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Simulating surface tension of Sn-based lead free solder using an artificial neural network

Min Wu (School of Mechanical Engineering, Liaoning Shihua University, Fushun, P.R. China)
Xiangyu Su (School of Mechanical Engineering, Liaoning Shihua University, Fushun, P.R. China)

Soldering & Surface Mount Technology

ISSN: 0954-0911

Article publication date: 5 September 2016

145

Abstract

Purpose

Because of the complexity of relationship between surface tension and its decisive factors, such as temperature, concentration, electronic density, molar atomic volume and electro-negativity, a reasonable predicting model of surface tension of Sn-based solder alloys has not been developed yet. The paper aims to address the surface tension issue that has to be considered if the new lead free solder will be applied for electronics.

Design/methodology/approach

Using an artificial neural network (ANN) model with back-propagation (BP) algorithm, the surface tension for Sn-based binary solder alloys was simulated, and the comparison between the simulating results and data from experiments and literatures was analyzed as well. In addition, the relationship between surface tension and its decisive factors would be discussed based on the ANN and orthogonal design methods.

Findings

It is shown that the predicting model of surface tension of Sn-based solder alloys is constructed according to the BP–ANN theory, and the predicted value from the BP–ANN is in excellent agreement with the experimental results. The surface tension of Sn-based solders is determined by five factors, i.e. temperature, concentration, electronic density, molar atomic volume and electro-negativity. Among of the factors, molar atomic volume is major factor, and the order of degree of influence on surface tension is molar atomic volume > electro-negativity > electronic > density > concentration > temperature. Moreover, a simply reasonable equation is proposed to estimate the surface tension for Sn-based solders.

Originality/value

The five decisive factors of surface tension for Sn-based binary solder alloys have been analyzed theoretically, and a reasonable model of surface tension for Sn-based binary solder alloys is proposed as well. It is shown that ANN theory will be applied well to simulate the surface tension of Sn-based lead free solder.

Keywords

Acknowledgements

The authors thank Zheng Wentao (Teacher at the College of Material Science and Engineering, Shengyang University of Technology, P.R.C) and Qu Zhoude (Professor of the College of Mechanical Engineering, Tianjin University of Technology and Education, P.R. China) for their kind permission to use the BP–ANN software. In addition, a special word of thanks goes to the Team of Advanced Metal-forming Technology, in the Specialized Materials and Devices Division, at the Institute of Metal Research Chinese Academy of Sciences for their kind support of this research. At same time, the authors would like to thank the Education Science Research of Liaoning Province, P.R. China (Grant no. 2008382).

Citation

Wu, M. and Su, X. (2016), "Simulating surface tension of Sn-based lead free solder using an artificial neural network", Soldering & Surface Mount Technology, Vol. 28 No. 4, pp. 201-206. https://doi.org/10.1108/SSMT-01-2016-0002

Publisher

:

Emerald Group Publishing Limited

Copyright © 2016, Emerald Group Publishing Limited

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