Laser-induced breakdown spectroscopy with neural network approach for plastic identification and classification in waste management

Karthigaikumar Palanivel, Justin Varghese

Article ID: 3092
Vol 7, Issue 1, 2024

VIEWS - 230 (Abstract) 158 (PDF)

Abstract


The threats to the environment and humans are increasing every day due to the use of modern plastics and their improper disposal approaches. Researchers pay more attention to reducing plastic waste through recycling so that it can be used as a raw material. In the recycling chain, grading or identifying different types of plastic is essential. For this, Lase Induced Breakdown Spectroscopy (LIBS) has been established. LIBS is an effective investigation tool that analyzes plastics in a qualitative and quantitative manner. Spectral analysis of different kinds of plastics is performed from the plasma emission obtained from LIBS. In this research work different types of plastic samples are identified using LIBS and classified using back propagation neural network algorithm (BPNN). The research aimed to attain a simple application to detect plastic polymers compared to existing approaches. To validate the better results proposed model performances are compared with existing kNN, SIMCA and ANN based classification models.


Keywords


Laser-induced breakdown spectroscopy (LIBS); plastic classification; Neural network; waste management

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References


1. Annual production of plastics worldwide from 1950 to 2021 (in million metric tons). Available online: https://www.statista.com/statistics/282732/global-production-of-plastics-since-1950/ (accessed on 18 July 2023).

2. Bolea-Fernandez E, Rua-Ibarz A, Velimirovic M, et al. Detection of microplastics using inductively coupled plasma-mass spectrometry (ICP-MS) operated in single-event mode. Journal of Analytical Atomic Spectrometry. 2020, 35(3): 455-460. doi: 10.1039/c9ja00379g

3. Zhu S, Chen H, Wang M, et al. Plastic solid waste identification system based on near infrared spectroscopy in combination with support vector machine. Advanced Industrial and Engineering Polymer Research. 2019, 2(2): 77-81. doi: 10.1016/j.aiepr.2019.04.001

4. Stefas D, Gyftokostas N, Bellou E, et al. Laser-Induced Breakdown Spectroscopy Assisted by Machine Learning for Plastics/Polymers Identification. Atoms. 2019, 7(3): 79. doi: 10.3390/atoms7030079

5. Adel Ismael Chaqmaqchee F. Comparison of Various Plastics Wastes Using X-ray Fluorescence. American Journal of Materials Synthesis and Processing. 2017, 2(2): 24. doi: 10.11648/j.ajmsp.20170202.12

6. Chen L, Jin S, Li W. Rapid identification of plastics based on Raman spectroscopy with the combination of support vector machine. 2017 16th International Conference on Optical Communications and Networks (ICOCN). Published online August 2017. doi: 10.1109/icocn.2017.8121214

7. Zhang L, Yin W, Dong L, et al. Stability Enhanced Online Powdery Cement Raw Materials Quality Monitoring Using Laser-Induced Breakdown Spectroscopy. IEEE Photonics Journal. 2017, 9(5): 1-10. doi: 10.1109/jphot.2017.2741066

8. Gaudiuso R, Melikechi N, Abdel-Salam ZA, et al. Laser-induced breakdown spectroscopy for human and animal health: A review. Spectrochimica Acta Part B: Atomic Spectroscopy. 2019, 152: 123-148. doi: 10.1016/j.sab.2018.11.006

9. Wang Q, Teng G, Zhao Y, et al. Identification and Determination of the Bloodstains Dry Time in the Crime Scenes Using Laser-Induced Breakdown Spectroscopy. IEEE Photonics Journal. 2019, 11(3): 1-12.

10. Vinod P, Desai BMA, Sarathi R, et al. Investigation on the electrical, thermal and mechanical properties of silicone rubber nanocomposites. IEEE Transactions on Dielectrics and Electrical Insulation. 2019, 26(6): 1876-1884. doi: 10.1109/tdei.2019.008205

11. Neelmani, Thangabalan B, Vasa NJ, et al. Investigation on Surface Condition of the Corona-Aged Silicone Rubber Nanocomposite Adopting Wavelet and LIBS Technique. IEEE Transactions on Plasma Science. 2021, 49(8): 2294-2304. doi: 10.1109/tps.2021.3094124

12. Yin P, Hu B, Li Q, et al. Imaging of Tumor Boundary Based on Multielements and Molecular Fragments Heterogeneity in Lung Cancer. IEEE Transactions on Instrumentation and Measurement. 2021, 70: 1-7. doi: 10.1109/tim.2021.3102755

13. Babu MS, Imai T, Sarathi R. Classification of Aged Epoxy Micro–Nanocomposites Through PCA- and ANN-Adopted LIBS Analysis. IEEE Transactions on Plasma Science. 2021, 49(3): 1088-1096. doi: 10.1109/tps.2021.3061410

14. Zhang Y, Zhang T, Li H. Application of laser-induced breakdown spectroscopy (LIBS) in environmental monitoring. Spectrochimica Acta Part B: Atomic Spectroscopy. 2021, 181: 106218. doi: 10.1016/j.sab.2021.106218

15. Junjuri R, Zhang C, Barman I, et al. Identification of post-consumer plastics using laser-induced breakdown spectroscopy. Polymer Testing. 2019, 76: 101-108. doi: 10.1016/j.polymertesting.2019.03.012

16. Costa VC, Castro JP, Andrade DF, et al. Laser-induced breakdown spectroscopy (LIBS) applications in the chemical analysis of waste electrical and electronic equipment (WEEE). TrAC Trends in Analytical Chemistry. 2018, 108: 65-73. doi: 10.1016/j.trac.2018.08.003

17. Wang Q, Cui X, Teng G, et al. Evaluation and improvement of model robustness for plastics samples classification by laser-induced breakdown spectroscopy. Optics & Laser Technology. 2020, 125: 106035. doi: 10.1016/j.optlastec.2019.106035

18. Tang Y, Guo Y, Sun Q, et al. Industrial polymers classification using laser-induced breakdown spectroscopy combined with self-organizing maps and K-means algorithm. Optik. 2018, 165: 179-185. doi: 10.1016/j.ijleo.2018.03.121

19. Brunnbauer L, Larisegger S, Lohninger H, et al. Spatially resolved polymer classification using laser induced breakdown spectroscopy (LIBS) and multivariate statistics. Talanta. 2020, 209: 120572. doi: 10.1016/j.talanta.2019.120572

20. Papai R, da Silva Mariano C, Pereira CV, et al. Matte photographic paper as a low-cost material for metal ion retention and elemental measurements with laser-induced breakdown spectroscopy. Talanta. 2019, 205: 120167. doi: 10.1016/j.talanta.2019.120167

21. Völker T, Millar S, Strangfeld C, et al. Identification of type of cement through laser-induced breakdown spectroscopy. Construction and Building Materials. 2020, 258: 120345. doi: 10.1016/j.conbuildmat.2020.120345

22. Chen D, Wang T, Ma Y, et al. Rapid characterization of heavy metals in single microplastics by laser induced breakdown spectroscopy. Science of The Total Environment. 2020, 743: 140850. doi: 10.1016/j.scitotenv.2020.140850

23. Król M, Gondko K, Kula A, et al. Characterization of the elemental composition of Polish banknotes by X-ray fluorescence and laser-induced breakdown spectroscopy. Spectrochimica Acta Part B: Atomic Spectroscopy. 2020, 169: 105898. doi: 10.1016/j.sab.2020.105898

24. Malenfant DJ, Paulick AE, Rehse SJ. A simple and efficient centrifugation filtration method for bacterial concentration and isolation prior to testing liquid specimens with laser-induced breakdown spectroscopy. Spectrochimica Acta Part B: Atomic Spectroscopy. 2019, 158: 105629. doi: 10.1016/j.sab.2019.05.018

25. Wang Q, Teng G, Li C, et al. Identification and classification of explosives using semi-supervised learning and laser-induced breakdown spectroscopy. Journal of Hazardous Materials. 2019, 369: 423-429. doi: 10.1016/j.jhazmat.2019.02.015

26. Gondal MA, Aldakheel RK, Almessiere MA, et al. Determination of heavy metals in cancerous and healthy colon tissues using laser induced breakdown spectroscopy and its cross-validation with ICP-AES method. Journal of Pharmaceutical and Biomedical Analysis. 2020, 183: 113153. doi: 10.1016/j.jpba.2020.113153

27. Singh J, Kumar R, Awasthi S, et al. Laser Induced breakdown spectroscopy: A rapid tool for the identification and quantification of minerals in cucurbit seeds. Food Chemistry. 2017, 221: 1778-1783. doi: 10.1016/j.foodchem.2016.10.104

28. Horsfall JPO, Trivedi D, Smith NT, et al. A new analysis workflow for discrimination of nuclear grade graphite using laser-induced breakdown spectroscopy. Journal of Environmental Radioactivity. 2019, 199-200: 45-57. doi: 10.1016/j.jenvrad.2019.01.004

29. Garlea E, Bennett BN, Martin MZ, et al. Novel use of a hand-held laser induced breakdown spectroscopy instrument to monitor hydride corrosion in uranium. Spectrochimica Acta Part B: Atomic Spectroscopy. 2019, 159: 105651. doi: 10.1016/j.sab.2019.105651




DOI: https://doi.org/10.24294/ace.v7i1.3092

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