Stochastic Finite Element Analysis Framework for Modelling Electrical Properties of Particle-Modified Polymer...

Area of Science:

• Materials Science
• Polymer Science
• Computational Modeling

Background:

• Polymers offer low cost and weight but have limited mechanical, thermal, and electrical properties compared to other materials.
• Improving polymer performance often involves adding particulate fillers, but the design space is vast and complex.
• Experimental and traditional analytical methods for designing polymer composites are time-consuming, costly, and lack accuracy.

Purpose of the Study:

• To develop and validate a stochastic finite element analysis (FEA) method for predicting the electrical properties of filler-modified polymers.
• To investigate the conductivity, percolation, and piezoresistivity of composites with randomly dispersed filler particles.
• To explore the influence of temperature on the electrical properties of these advanced polymer composites.

Main Methods:

• A stochastic finite element analysis (FEA) framework was developed to model polymer composites.
• The method focused on predicting electrical properties, including conductivity, percolation, and piezoresistivity.
• The study specifically analyzed nano-silver spherical particles in an epoxy polymer matrix, considering temperature effects.

Main Results:

• The developed FEA method successfully predicted the electrical properties of nano-silver modified epoxy polymers.
• The model demonstrated viability in predicting conductivity, percolation thresholds, and piezoresistivity.
• Model predictions showed good agreement with existing data in technical literature, validating the approach.

Conclusions:

• Stochastic finite element analysis offers a powerful and accurate approach for designing polymer composites with tailored electrical properties.
• This computational framework can significantly reduce the time and cost associated with experimental material design.
• The method provides a versatile tool for predicting the behavior of various filler morphologies and operating conditions, including temperature variations.