Nanoboron nitride-filled heat-treated wood polymer nanocomposites: Comparison of different multicriteria decision-making models to predict optimum properties of the nanocomposites

Abstract

The aim of this study is to investigate the effects of nanoboron nitride on the physical, mechanical, morphological and thermal properties of heat-treated wood high-density polyethylene composites. Three different multicriteria decision-making models such as the technique for order preference by similarity to ideal solutions, multi-attribute utility theory and compromise programming were used to predict the nanocomposites having optimum properties. High-density polyethylene as a matrix, heat-treated wood (30%) as a reinforcement filler and nanoboron nitride (0.5%, 1% and 2%) for improving the thermal stability were used; the composites prepared were grounded in a single-screw extruder, and the test samples were prepared with injection molding. According to the results, both testing and multicriteria decision-making models showed that heat-treated wood polymer nanocomposites with 2% nanoboron nitride have the optimum properties. Multicriteria decision-making methods are thought to be useful tools for materials having the optimal properties. It can be said that this study will be a guide for future material selection studies.