4.7 Article

Mechanical behaviour of Mater-Bi®/wood flour composites: A statistical approach

Journal

COMPOSITES PART A-APPLIED SCIENCE AND MANUFACTURING
Volume 39, Issue 9, Pages 1537-1546

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.compositesa.2008.05.015

Keywords

Polymer-matrix composites (PMCs); Mechanical properties; Statistical properties/methods; Electron microscopy

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Interest in biocomposites (lignocellulosic filled biopolymers) started in the 90s, due to environmental advantages, related to the full biodegradability of both matrix and filler, economical issues (organic fillers usually come from sawmill or agriculture wastes) and aesthetical issues (wood filled biopolymers could be particularly pleasant if used for indoor furnishing and automotive interior). In this work, a method for a systematic study of the properties of Mater-Bi (R)/wood flour composites is presented. A two-level full factorial model was built. It allows investigating the effects of multiple operative variables on the observed properties, their contributions, their optimal combinations and their possible interactions. Several composites were prepared in a batch mixer, by changing the processing conditions like filler aspect ratio, filler content, mixing speed, mixing temperature and polymer pre-treatment. The model allowed detecting the statistically significant variations of mechanical properties like the elastic modulus, the impact strength and the heat detection temperature upon changing the process variables. All these properties are of interest in the view of the possible final applications of these composites. It was found that the most influencing variable on the elastic modulus is the filler content, even if the pretreatment of the matrix and the mixing speed showed to have some influence too. The impact strength was mainly influenced by the filler aspect ratio and the mixing speed, while only a moderate statistical significance was attributed to the temperature and the pre-treatment. The heat detection temperature proved to be statistically significantly influenced by the filler content and by its size. (C) 2008 Elsevier Ltd. All rights reserved.

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