ANN approaches to determine the dielectric strength improvement of MgO based low density polyethylene nanocomposite

Abstract

This paper presents the modification occurred to the dielectric strength feature of low density polyethylene compounded with nano magnesia (LDPE/MgO). MgO nanoparticles were prepared using sol–gel technique, MgO filler surface was functionalized to improve the interfacial bonding. Specimen’s groups of composites with different filler concentrations were fabricated by mix blend method. Samples exposed to various salinity media by immersion, dielectric strength test was applied on each set according to relevant ASTM standard with identical testing technique. The results were statistically processed then compared to the pristine material. Tests results utilized to learn Artificial Neural Network in order to acquire the value of dielectric strength of compounds having similar composition but containing different doping amounts or influenced with various salinity level media. The dielectric strength is enhanced by the addition of MgO nanofiller. From the investigation of the obtained results, it is concluded that additives of 1.4% filler concentration by weight is the optimum MgO content for LDPE/MgO nanofiller material. We think that this paper may promote a good researching methodology that gather both empirical work and numerical tools in this field.