4.5 Article

Comparison of physico-chemical and thermo-mechanical properties of sungkai (Peronema canescens Jack.), sengon (Falcataria moluccana (Miq.) Barneby & J.W. Grimes), and teak (Tectona grandis L.f.) wood veneers

Journal

WOOD MATERIAL SCIENCE & ENGINEERING
Volume -, Issue -, Pages -

Publisher

TAYLOR & FRANCIS LTD
DOI: 10.1080/17480272.2023.2255166

Keywords

Chemical properties; sengon; sungkai; teak; thermo-mechanical characteristics; wood colour

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This study evaluated the properties of three main fast-growing wood species in Indonesia and found that wood properties can be predicted based on its color appearance, which is of great importance for the rapid identification and utilization of wood in industrial applications.
Sungkai (Peronema canescens Jack.), sengon (Falcataria moluccana (Miq.) Barneby & J.W. Grimes), and teak (Tectona grandis L.f.) are some of the main fast-growing species in Indonesia. Limited research data on the physicochemical and thermo-mechanical properties of these wood species represents a significant drawback for their enhanced industrial utilization. This study aimed to evaluate the properties of these three kinds of wood according to their colour by applying the CIELab colour measuring system, chemical composition by Fourier-transform Infrared Spectroscopy (FTIR), and Pyrolysis-gas Chromatography-Mass Spectrometry (Py-GC/MS) analyses, and the thermo-mechanical properties by Thermogravimetric Analysis (TGA) and Dynamic Mechanical Analysis (DMA). The higher colour quantification (E*) value indicated brighter wood having higher carbohydrate and lower lignin content according to Py-GC/MS results. Besides, the colour may be attributed to the higher phenolic and extractive content. The order of woods from the highest to the lowest phenolic content was teak > sengon > sungkai. Meanwhile, DMA analysis revealed that sungkai had the highest storage modulus, followed by teak and sengon. The findings of this study suggested that the properties of wood could be predicted based on its colour appearance, which could be used in industrial applications for rapid identification of wood properties.

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