Abstract

The purpose of this work is to propose a decision-making algorithm to select the optimal composite material for thermally conductive but electrically insulating applications, such as microelectronic packaging heat sinks, diodes, and other electronic devices. In particular, an algorithm based on the criteria importance through inter-criteria correlation (CRITIC) and additive ratio assessment (ARAS) methods are used to evaluate several conflicting attributes. The evaluated samples were acrylonitrile butadiene styrene (ABS) composites filled with 0–30 vol% of boron nitride (BN) particles and prepared through melt compounding. The performance attributes considered through testing were heat conductivity, electrical resistivity, density, hardness, and tensile properties (Young's modulus, tensile strength, and elongation). As expected, the composite containing 30 vol% BN exhibited the highest heat conductivity, electrical resistivity, and Young's modulus. Meanwhile, unfilled ABS had the highest elongation at break, tensile strength, and lowest density. With respect to hardness, the 1 vol% BN-loaded composite proved to be superior. Therefore, the experimental data revealed a considerable compositional dependence with no obvious trend. The optimal composition was identified by adopting the CRITIC-ARAS multi-criteria decision-making algorithm, based on which the 30 vol% BN-containing composite was dominant among all the prepared samples. A validation through other decision-making techniques was performed to support the robustness of the proposed technique. Additionally, a sensitivity analysis was carried out on several weight exchange scenarios to see the stability of the ranking results.

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