Prediction of Dielectric Properties of Polypropylene/Polyaniline Composite Films By Artificial Neural Networks Model

Abstract

In this study, the change of the frequency dependence of the real and imaginary components of the complex dielectric function of the polypropylene (PP) polymer depending on the addition of 0.3%, 0.4%, 0.6% and 0.7% polyaniline (PANI) was investigated by using dielectric spectroscopy method. Dielectric measurements were performed at room temperature in the frequency range of 100 Hz to 15 MHz by impedance analyzer. Experimental results have shown that the dielectric parameters of PP exhibit non-linear variation with the PANI contribution. In this context, firstly, it has been shown that the frequency dependence of real and virtual components of complex dielectric functions of PP / PANI composites can be estimated with Artificial Neural Network (ANN) model. Then, the frequency dependences of the real and imaginary components of the complex dielectric function of the PP/PANI composites with different PANI additive concentrations (0.1, 0.2, 0.5, 0.8, and 1.0%), which were not prepared experimentally, were calculated by using ANN method. The results obtained with the YSA model were also found to be consistent with the nonlinear variation of the real and imaginary components of complex dielectric function with increasing PANI doping. Hence, suitable PP and PANI mass percentages can be predicted in the production of PP/PANI composites with desired dielectric parameters for various dielectric applications such as capacitor.

Authors and Affiliations

Önder EYECİOĞLU, Mehmet , KILIÇ, Zeynep GÜVEN ÖZDEMİR

Keywords

Related Articles

Prediction of Dielectric Properties of Polypropylene/Polyaniline Composite Films By Artificial Neural Networks Model

In this study, the change of the frequency dependence of the real and imaginary components of the complex dielectric function of the polypropylene (PP) polymer depending on the addition of 0.3%, 0.4%, 0.6% and 0.7% polya...

The Impact of Acoustic Parameters on the Classification of Firearms Using Gunshots

Acoustic analysis is mainly used in material science and human voice. In recent years, many areas such as sound perception, gun and shooter detection, unmanned aerial vehicles have been used in the defense industry. Acti...

Fabrication of Topologically Optimized Parts via Direct 3D Printing

Within the scope of this study, machine codes are generated to fabricate topologically optimized parts directly, conveyed to the design and fabrication pipeline, utilizing 3 dimensional printers employing Fused Depositio...

Design and Numerical Analysis of a Double-Tube Magnetorheological Shock Absorber for Vehicle Seat Suspension Systems

In scissors-type suspension mechanisms of the driver's seats of vehicles such as tractors, trucks and buses, conventional double-tube shock absorbers are often used as dampers due to the length of the course. The damping...

Development of Metal-Porous Silicon Direct Hydrogen Fuel-Cell Production Parameters

Effect of the electrochemical etching (anodization) that is one of the manufacturing process of porous silicon (PS) on the electrical parameters of metal-porous silicon direct hydrogen cell (Metal-PS-DHC) is considerably...

Download PDF file
  • EP ID EP491169
  • DOI 10.29109/gujsc.398275
  • Views 76
  • Downloads 0

How To Cite

Önder EYECİOĞLU, Mehmet, KILIÇ, Zeynep GÜVEN ÖZDEMİR (2018). Prediction of Dielectric Properties of Polypropylene/Polyaniline Composite Films By Artificial Neural Networks Model. Gazi Üniversitesi Fen Bilimleri Dergisi Part C: Tasarım ve Teknoloji, 6(4), 787-802. https://europub.co.uk/articles/-A-491169