A bead random generation method revealing structure-function relation of magnetorheological fluids with arbitrary morphology particles

The structure-function relation is crucial for guiding the preparation of magnetic intelligent materials with arbitrary particle morphologies. However, from the experimental perspective, it is both challenging and inefficient to elucidate this relationship, given the experimental scale and the randomness of particle preparation. Here, we propose a multiscale computational method through the superellipsoid morphology constraint equation and bead random generation method, ensuring the force-magnet coupling simulation for arbitrary particle morphologies with an error of only 2.24 %. The mechanical behaviors, including magnetic-induced stress, dynamic response, and anti-settlement, are systematically calculated and comprehensively analyzed. The derived morphology constraint dimensionless numbers exhibit a strong correlation with particle interactions, thereby revealing the structure-function relation between mechanical behaviors and particle morphologies. This work develops an accurate and efficient computational method for investigating the structure-function relation and provides deep insights into morphology-induced interactions, demonstrating significant potential to accelerate customized material design for next-generation magnetic intelligent materials.