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

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...

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Bibliographic Details
Published in:Wood Material Science and Engineering
Main Author: Bahanawan A.; Nurhamiyah Y.; Solihat N.N.; Fatriasari W.; Antov P.; Lee S.H.
Format: Article
Language:English
Published: Taylor and Francis Ltd. 2024
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85170661618&doi=10.1080%2f17480272.2023.2255166&partnerID=40&md5=732b2efc90fb21b2b6532493169f0a16
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Summary: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. © 2023 Informa UK Limited, trading as Taylor & Francis Group.
ISSN:17480272
DOI:10.1080/17480272.2023.2255166