Modelling the Effect of Cu Content on the Microstructure and Vickers Microhardness of Sn-9Zn Binary Eutectic Alloy Using an Artificial Neural Network
The present study aims to clarify the impact of Cu addition and aging conditions on the microstructure development and mechanical properties of Sn-9Zn binary eutectic alloy. The Sn-9Zn alloys with varying Cu content (0, 1, 2, 3, and 4 wt.%) were fabricated by permanent mold casting. X-ray diffractio...
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MDPI AG
2021-04-01
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| Online Access: | https://www.mdpi.com/2073-4352/11/5/481 |
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| author | Heba Y. Zahran Hany Nazmy Soliman Alaa F. Abd El-Rehim Doaa M. Habashy |
| author_facet | Heba Y. Zahran Hany Nazmy Soliman Alaa F. Abd El-Rehim Doaa M. Habashy |
| author_sort | Heba Y. Zahran |
| collection | DOAJ |
| description | The present study aims to clarify the impact of Cu addition and aging conditions on the microstructure development and mechanical properties of Sn-9Zn binary eutectic alloy. The Sn-9Zn alloys with varying Cu content (0, 1, 2, 3, and 4 wt.%) were fabricated by permanent mold casting. X-ray diffraction (XRD) and scanning electron microscopy (SEM) techniques were utilized to investigate the influence of Cu concentration on the microstructure of pre-aged Sn-9Zn-Cu alloys. The main phases are the primary β-Sn phase, eutectic α-Zn/β-Sn phases, and γ-Cu<sub>5</sub>Zn<sub>8</sub>/η-Cu<sub>6</sub>Sn<sub>5</sub>/ε-Cu<sub>3</sub>Sn intermetallic compounds. Vickers microhardness values of Sn-9Zn alloys increased with additions of 1 and 2 wt.% Cu. When the concentration of Cu exceeds 2 wt.%, the values of microhardness declined. Besides, the increase in the aging temperature caused a decrease in the microhardness values for all the investigated alloys. The variations in the microhardness values with Cu content and/or aging temperature were interpreted on the basis of development, growth, and dissolution of formed phases. The alterations of the lattice strain, dislocation density, average crystallite size, and stacking fault probability were evaluated from the XRD profiles of the investigated alloys. Their changes with Cu content and/or aging temperature agree well with the Vickers hardness results. An artificial neural network (ANN) model was employed to simulate and predict the Vickers microhardness of the present alloys. To check the adequacy of the ANN model, the calculated results were compared with experimental data. The results confirm the high ability of the ANN model for simulating and predicting the Vickers microhardness profile for the investigated alloys. Moreover, an equation describing the experimental results was obtained mathematically depending on the ANN model. |
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| last_indexed | 2024-03-10T11:57:43Z |
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| series | Crystals |
| spelling | doaj.art-2dc5b8ac1a1043bd9d13ba754f5372a32023-11-21T17:08:30ZengMDPI AGCrystals2073-43522021-04-0111548110.3390/cryst11050481Modelling the Effect of Cu Content on the Microstructure and Vickers Microhardness of Sn-9Zn Binary Eutectic Alloy Using an Artificial Neural NetworkHeba Y. Zahran0Hany Nazmy Soliman1Alaa F. Abd El-Rehim2Doaa M. Habashy3Physics Department, Faculty of Science, King Khalid University, P.O. Box 9004, Abha 61413, Saudi ArabiaPhysics Department, Faculty of Education, Ain Shams University, P.O. Box 5101, Heliopolis 11771, EgyptPhysics Department, Faculty of Science, King Khalid University, P.O. Box 9004, Abha 61413, Saudi ArabiaPhysics Department, Faculty of Education, Ain Shams University, P.O. Box 5101, Heliopolis 11771, EgyptThe present study aims to clarify the impact of Cu addition and aging conditions on the microstructure development and mechanical properties of Sn-9Zn binary eutectic alloy. The Sn-9Zn alloys with varying Cu content (0, 1, 2, 3, and 4 wt.%) were fabricated by permanent mold casting. X-ray diffraction (XRD) and scanning electron microscopy (SEM) techniques were utilized to investigate the influence of Cu concentration on the microstructure of pre-aged Sn-9Zn-Cu alloys. The main phases are the primary β-Sn phase, eutectic α-Zn/β-Sn phases, and γ-Cu<sub>5</sub>Zn<sub>8</sub>/η-Cu<sub>6</sub>Sn<sub>5</sub>/ε-Cu<sub>3</sub>Sn intermetallic compounds. Vickers microhardness values of Sn-9Zn alloys increased with additions of 1 and 2 wt.% Cu. When the concentration of Cu exceeds 2 wt.%, the values of microhardness declined. Besides, the increase in the aging temperature caused a decrease in the microhardness values for all the investigated alloys. The variations in the microhardness values with Cu content and/or aging temperature were interpreted on the basis of development, growth, and dissolution of formed phases. The alterations of the lattice strain, dislocation density, average crystallite size, and stacking fault probability were evaluated from the XRD profiles of the investigated alloys. Their changes with Cu content and/or aging temperature agree well with the Vickers hardness results. An artificial neural network (ANN) model was employed to simulate and predict the Vickers microhardness of the present alloys. To check the adequacy of the ANN model, the calculated results were compared with experimental data. The results confirm the high ability of the ANN model for simulating and predicting the Vickers microhardness profile for the investigated alloys. Moreover, an equation describing the experimental results was obtained mathematically depending on the ANN model.https://www.mdpi.com/2073-4352/11/5/481Pb-free soldersVickers hardnessANN modelmicrostructurecopper content |
| spellingShingle | Heba Y. Zahran Hany Nazmy Soliman Alaa F. Abd El-Rehim Doaa M. Habashy Modelling the Effect of Cu Content on the Microstructure and Vickers Microhardness of Sn-9Zn Binary Eutectic Alloy Using an Artificial Neural Network Crystals Pb-free solders Vickers hardness ANN model microstructure copper content |
| title | Modelling the Effect of Cu Content on the Microstructure and Vickers Microhardness of Sn-9Zn Binary Eutectic Alloy Using an Artificial Neural Network |
| title_full | Modelling the Effect of Cu Content on the Microstructure and Vickers Microhardness of Sn-9Zn Binary Eutectic Alloy Using an Artificial Neural Network |
| title_fullStr | Modelling the Effect of Cu Content on the Microstructure and Vickers Microhardness of Sn-9Zn Binary Eutectic Alloy Using an Artificial Neural Network |
| title_full_unstemmed | Modelling the Effect of Cu Content on the Microstructure and Vickers Microhardness of Sn-9Zn Binary Eutectic Alloy Using an Artificial Neural Network |
| title_short | Modelling the Effect of Cu Content on the Microstructure and Vickers Microhardness of Sn-9Zn Binary Eutectic Alloy Using an Artificial Neural Network |
| title_sort | modelling the effect of cu content on the microstructure and vickers microhardness of sn 9zn binary eutectic alloy using an artificial neural network |
| topic | Pb-free solders Vickers hardness ANN model microstructure copper content |
| url | https://www.mdpi.com/2073-4352/11/5/481 |
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