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Qualitative and Quantitative Analysis of Two Types of Wood Plastic Composites |
LAO Wan-li, LI Gai-yun*, CHEN Yi, XIANG Qin, WANG Chao, HUANG An-min |
Research Institute of Wood Industry, Chinese Academy of Forestry, Beijing 100091, China |
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Abstract Qualitative and quantitative analysis of different types of wood plastic composites (WPC) made of different plastics is important for waste WPC products classifying, recycling and quality controlin the production process, standardizing market order, protecting the legitimate rights and interests of the consumers during sales and use. Establishing a mixed model used for quantitative analysis of WPCmade of different plastics can reduce the costs and improve model applicability. However, the current studies on qualitative analysis of WPC made of different plastics do not address the quantitative analysis of WPC. Therefore, the complete technical systemcan not be established. There have been no studies concerning the quantitative analysis of WPC made of different plastics. For this purpose, in this study, Polyethylene (PE)and polypropylene (PP) were used as matrix materials, respectively. Chinese fir powders were used as filler, and some chemical regents were added. Then 20 Chinese fir/PE and 20 Chinese fir/PP composites were manufactured by extrusion moulding. FTIR spectral data of 40 WPC samples were obtained by potassium bromide pressed-disk technique. First derivatives and Standard Normal Variate(SNV)were used to preprocess the spectral data by The Unscrambler version 9.2. And the FTIR spectral data were analyzed by principal component analysis (PCA). Results showed that the WPC samples could be grouped according to their plastic matrixes, and the correct rate was 100% due to the differences between PE and PP. Partial least square regression (PLSR) models were developed to predict both wood flour and plastic contents in two types of WPC based the above FTIR spectra. Results indicated that for wood and plastic calibration, the coefficients of determination (R2) were 0.984 and 0.985, respectively; the standard errors of calibration (SEC) were 1.034% and 1.026%, respectively. For both wood and plastic validation, the R2 values were 0.956; the standard errors of cross validation (SECV) were 1.779% and 1.792%, respectively; the ratios of performance to deviation (RPD) were 4.83 and 4.85, respectively; The current model was used to predict the contents of wood and plastic in ten WPCs samples that were randomly selected for external validation. Results show that theaccuracy of the model is high, the relative prediction deviations for wood flour contents were lower than ±8%, and plastic contents were lower than ±7%. A rapid and accurate identification and determination method applied for PE-based WPC and PP-based WPC was established, whichlays the foundation for FTIR’s use in the manufacturing, quality control and recycling.
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Received: 2018-08-01
Accepted: 2018-12-15
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Corresponding Authors:
LI Gai-yun
E-mail: ligy@caf.ac.cn
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[1] Rimdusit S, Wongsongyot S, Jittarom S, et al. Journal of Polymer Research, 2011, 18(4): 801.
[2] LAO Wan-li, LI Gai-yun, QIN Te-fu, et al(劳万里, 李改云, 秦特夫, 等). Chemistry and Industry of Forest Products(林产化学与工业), 2015, 35(3): 20.
[3] LAO Wan-li, HE Yu-chan, LI Gai-yun, et al(劳万里, 何玉婵, 李改云, 等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2016, 36(1): 55.
[4] Fuad M Y, Zaini M J, Jamaludin M, et al. Journal of Applied Polymer Science, 1994, 51(11): 1875.
[5] Renneckar S, Zink-Sharp A G, Ward T C, et al. Journal of Applied Polymer Science, 2004, 93(3): 1484.
[6] Jeske H, Schirp A, Cornelius F. Thermochimica Acta, 2012, 543: 165.
[7] Windt M, Meier D, Lehnen R. Holzforschung, 2011, 65(2): 199.
[8] Lao W, Li G, Zhou Q, et al. Bioresources, 2014, 9(4).
[9] Li G, Lao W, Zou X, et al. Wood Science & Technology, 2016, 50(4): 705.
[10] Li G, Lao W, Qin T, et al. Holzforschung, 2015, 69(4): 399.
[11] Lohumi S. Journal of the Korean Wood Science & Technology, 2016, 44(6).
[12] Chiahuang L, Wu T L, Chen Y L, et al. Holzforschung, 2010, 64(6): 699.
[13] Mauruschat D, Plinke B, Aderhold J, et al. Wood Science & Technology, 2016, 50(2): 313.
[14] Geyter N D, Morent R, Leys C. Surface and Interface Analysis, 2010, 40(3-4): 608.
[15] Morent R, Geyter ND, Leys C, et al. Surface and Interface Analysis, 2008, 40: 597. |
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