InstaMATiF

Magnetorheological Elastomers (MREs) are smart materials comprising magnetizable particles embedded in an elastomer matrix. They readily respond to the application of a magnetic field, either by exhibiting magneto-induced large deformations (if conditions permit) or by displaying large displacements induced by structural instabilities (that are linked to the magnetic compass effect or to combined magneto-mechanical compressive stresses). In particular, in a system made of a uniform MRE film bonded to a non-magnetic substrate, instabilities can be triggered by mechanical loading, magnetic loading or a combination of both, thus yielding periodic wrinkling (Psarra et al., 2017) or more complex profiles, such as crinkling (Psarra et al., 2019). Such controllable instabilities were demonstrated both experimentally and numerically (Psarra et al., 2017) but remained limited to mainly 2.5D patterns, that is a profile extruded in one direction. As a matter of fact, molding—a standard fabrication technique for elastomers—was employed to fabricate the samples, hence the uniformity of the film, and numerical modeling was restricted to 2D simulations due to computational complexity and cost.By combining the experience of the French team in experiments and theory related to MREs and magneto-mechanical instabilities, as well as the expertise of the German team in computational multi-physics modeling of MREs and in machine-learning techniques, we propose to investigate and exploit experimentally, theoretically and numerically the instabilities inherently present in MRE-based materials and structures. The background of the German team in data-driven modeling and simulation will enable the consortium to develop a data-integrated surrogate model building on the experimental, theoretical and numerical findings in order to predict instability modes at reasonable investments. In particular, we aim at lifting the above-mentioned barriers (i.e., 2.5D patterns and 2D models) and further harness magneto-mechanical instabilities to create, for the first time, reversible on-demand 3D surface patterns that can be controlled remotely via a magnetic field by solving inverse problems using novel surrogate models. Controllable 3D patterns could indeed be obtained by imparting heterogeneous magneto-mechanical properties to an MRE film resting on a passive or MRE substrate.By the end of the project, we expect to compute rapidly the spatially heterogeneous magneto-mechanical properties that need to be imparted to an MRE film bonded to a non-magnetic (or magnetic) substrate to reach a desired 3D pattern and then to fabricate the corresponding system. The specificities of the desired 3D pattern could be motivated by applications in the domain of haptic surfaces (human-machine interactions/reconfigurable braille), morphable structures for adaptive lenses or cell growth studies, as well as in the domain of actuators.