the coefficient of determination (R2) is around 0.97, which signifies that the ANN set up is appropriate for the evaluation.

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