Researchers have published a standardized materials dataset aimed at making magnetorheological elastomers easier to design into soft robots. The study tested 48 silicone-based formulations, including seven unfilled elastomers and 41 composites containing carbonyl iron, Fe–Si–Al flakes or magnetite.
Filler choice and concentration changed the balance between stiffness, stretchability and magnetic response. At 70% carbonyl-iron content, saturation polarization reached 1.42 tesla. Fe–Si–Al flakes produced the strongest reinforcement: at 30% loading, Young’s modulus rose roughly 2.5- to 4-fold, although stretchability fell about two- to threefold. Carbonyl iron offered the strongest stiffness–ductility compromise, retaining elongation above 300% even at the highest loading.
The work complements efforts to build soft robots that learn and adapt to changing conditions and magnetically responsive soft materials for microscopic robots. Its contribution is practical rather than a finished robot: a common dataset and validated material models that designers can use when selecting materials for future magnetic soft machines.