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Qualitative and Quantitative Multivariate Analysis of Optical Density Spectra of Plastic Waste
Abstract
5 types of plastics were classified based on NIR spectra of optical density using multivariate cluster analysis in principal component space. Accuracy above 0.96 is obtained by ranking spectral variables by decreasing variance of measured optical density. Changes in polycarbonate VIS-NIR spectra during thermal degradation were modeled using partial least squares method with searching combination moving windows of optimal width. A quantitative calibration of the aging term up to 11.5 years was obtained with a root mean square error of the estimate around 19 days and a residual predictive deviation of more than 45.
Keywords
absorption spectrum,
principal component analysis,
spectral variables selection,
k nearest neighbors,
hierarchical cluster analysis,
partial least squares,
polymers
Supporting agencies: The work was carried out with the financial support of the Belarusian Republican Foundation for Basic Research (grant no. F22-031)
About the Authors
P. A. Kulikovskaya
B. I. Stepanov Institute of Physics of the National Academy
of Sciences of Belarus
Belarus
Belarus
Minsk
M. A. Khodasevich
B. I. Stepanov Institute of Physics of the National Academy
of Sciences of Belarus
Belarus
Belarus
Minsk
References
1. R. Geyer, J. Jambeck, K. Law. Sci. Adv., 3 (2017) e1700782
2. J. Yang, Y. P. Xu, P. Chen, J. Y. Li, D. Liu, X. L. Chu. J. Cleaner Prod., 431 (2023) 139771
3. J. Zalasiewicz, C. N. Waters, J. A. Ivar do Sul, P. L. Corcoran. Anthropocene, 13 (2016) 4—17
4. Б. С. Кирин, А. Н. Клокова. Успехи в химии и хим. технологии, 3 (2014) 31—33
5. Q. Wang, X. Wu, L. Chen, Z. Yang, Z. Fang. Appl. Spectrosc., 71 (2017) 2538—2548
6. R. Junjuri, M. Gundawar. Waste Management, 117 (2020) 48—57
7. S. Zhu, H. Chen, M. Wang, X. Guo, Y. Lei, G. Jin. Adv. Industr. and Eng. Polymer Res., 2 (2019) 77—81
8. R. Lenz, K. Enders, C. A. Stedmon, D. M. A. Mackenzie, T. G. Nielsen. Marine Pollution Bulletin, 100 (2015) 82—91
9. S. Musazzi, U. Perini. Laser-Induced Breakdown Spectroscopy Theory and Applications, Springer-Verlag Berlin Heidelberg (2014) 56
10. A. Alassali, S. Fiore, K. Kuchta. Waste Management, 82 (2018) 71—81
11. A. Boldizar, K. Möller. Polymer Degradation and Stability, 81 (2003) 359—366
12. A. Rinnan, F. van den Berg, S. B. Engelsen. TrAC Trends in Analytical Chemistry, 28 (2009) 1201—1222
13. G. Schulze, A. Jirasek, M. M. L. Yu, A. Lim, R. F. B. Turner, M. W. Blades. Appl. Spectrosc., 59 (2005) 545—574
14. K. Zhao, Y. Ji, Y. Li, T. Li. Sensors, 18 (2018) 312(1—10), doi: 10.3390/s18010312
15. Z. M. Zhang, S. Chen, Y. Z. Liang. Analyst, 135 (2010) 1138—1146
16. https://code.google.com/archive/p/airpls/
17. A. Savitzky, M. Y. E. Golay. Anal. Chem., 36 (1964) 1627—1639
18. K. H. Esbensen, P. Geladi. Comprehensive Chemometrics (2009) 211—226
19. Б. Дюран, П. Оделл. Кластерный анализ, Москва, Статистика (1977)
20. S. Schiavone, B. Marchionni, R. Bucci, F. Marini. Vibr. Spectrosc., 107 (2020) 103040(1—9)
21. T. W. Liao. Pattern Recognition, 38 (2005) 1857—1874
22. P. Govender, V. Sivakumar. Atm. Poll. Res., 11 (2020) 40—56
23. L.A. Berrueta, R. M. Alonso-Salces, K. Héberger. J. Chromatography A, 1158 (2007) 196—214
24. Z. Xiaobo, Z. Jiewen, M. J. W. Povey, M. Holmes, M. Hanpin. Analyt. Chim. Acta, 667 (2010) 14—32
25. P. Geladi, B. Kowalski. Partial Least-Squares Regression: a Tutorial Analytica Chemica Acta, 186 (1986) 1—17
26. G. D. Garson. Statistical Publishing Associates (2016)
27. R. Zornoza, C. Guerrero, J. Mataix-Solera, K. M. Scow, V. Arcenegui, J. Mataix-Beneyto. Soil Biology & Biochemistry, 40 (2008) 1923—1930
28. М. А. Ходасевич, Н. А. Саскевич. Весцi НАН Беларусi, сер. фiз.-мат. навук, 1 (2018) 77—83
29. Стандартные методы по инфракрасному многомерному количественному анализу: СТ РК АСТМ Е 1655-2011. Введ. РК 20.11.11, Астана: Госстандарт Республики Казахстан (2011)
Review
For citations:
Kulikovskaya P.A., Khodasevich M.A. Qualitative and Quantitative Multivariate Analysis of Optical Density Spectra of Plastic Waste. Zhurnal Prikladnoii Spektroskopii. 2024;91(5):714-722. (In Russ.)
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