Prediction of mechanical and thermal properties of particle reinforced hydrogel composites using the structural genome approach

In this paper, the structural genome approach is used for multiscale analyses to predict the mechanical and thermal properties of particle reinforced hydrogel composites. First, the structure genome model of particle reinforced hydrogel composites is created by the random sequential adsorption algorithm. Then the mechanical properties and equivalent thermal conductivity of hydrogel composites are numerically studied by the structural genome approach. The effects of particles with different volume fractions and material properties on their mechanical and thermal properties are investigated. From the simulation results, it can be found that within a certain range of volume fraction, the mechanical properties and equivalent thermal conductivity of hydrogel composites are positively correlated with the volume fractions of particles. We also find that with the increase of the mechanical properties and thermal conductivity of particles, the properties of hydrogel can be improved and eventually reach stabilization. The structural genome approach shows excellent efficiency in multiscale structure analysis. It is a convenient method for the simulation of complex soft material composites.