Prediction of carbon black/carbon nanotube reinforced polydimethylsiloxane properties based on BP neural network

Abstract

Sensory structure integration is the future development trend of flexible robots. At present, polydimethylsiloxane (PDMS) is often used as the main structural material for flexible robots, in which the addition of conductive fillers can achieve the perception of external forces and temperature. Therefore, it is of great research value to explore the roadwriting properties of doped PDMS. This paper focuses on the mechanical properties of carbon black (CB)/carbon nanotubes (CNTs) doped PDMS on the line, aiming to promote the development of flexible robot industry.

Keywords

• polydimethylsiloxane
• carbon black
• Young’s modulus
• tensile test
• neural network