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Optimization of Processing Technology for Tiebangchui with Zanba Based on CRITIC Combined with Box-Behnken Response Surface Method
Published on: May 12, 2023
Optimization of TiO2, SiO2, and ATH filler loadings in silicone rubber composites using Box-Behnken response surface
Matin Moazami Goudarzi1, Mohsen Najafi2, Mehdi HajiBagherian1
1Department of Polymer Engineering, Faculty of Engineering, Qom University of Technology, P.O. Box 37195-1519, Qom, Iran.
Abstract:
The electrical industry is continually evolving to develop advanced materials for reliable insulation of wires and components in diverse environments. Silicone, recognized for its inherent flexibility and high thermal resistance is a predominant material in this field. The incorporation of various fillers further enhances its performance for specific applications. In this study, aluminum trihydroxide (ATH), titanium dioxide (TiO2), and silicon dioxide (SiO2) were employed as commonly used fillers in silicone insulating composites. Critical processing parameters, including the concentrations of ATH, TiO2, and SiO2, were reviewed using Design Expert software via a Box-Behnken experimental design. Each parameter was examined at three levels: ATH (10, 15, and 20 phr), SiO2 (20, 30, and 40 phr), and TiO2 (20, 30, and 40 phr), selected based on the characteristics of the base silicone polymer and the fillers. The properties of the prepared composites were assessed through tensile tests, contact angle measurements, dielectric strength, hardness tests, and rheological analyses. The experimental results demonstrate that the type and content of fillers significantly influence the material's properties. All formulations met the minimum dielectric strength threshold of 50 kV/mm, confirming electrical suitability. Optimization therefore focused on mechanical and surface properties. It was observed that the highest tensile strength (approximately 4.28 MPa), hardness (around 81 Shore A), and tensile modulus (about 8.67 MPa) were achieved at higher filler loadings. The results indicate that filler type and loading level significantly influenced all measured properties, with optimal formulations identified via regression modelling.
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