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Modeling Thermal Conductivity of Al-Ni, Al-Fe, and Al-Co Spark Plasma Sintered Alloys

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Abstract

Owing to their low density and high thermal conductivity, aluminum and its alloys are being increasing sought and utilized to produce automotive components to dissipate heat and conduct electricity. This study involved preparing spark plasma sintered Al-x wt.% Ni/Fe/Co (x = 0.5, 1.0, 1.5, and 3.0) alloys and developing a microstructural finite element approach to predict their thermal conductivity and validate it with experimental and analytical thermal conductivity calculations. Optical and electron microscopy, porosity and microhardness measurements were used to characterize the spark plasma sintered alloys. The thermal conductivity of Al-Ni/Fe/Co alloys decreased with increasing Ni/Fe/Co content and it ranged from 227 to 155 W/m.K for Al-0.5 to Al-3.0 wt.% Ni/Fe/Co alloys, respectively. The models to predict the thermal conductivity of spark plasma sintered aluminum alloys help explain the microstructural influence on conductivity and enable design of alloys for more demanding thermal/electrical applications.

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Acknowledgments

The authors would like to thank NSERC (NSERC, RGPIN‐2019‐04169) and the University of Guelph for financial support. The authors also thank M. Sharma, M. Bolan, A. Zimmer and A. Prasad for help with experimentation and data collection. The authors also thank Dr. D. Soldatov and Dr. G. Szymanski at the x-ray facility in the Chemistry department at the University of Guelph for assistance with the XRD experiments. Appreciation also to Dr. J. Leitch at the University of Guelph for SEM support.

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  1. School of Engineering, University of Guelph, Guelph, ON, N1G 2W1, Canada

    P. Bhagtani, A. Bardelcik & A. Elsayed

  2. School of Engineering, University of British Columbia-Okanagan, Kelowna, BC, V1V 1V7, Canada

    L. Bichler

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  1. P. Bhagtani
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Bhagtani, P., Bichler, L., Bardelcik, A. et al. Modeling Thermal Conductivity of Al-Ni, Al-Fe, and Al-Co Spark Plasma Sintered Alloys. J. of Materi Eng and Perform 32, 6821–6832 (2023). https://doi.org/10.1007/s11665-022-07612-8

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