Origami — the Japanese art of folding — has inspired various engineering applications for several decades due to its ability to manipulate complex shapes. In our study, multi-field actuated self-folding Origami structures are developed with the implementation of two classes of smart materials: relaxor ferroelectric polymers and magneto-active elastomers (MAEs). The chosen relaxor ferroelectric is P(VDF-TrFE-CTFE), a P(VDF)-based terpolymer and the MAE is a PDMS substrate with embedded barium hexaferrite particles. At the macroscale, this study involves the modeling of the large deformation of a bimorph comprising the aforementioned magnetically and electrically actuated materials using a 1D analytical model derived from the equilibrium of a differential element. The large deformation is extracted from curvatures solved at each point for the resulting differential equation of the equilibrium state. On the microscale, this study also considers the nonlinear behavior of the smart materials. The nonlinear dielectric response of the relaxor ferroelectric polymer is captured by an electric field-dependent electrostrictive coefficient derived from a microstructure-based energy balance for the electrostriction of the terpolymer. The energy density function is postulated to be composed of an elastic contribution described by the Arruda-Boyce hyperelastic model and an electric contribution based on dipole-dipole interactions. On the other hand, a magnetic field-dependent torque drives the actuation of the MAEs, which is also dependent on the orientation of the material to the field. The integration of the micro and macro components results in an analytical model of a 1D, multi-layered flat structure that can be numerically solved for displacements under combined fields. The model is compared with well-matching experimental results of a unimorph and a bimorph structure as validation. The experiments measured the tip displacement of the beam under combined fields for a quantitative analysis. The study takes the analysis further by optimizing parameters such as geometry, field strengths, and the combination of active layers for relevant target shapes.

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