Design and optimization of magnetorheological elastomer (MRE) soft robots require reliable material parameters, yet comparative datasets covering multiple elastomer matrices and magnetic fillers are scarce. In this work, we present a standardized dataset combining mechanical and magnetic properties, density, hardness, and hyperelastic-model parameters for 48 silicone-based formulations (7 neat elastomers and 41 composites) prepared and characterized under the same conditions. Seven commercial silicones (Shore hardness 00-30 to 60A) were filled with carbonyl iron powder (CIP), Fe–Si–Al flakes (SP-3B), or magnetite (Fe \(_3\) O \(_4\) ) at contents of 30 wt% for all silicones and 10–70 wt% for chosen reference silicones. The saturation polarization of the composites increased monotonically with filler content, reaching 1.42 T for the 70 wt% CIP composites (relative permeability up to 3.5). The SP-3B filler provided the strongest mechanical reinforcement, significantly raising the Young’s modulus and stress at 100 % elongation for all investigated silicones. For example for 30 wt% of the filler content the Young’s modulus increases approximately 2.5 to 4 fold, and at the same time loss of stretchability by about 2 to 3 fold is observed. The CIP filler offers the best stiffness–ductility compromise with elongation at break exceeding 300% even at 70 wt%. All stress–strain curves were fitted with first- and second-order Ogden models, and the resulting parameter sets were validated by finite-element simulation. The openly available dataset is intended as a consolidated reference for material selection and modelling of MRE-based soft robots.
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Bernat et al. (2026) studied this question.
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