|
|
|
|
|
|
Rapid Determination of Physical and Chemical Properties of Two Kinds of Solid Floor Woods with XRD and FTIR Approaches |
SU Ming-lei1, 2, LIU Cang-wei1, WANG Yu-rong1, 2*, SUN Hai-yan1, 2, REN Hai-qing1, Lü Bin1 |
1. Research Institute of Wood Industry,Chinese Academy of Forestry,Beijing 100091,China
2. Research Institute of Forestry New Technology,Chinese Academy of Forestry, Beijing 100091,China |
|
|
Abstract As a kind of natural and environmental paving materials, the solid wood flooring has become popular among people whose demand is increasing day by day. However, how to understand and detect wood properties quickly has been a urgent problem to be solved for material selection and quality inspection. So the profile densities of two kinds of import solid wood floorings made of Dipteryx odorata,Pometia spp. were quickly detected for physical properties and major chemical compositions by using rapid detection technology, X-ray scanning method and fourier transfoum infrared spectrum(FTIR). At the same time,the basic density of wood was measured by direct measurement and we also analyzed the correlation between the rapid detection density and the basic density of the two kinds floors. The profile density results showed that the density of Dipteryx odorata was higher than that of Pometia spp. and the heterogeneity of two kinds solid wood were great,correlation analysis data showed that there was a high correlation between the average of profile density and the basic density,the correlation coefficients of fitted parameters were 0.983 and 0.981,respectively. Besides the correlation coefficients of all materials was 0.991. The FTIR results showed that the extracts of Dipteryx odorata was higher than that of Pometia spp.,the lignin characteristic peaks intensity ratio of I1 507/I1 425,I1 507/I1 740 of Dipteryx odorata was higher thanthat of Pometia spp.,while the cellulose characteristic peaks intensity ratio of I1 507/I1 425,I1 507/I1 740 was less than that of Pometia spp.. The results showed that the lignin content of Dipteryx odorata was higher than that of Pometia spp.,while the cellulose content was less than that of Pometia spp. Thus,the X-ray scanning method can quickly detect the heterogeneity of the wood and also can predict the basic density. While the FTIR can quickly detect the relative content of wood chemical components,so the combination of the two methods can detect the physical and chemical properties of solid floor woods and other lumbers rapidly.
|
Received: 2017-03-16
Accepted: 2017-08-09
|
|
Corresponding Authors:
WANG Yu-rong
E-mail: yurwang@caf.ac.cn
|
|
[1] National Standards of the People’s Republic of China(中华人民共和国国家标准). GB/T 15036.1—2009. Solid Wood Flooring(实木地板). Part 1:Technical Requirements(第1部分:技术要求).
[2] XU Feng(徐 峰). Wood Identification Map(木材鉴定图谱). Beijing:Chemical Industry Press(北京:化学工业出版社),2010. 9.
[3] WANG Yu-rong,REN Hai-qing(王玉荣,任海青). Journal of Anhui Agricultural University(安徽农业大学学报),2012,39(6):894.
[4] WANG Yu-rong,REN Hai-qing,ZHAO Rong-jun,et al(王玉荣,任海青,赵荣军,等). Wood Processing Machinery(木材加工机械),2012,23(5):9.
[5] National Standards of the People’s Republic of China(中华人民共和国国家标准). GB/T 1933—2009. Method for Determination of the Density of Wood(木材密度测定方法).
[6] Chen F,Jiang Z,Deng J,et al. Bioresources,2014,9(1):554.
[7] Belt T,Laine K,Hill C A S. Journal of Materials Science,2013,48(18):6426.
[8] Santos R B,Gomide J L,Hart P W. Tappi Journal,2015,14(1):9.
[9] Meng F D,Yu Y L,Zhang Y M,et al. Applied Surface Science,2016,371:383.
[10] Hao H,Chen T,Fan L,et al. Plos One,2013,8(10):e76660.
[11] Timar M C,Varodi A M,Gurǎu L. Wood Science and Technology,2016,50(1):135.
[12] LIU Yi-xing,ZHAO Guang-jie(刘一星,赵广杰). Materials of Wood Resources(木质资源材料学). Beijing:China Forestry Publishing House(北京:中国林业出版社),2004. 8.
|
[1] |
HAN Xue1, 2, LIU Hai1, 2, LIU Jia-wei3, WU Ming-kai1, 2*. Rapid Identification of Inorganic Elements in Understory Soils in
Different Regions of Guizhou Province by X-Ray
Fluorescence Spectrometry[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 225-229. |
[2] |
CHENG Hui-zhu1, 2, YANG Wan-qi1, 2, LI Fu-sheng1, 2*, MA Qian1, 2, ZHAO Yan-chun1, 2. Genetic Algorithm Optimized BP Neural Network for Quantitative
Analysis of Soil Heavy Metals in XRF[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3742-3746. |
[3] |
SUN Wei-ji1, LIU Lang1, 2*, HOU Dong-zhuang3, QIU Hua-fu1, 2, TU Bing-bing4, XIN Jie1. Experimental Study on Physicochemical Properties and Hydration Activity of Modified Magnesium Slag[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3877-3884. |
[4] |
LIU Wei1, 2, ZHANG Peng-yu1, 2, WU Na1, 2. The Spectroscopic Analysis of Corrosion Products on Gold-Painted Copper-Based Bodhisattva (Guanyin) in Half Lotus Position From National Museum of China[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3832-3839. |
[5] |
FANG Zheng, WANG Han-bo. Measurement of Plastic Film Thickness Based on X-Ray Absorption
Spectrometry[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3461-3468. |
[6] |
LIN Hong-jian1, ZHAI Juan1*, LAI Wan-chang1, ZENG Chen-hao1, 2, ZHAO Zi-qi1, SHI Jie1, ZHOU Jin-ge1. Determination of Mn, Co, Ni in Ternary Cathode Materials With
Homologous Correction EDXRF Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3436-3444. |
[7] |
LI Xiao-li1, WANG Yi-min2*, DENG Sai-wen2, WANG Yi-ya2, LI Song2, BAI Jin-feng1. Application of X-Ray Fluorescence Spectrometry in Geological and
Mineral Analysis for 60 Years[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 2989-2998. |
[8] |
ZHU Yu-qi1, 2, ZHANG Xin2, DU Pan-pan2, LIU Shu1, ZHANG Gui-xin1, 2, GUAN Song-lei2*, ZHENG Zhong1*. Infrared Spectroscopy and X-Ray Spectroscopy Combined With
Inductively Coupled Plasma Mass Spectrometry for Quality
Control of Mongolian Medicine Yu Grain Soil[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3163-3169. |
[9] |
XU Ya-fen1, LIU Xian-yu1*, CHEN Quan-li2, XU Chang3. Study on Mineral Composition and Spectral Characteristics of “Middle East Turquoise”[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2862-2867. |
[10] |
LI Yu-tang1, WANG Lin-zhu1, 2*, LI Xiang3, WANG Jun1. Characterization and Comparative Analysis of Non-Metallic Inclusions in Zirconium Deoxidized Steel[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2916-2921. |
[11] |
GAO Ya1, LIAO Cui-ping1, ALATAN Chaolumen2, CHEN Jian-bo3, TU Ya4*. X-Ray Diffraction and Infrared Spectral Analysis of the Differential Chemical Indicators Between the Raw and Milk-Processed Corals[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(08): 2494-2499. |
[12] |
CHENG Fang-beibei1, 2, GAN Ting-ting1, 3*, ZHAO Nan-jing1, 4*, YIN Gao-fang1, WANG Ying1, 3, FAN Meng-xi4. Rapid Detection of Heavy Metal Lead in Water Based on Enrichment by Chlorella Pyrenoidosa Combined With X-Ray Fluorescence Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(08): 2500-2506. |
[13] |
ZHOU Qing-qing1, LI Dong-ling1, 2, JIANG Li-wu1, 3*, WAN Wei-hao1, ZENG Qiang4, XUE Xin4, WANG Hai-zhou1, 2*. Quantitative Statistical Study on Dendritic Component Distribution of Single Crystal Blade Based on Microbeam X-Ray Fluorescence Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(07): 2112-2118. |
[14] |
DU Zhi-heng1, 2, 3, HE Jian-feng1, 2, 3*, LI Wei-dong1, 2, 3, WANG Xue-yuan1, 2, 3, YE Zhi-xiang1, 2, 3, WANG Wen1, 2, 3. A New EDXRF Spectral Decomposition Method for Sharpening Error Wavelets[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(06): 1719-1724. |
[15] |
WANG Mei-ling1, 2, 3, 4, LI Fei1, 2, 3, 4*, WANG Xu-yang1, 2, 3, 4, ZHU Han-yu1, 2, 3, 4, QIAO Meng-dan1, 2, 3, 4, YUAN Jun-sheng1, 2, 3, 4*. Study on the Structure of K2SO4 Aqueous Solutions by X-Ray Scattering and Raman Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(06): 1838-1845. |
|
|
|
|