4.6 Article

The Preparation of High-Volume Fraction SiC/Al Composites with High Thermal Conductivity by Vacuum Pressure Infiltration

期刊

CRYSTALS
卷 11, 期 5, 页码 -

出版社

MDPI
DOI: 10.3390/cryst11050515

关键词

SiC; Al; volume fraction; infiltration; pore; thermal conductivity

资金

  1. General Research Institute for Nonferrous Metals

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The study prepared high-volume fraction SiC/Al composites by vacuum pressure infiltration, investigated the influence of SiC particle size and NH4HCO3 on preform pores, and studied the relationship between porosity and thermal conductivity. Adjusting SiC volume fraction regularly, NH4HCO3 promoting pore connectivity, and the sensitivity of thermal conductivity to porosity were highlighted. The developed thermal conductivity model showed good agreement with experimental results.
The high-volume fraction SiC/Al composite is the new type of electronic packaging material, which plays an important role in the field of high-power integrated circuits. In this study, SiC/Al composites with high-volume fraction of SiC particles were prepared by vacuum pressure infiltration. The influence of SiC particle size and NH4HCO3 on the pores in the preform was explored, aiming to accurately adjust the volume fraction of SiC to meet the thermal performance requirements in different fields. In addition, the preform was infiltrated with different Al alloys, and the relationship between the porosity and thermal conductivity of SiC/Al was studied. For the SiC preform, the volume fraction of SiC can be adjusted regularly when 12 mu m and 100 mu m SiC particles are mixed in different proportions, and the volume fraction reaches the maximum when the proportion of coarse particles is about 77%. NH4HCO3 is conducive to the connectivity of pores in the preform, and about 40 vol.% of NH4HCO3 can effectively increase the porosity of the preform. Thermal conductivity is sensitive to the porosity of composites, especially in the range of 2.5-4.5%. A simple application of the Hasselman-Johnson model and a new thermal conductivity model, lambda(d), established in this article, offer a good agreement with the experimental results.

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