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Polipropilen/Polianilin Kompozit Filmlerin Dielektrik Özelliklerinin Yapay Sinir Ağları Modeli İle Tahmini

Year 2018, Volume: 6 Issue: 4, 787 - 802, 30.12.2018
https://doi.org/10.29109/gujsc.398275

Abstract

Bu
çalışmada, polipropilen (PP) polimerinin frekansa bağlı kompleks dielektrik
fonksiyonunun gerçek ve sanal bileşenlerinin, kütlece % 0,3, 0,4, 0,6 ve 0,7
polianilin (PANI) katkısına bağlı olarak değişimi dielektrik spektroskopisi
yöntemiyle incelenmiştir.  Dielektrik
ölçümler, 100 Hz ile 15 MHz arasında değişen frekans aralığında oda
sıcaklığında empedans analizör yardımıyla gerçekleştirilmiştir. Ayrıca, PP/PANI
kompozitlerin kompleks dielektrik fonksiyonlarının gerçek ve sanal
bileşenlerinin frekansa bağlılığının Yapay Sinir Ağları (YSA) modeli ile tahmin
edilebileceği gösterilmiştir. Bu bağlamda, deneysel olarak hazırlanmamış farklı
PP/PANI kompozitler için YSA modeliyle kütlece farklı PANI katkı yüzdeleri için
(% 0,1, 0,2, 0,5, 0,8 ve 1), kompleks dielektrik fonksiyonun gerçek ve sanal
bileşenlerin frekansa bağlı değişimleri hesaplanmıştır.  YSA modeli ile elde edilen sonuçlar, kompleks
dielektrik fonksiyonlarının gerçek ve sanal bileşenlerinin artan PANI
katkısıyla lineer olmayan değişimiyle uyumlu olarak bulunmuştur.

References

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  • S. Nagasawa, A. Fujimori, T. Masuko, M. Iguchi, Crystallization of polypropylene containing nucleators. Polymer, 46: 14 (2005) 5241-5250.
  • M. Chipara, D. Hui, P.V. Notingher, M.D. Chipara, K.T. Lau, J. Sankar and D. Panaitescu. On polyethylene–polyaniline composites. Composites Part B: Engineering, 34: 7 (2003) 637-645.
  • M. Ates, A review study of (bio) sensor systems based on conducting polymers. Materials Science and Engineering: C, 33: 4 (2013) 1853-1859.
  • H. Tang, Y. Ding, C. Zang, J. Gu, Q. Shen, J. Kan, Effect of Temperature on Electrochemical Degradation of Polyaniline. International Journal of Electrochemical Science, 9 (2014) 7239-7252.
  • Zh. A. Boeva, V. G. Sergeyev, Polyaniline: Synthesis, Properties, and Application. Polymer Science Series C, 56: 1 (2014) 144-153.
  • A. B. Samui, A. S, Patankar, J, Rangarajan and P. C. Deb, Study of polyaniline containing paint for corrosion prevention. Progress in Organic Coatings, 47: 1 (2003) 1-7.
  • A. Mekki, B. Mettai, Z. Ihdene, R.Mahmoud, Z. Mekhalif. Inverse gas chromatography characterization of polyaniline complexes: application to volatile organic compounds sensing. Iranian Polymer Journal, 22: 9 (2013) 677-687.
  • W. Z. Zhang, X. W. Kan, S. F. Jiao, J. G. Sun, D. S. Yang, B. Fang, Electrochemical characteristics and catalytic activity of polyaniline doped with ferrocene perchlorate. Journal of Applied Polymer Science, 102: 6 (2006) 5633- 5639.
  • E. Akbarinezhad, M. Ebrahimia, F. Sharif, M.M. Attar, H.R. Faridi, Synthesis and evaluating corrosion protection effects of emeraldine base PAni/clay nanocomposite as a barrier pigment in zinc-rich ethyl silicate primer, Progress in Organic Coatings 70: 1 (2011) 39-44
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  • P. Sukitpaneenit, T. Thanpitcha, A. Sirivat, C. Weder, R. Rujiravanit, Electrical Conductivity and Mechanical Properties of Polyaniline/Natural Rubber Composite Fibers. Journal of Applied Polymer Science, 106: 6 (2007) 4038-4046
  • S. Chandran A. and S. K. Narayanankutty, Polyaniline-Coated Short Nylon Fiber/Natural Rubber Conducting Composite. Polymer-Plastics Technology and Engineering, 50: 5 (2011) 443-452
  • M. J. da Silva, A. O. Sanches, L. F. Malmonge, J. A. Malmonge, Electrical, mechanical, and thermal analysis of natural Rubber/Polyaniline-Dbsa composite. Materials Research, 17: 1 (2014) 59-63.
  • O. Eyecioglu, M. Kilic, Y. Karabul, U. Alkan, O. Icelli, Artificial Neural Networks Study on Prediction of Dielectric Permittivity of Basalt/PANI Composites, International Journal of Engineering Technologies, 2: 2 (2016) 42-48.
  • S. Thawornwong, D. Enke, The adaptive selection of financial and economic variables for use with artificial neural networks. Neurocomputing, 56 (2004) 205-231.
  • J. A. Jargon, K. C. Gupta, D. C. DeGroot, Applications of Artificial Neural Networks to RF and Microwave Measurements. Int. J. RF and Microwave CAE, 12 (2002) 3-24.
  • M. Demetgül, Pnömatik Sistemde Gerçek Zamanlı Lvq Yapay Sinir Ağı Algoritması ile Arıza Tespiti. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, 14: 1 (2008) 83-90.
  • A. Habibi-Yangjeh, Prediction dielectric constant of different ternary liquid mixtures at various temperatures and compositions using artificial neural networks. Physics and Chemistry of Liquids, 45: 4 (2007) 471-478.
  • M. İnal ve F. Aras, Yalıtkan Malzemelerin Dielektrik Özelliklerinin Yapay Sinir Ağlarıyla Belirlenmesi. Gazi Üniv. Müh. Mim. Fak. Der., 20: 4 (2005) 455-462.
  • R. C. Schweitzer, J. B. Morris, The development of a quantitative structure property relationship (QSPR) for the prediction of dielectric constants using neural networks. Analytica Chimica Acta, 384 (1999) 285-303.
  • V. F. Lvovich, Impedance Spectroscopy Applications to Electrochemical and Dielectric Phenomena, New Jersey: Wiley, 2012.
  • M. T. Hagan, M. B. Menhaj, Training feedforward networks with the Marquardt algorithm. IEEE Transactions on Neural Networks, 5: 6 (1994) 989-993.
  • D. Svozil, V. Kvasnicka, J. Pospichal, Introduction to multi-layer feed-forward neural networks," Chemometrics and Intelligent Laboratory Systems, 39: 1, (1997) 43-62.
  • R. Hecht-Nielsen, Theory of the backpropagation neural network. Neural Networks for Perception, (1992) 65–93.
  • S.Sapna, A. Tamilarasi, M. P. Kumar, Backpropagation Learning Algorithm Based on Levenberg Marquardt Algorithm. Computer Science & Information Technology 7 (2012) 393-398.
  • K. Levenberg, A Method for the Solution of Certain Non-Linear Problems in Least Squares. Quarterly of Applied Mathematics, 2: 1 (1944) 164-168.
  • D. Marquardt, An Algorithm for Least-Squares Estimation of Nonlinear Parameters, SIAM Journal on Applied Mathematics, 11: 1 (1963) 431-441.
  • A. A. Suratgar, M. B. Tavakoli, A. Hoseinabadi, Modified Levenberg-Marquardt Method for Neural Networks Training, World Academy of Science, Engineering and Technology, 1: 6 (2007) 1745-1747.
  • P. K. C. Pillai, G. K. Narula, A. K. Tripathi, Dielectric properties of Polypropylene/Polycarbonate Polyblends, Polymer Journal, 16: 7 (1984) 575-578.
  • Y. Dang, Y. Wang, Y. Deng, M. Li, Y. Zhang, Zhi-Wei Zhang, Enhanced dielectric properties of polypropylene based composite using Bi2S3 nanorod filler, Progress in Natural Science: Materials International, 21: 3 (2011) 216-220.
Year 2018, Volume: 6 Issue: 4, 787 - 802, 30.12.2018
https://doi.org/10.29109/gujsc.398275

Abstract

References

  • A. Akinci, Mechanical and structural properties of polypropylene composites filled with graphite flakes. Archives of Materials Science and Engineering, 35: 2 (2009) 91-94.
  • S. Nagasawa, A. Fujimori, T. Masuko, M. Iguchi, Crystallization of polypropylene containing nucleators. Polymer, 46: 14 (2005) 5241-5250.
  • M. Chipara, D. Hui, P.V. Notingher, M.D. Chipara, K.T. Lau, J. Sankar and D. Panaitescu. On polyethylene–polyaniline composites. Composites Part B: Engineering, 34: 7 (2003) 637-645.
  • M. Ates, A review study of (bio) sensor systems based on conducting polymers. Materials Science and Engineering: C, 33: 4 (2013) 1853-1859.
  • H. Tang, Y. Ding, C. Zang, J. Gu, Q. Shen, J. Kan, Effect of Temperature on Electrochemical Degradation of Polyaniline. International Journal of Electrochemical Science, 9 (2014) 7239-7252.
  • Zh. A. Boeva, V. G. Sergeyev, Polyaniline: Synthesis, Properties, and Application. Polymer Science Series C, 56: 1 (2014) 144-153.
  • A. B. Samui, A. S, Patankar, J, Rangarajan and P. C. Deb, Study of polyaniline containing paint for corrosion prevention. Progress in Organic Coatings, 47: 1 (2003) 1-7.
  • A. Mekki, B. Mettai, Z. Ihdene, R.Mahmoud, Z. Mekhalif. Inverse gas chromatography characterization of polyaniline complexes: application to volatile organic compounds sensing. Iranian Polymer Journal, 22: 9 (2013) 677-687.
  • W. Z. Zhang, X. W. Kan, S. F. Jiao, J. G. Sun, D. S. Yang, B. Fang, Electrochemical characteristics and catalytic activity of polyaniline doped with ferrocene perchlorate. Journal of Applied Polymer Science, 102: 6 (2006) 5633- 5639.
  • E. Akbarinezhad, M. Ebrahimia, F. Sharif, M.M. Attar, H.R. Faridi, Synthesis and evaluating corrosion protection effects of emeraldine base PAni/clay nanocomposite as a barrier pigment in zinc-rich ethyl silicate primer, Progress in Organic Coatings 70: 1 (2011) 39-44
  • M. Chipara, D. Hui, P. V. Notingher, M. D. Chipara, K. T. Lau, J. Sankar and D. Panaitescu, On polyethylene–polyaniline composites. Composites Part B: Engineering, 34: 7 (2003) 637-645.
  • P. Sukitpaneenit, T. Thanpitcha, A. Sirivat, C. Weder, R. Rujiravanit, Electrical Conductivity and Mechanical Properties of Polyaniline/Natural Rubber Composite Fibers. Journal of Applied Polymer Science, 106: 6 (2007) 4038-4046
  • S. Chandran A. and S. K. Narayanankutty, Polyaniline-Coated Short Nylon Fiber/Natural Rubber Conducting Composite. Polymer-Plastics Technology and Engineering, 50: 5 (2011) 443-452
  • M. J. da Silva, A. O. Sanches, L. F. Malmonge, J. A. Malmonge, Electrical, mechanical, and thermal analysis of natural Rubber/Polyaniline-Dbsa composite. Materials Research, 17: 1 (2014) 59-63.
  • O. Eyecioglu, M. Kilic, Y. Karabul, U. Alkan, O. Icelli, Artificial Neural Networks Study on Prediction of Dielectric Permittivity of Basalt/PANI Composites, International Journal of Engineering Technologies, 2: 2 (2016) 42-48.
  • S. Thawornwong, D. Enke, The adaptive selection of financial and economic variables for use with artificial neural networks. Neurocomputing, 56 (2004) 205-231.
  • J. A. Jargon, K. C. Gupta, D. C. DeGroot, Applications of Artificial Neural Networks to RF and Microwave Measurements. Int. J. RF and Microwave CAE, 12 (2002) 3-24.
  • M. Demetgül, Pnömatik Sistemde Gerçek Zamanlı Lvq Yapay Sinir Ağı Algoritması ile Arıza Tespiti. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, 14: 1 (2008) 83-90.
  • A. Habibi-Yangjeh, Prediction dielectric constant of different ternary liquid mixtures at various temperatures and compositions using artificial neural networks. Physics and Chemistry of Liquids, 45: 4 (2007) 471-478.
  • M. İnal ve F. Aras, Yalıtkan Malzemelerin Dielektrik Özelliklerinin Yapay Sinir Ağlarıyla Belirlenmesi. Gazi Üniv. Müh. Mim. Fak. Der., 20: 4 (2005) 455-462.
  • R. C. Schweitzer, J. B. Morris, The development of a quantitative structure property relationship (QSPR) for the prediction of dielectric constants using neural networks. Analytica Chimica Acta, 384 (1999) 285-303.
  • V. F. Lvovich, Impedance Spectroscopy Applications to Electrochemical and Dielectric Phenomena, New Jersey: Wiley, 2012.
  • M. T. Hagan, M. B. Menhaj, Training feedforward networks with the Marquardt algorithm. IEEE Transactions on Neural Networks, 5: 6 (1994) 989-993.
  • D. Svozil, V. Kvasnicka, J. Pospichal, Introduction to multi-layer feed-forward neural networks," Chemometrics and Intelligent Laboratory Systems, 39: 1, (1997) 43-62.
  • R. Hecht-Nielsen, Theory of the backpropagation neural network. Neural Networks for Perception, (1992) 65–93.
  • S.Sapna, A. Tamilarasi, M. P. Kumar, Backpropagation Learning Algorithm Based on Levenberg Marquardt Algorithm. Computer Science & Information Technology 7 (2012) 393-398.
  • K. Levenberg, A Method for the Solution of Certain Non-Linear Problems in Least Squares. Quarterly of Applied Mathematics, 2: 1 (1944) 164-168.
  • D. Marquardt, An Algorithm for Least-Squares Estimation of Nonlinear Parameters, SIAM Journal on Applied Mathematics, 11: 1 (1963) 431-441.
  • A. A. Suratgar, M. B. Tavakoli, A. Hoseinabadi, Modified Levenberg-Marquardt Method for Neural Networks Training, World Academy of Science, Engineering and Technology, 1: 6 (2007) 1745-1747.
  • P. K. C. Pillai, G. K. Narula, A. K. Tripathi, Dielectric properties of Polypropylene/Polycarbonate Polyblends, Polymer Journal, 16: 7 (1984) 575-578.
  • Y. Dang, Y. Wang, Y. Deng, M. Li, Y. Zhang, Zhi-Wei Zhang, Enhanced dielectric properties of polypropylene based composite using Bi2S3 nanorod filler, Progress in Natural Science: Materials International, 21: 3 (2011) 216-220.
There are 31 citations in total.

Details

Primary Language Turkish
Subjects Metrology, Applied and Industrial Physics
Journal Section Original Articles
Authors

Önder Eyecioglu

Mehmet Kılıç This is me

Zeynep Güven Özdemiir This is me

Publication Date December 30, 2018
Submission Date February 24, 2018
Published in Issue Year 2018 Volume: 6 Issue: 4

Cite

APA Eyecioglu, Ö., Kılıç, M., & Özdemiir, Z. G. (2018). Polipropilen/Polianilin Kompozit Filmlerin Dielektrik Özelliklerinin Yapay Sinir Ağları Modeli İle Tahmini. Gazi University Journal of Science Part C: Design and Technology, 6(4), 787-802. https://doi.org/10.29109/gujsc.398275

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