FT-IR Spectral Model of Polyester-Cotton Fabrics with Corona Plasma Treatment using Artificial Neural Networks (ANNs)

Irwan Irwan, Valentinus Galih Vidia utra, Juliany Ningsih Mohamad

Abstract

Corona plasma technology has been studied as a surface modification for the adhesive bonding of polymers. Although corona plasma (C.P.) is becoming more popular in nanotechnology, the influence of corona plasma treatment parameters on the FT-IR spectra is a problem that has yet to be addressed. The purpose of this study is to use an artificial neural network to study the influence of corona plasma (C.P.) treatment parameters on textile polymer and evaluate the ability of this model to predict FT-IR spectral information from FT-IR measurements. In this study, polymers were modified under various corona plasma treatment conditions. We investigated FT-IR spectra information of polymers from FT-IR measurements by varying corona plasma treatment variables. We used three input parameters in this study: wavenumber, voltage, and exposure time—two output parameters: fabric roughness with SEM according to the degree of smoothness and percent transmission with FT-IR. The novel aspect of this study is that we used ANN to model the plasma treatment on polyester-cotton fabrics and the FT-IR spectra accurately enough for the first time. According to this study, the model that used four nodes (neurons) in the hidden layer, three input parameters (x1,x2,x3), and 20 iterations is appropriate for determining fabric surface roughness (S.R.) and percent transmission (T%). Based on this research, the values of R2 for determining fabric surface roughness (S.R.) and percent transmission (T%) were 99.79 percent and 67.18 percent, respectively. The results showed that the developed ANNs could accurately predict the experimental data in detail. This study is significant because it uses artificial intelligence to calculate and simulate the FT-IR spectra and fabric surface roughness of plasma treatment on textile fabrics. This study's scientific application is that it will help experts, researchers, and engineers understand the implications of plasma on the chemical structure of textile materials.

Keywords

Plasma; ANN; FT-IR; Fabric; Textile

Full Text:

PDF

References

  1. D. L. Francisco, L. B. Paiva, and W. Aldeia, "Advances in Polyamide Nanocomposites: A Review.," Polymer Composites., vol. 40, no. 3, pp. 851- 870, 2018.
  2. V. Putra, J. Mohamad, D. Arief and Y. Yusuf, "Surface modification of polyester-cotton (T.C. 70%) fabric by corona discharged plasma with tip cylinder electrode configuration-assisted coating carbon black conductive ink for electromagnetic shielding fabric," Arab Journal of Basic and Applied Sciences, vol. 28, no. 1, p. 272–282, vol. 28, no. 1, pp. 272–282, 2021.
  3. M. Molakarimi, M. Khajeh Mehrizi and A. Haji, "Effect of plasma treatment and grafting of B-cyclodextrin on color properties of wool fabric dyed with shrimp shell extract," The Journal of the Textile Institute, vol. 107, no. 10, pp. 1314-1321, 2016.
  4. H. Rausher, M. Perucca and G. & Buyle, Plasma technology for hyperfunctionals surfaces, Weinheim: Wiley-VCH, 2010.
  5. R. Morent, N. De Geyter, J. Verschuren, K. De Clerck, P. Kiekens and C. Leys, "Non-thermal plasma treatment of textiles," Surface and Coatings Technology, vol. 202, no. 14, pp. 3427–3449, 2008.
  6. M. R. Alexander, S. Payan and T. M. Duc, "Interfacial interactions of plasma-polymerized acrylic acid and an oxidized aluminium surface investigated using XPS, FTIR and poly(acrylic acid) as a model compound," Surface and Interface Analysis, vol. 26, no. 13, pp. 961-973, 1998.
  7. N. Bhat, A. Netravali, A. Gore, M. Sathianarayanan, G. Arolkar and R. Deshmukh, "Surface modification of cotton fabrics using plasma technology," Textile Research Journal, vol. 81, no. 10, pp. 1014-1026, 2011.
  8. B. Paosawatyanyong, K. Kamlangkla and S. Hodak, "Hydrophobic and Hydrophilic Surface Nano-Modification of PET Fabric by Plasma Process," Journal of Nanoscience and Nanotechnology, vol. 10, no. 11, pp. 7050-7054, 2010.
  9. S. Masaoka, "Plasma sterilization of polyethylene terephthalate bottles by pulsed corona discharge at atmospheric pressure," Biocontrol Sci, p. 59, 2007.
  10. F. Leroux, A. Perwuelz, C. Campagne and e. al, "Atmospheric air-plasma treatments of polyester textile structures," J Adhes Sci Technol, vol. 20, pp. 939–957, 2006.
  11. C. Murru, C. Chimeno-Trinchet, M. E. Díaz-García, R. Badía-Laíño and A. Fernández-González, "Artificial Neural Network and Attenuated Total Reflectance-Fourier Transform Infrared Spectroscopy to identify the chemical variables related to ripeness and variety classification of grapes for Protected. Designation of Origin wine production," Computers and Electronics in Agriculture, vol. 164, pp. 104922, 2019.
  12. W. Q. Z. M. X. J. L. L. K. B. C. M. N. Z. W. Q. M. Nie, M. Xiao, L. Luo, K. Bao, J. K. Chen and B. Li, "FT-IR Spectroscopy and Artificial Neural Network Identification of Fusarium Species," J. Phytopathology, vol. 155, no. doi: 10.1111/j.1439-0434.2007.01245.x, pp. 364–367, 2007.
  13. N. Naderi, F. Agend, R. Faridi-Majidi, N. Sharifi-Sanjani and M. Madani, "Prediction of nanofiber diameter and optimization of electrospinning process via response surface methodology," J. Nanosci. Nanotechnol, vol. 8, no. 5, pp. 2509–2515, 2008.
  14. T. Padmanabhan, V. Kamaraj, L. Magwood and B. Starly, "Experimental investigation on the operating variables of a near-field electrospinning process via response surface methodology," J. Manuf. Process, vol. 13, no. 2, pp. 104–112, 2011.
  15. P. Souza, G. Dotto and N. Salau, Journal of Environmental Chemical Engineering, vol. 6, no. 6, pp. 7152-710, 2018.
  16. C. Wang, X. Wang and X. He, " Neural networks model of polypropylene surface modification by air plasma," in Proceedings of the IEEE International Conference on Automation and Logistic, Jinan, China, 2007.
  17. A. Majumdar, M. Ciocoiu and M. Blaga, "Modelling of ring yarn unevenness by soft computing approach," Fibers and Polymers, vol. 9, no. 2, pp. 210-216, 2008.
  18. O. Demiryurek and E. Koe, "Predicting the tensile strength of polyester/viscose blended open-end rotor spun yarns using artificial neural network and statistical models," Fibers and Polymers, vol. 10, no. 2, pp. 237-245, 2009.
  19. M. A. Karimi, P. Pourhakkak, M. Adabi, S. Firoozi, M. Adabi and M. Naghibzadeh, "Using an artificial neural network for the evaluation of the parameters controlling PVA/chitosan electrospun nanofibers diameter," e-Polymers, vol. 15(2), no. https://doi.org/10.1515/epoly-2014-0198, pp. 127–38, 2015.
  20. R. Faridi‐Majidi, H. Ziyadi, N. Naderi and A. Amani, "Use of artificial neural networks to determine parameters controlling the nanofibers diameter in electrospinning of nylon‐6," J. Appl. Polym. Sci., vol. 124, no. 2, pp. 1589–97, 2012.

Refbacks

  • There are currently no refbacks.