Morphing soft kirigami composite system for the design of flexible deployables and soft-robots

We introduce a new class of thin flexible structures that spontaneously morph from flat shape into a prescribed 3D form. To control the targeted 3D form, two different concepts are coupled: (1) motivated by biological growth, we apply strain mismatch betweem flat composite layers, and (2) we either remove portions of the material or make incisions in a specific pattern according to kirigami. This dramatically increases the number of attainable 3D forms. A unique feature of our morphing system is that it is purely mechanical and fully flexible, which makes it perfect for making packable structures with a predetermined folding pattern. Since the constituent materials are highly elastic, they store the potential energy while packed to actuate the deployment and regaining their original pre-programmed form when released. The central idea behind our specially architectured material is motivated by an example from Nature, more specifically by differential growth occurring in various types of adherent biological tissues leading to strain mismatch and internal stresses. These are relaxed through the formation of 3D deformation modes, especially when the structure is thin. In our system we use a composite of thin flat layers of highly elastic material and apply a membrane strain in individual layers (another distinctive feature of our system) to induce strain mismatch between them. This activates morphing of an originally flat (2D) system into a pre-set 3D form upon the release of pre-stretched layers. We emphasize that our system is not limited to bi-layers, as multiple elastic layers can be manipulated individually and coupled. A wide range of fabrication parameters, such as geometric and material properties, individual stretching modes, their amplitudes, orientations, local coupling (along-the-thickness) and global (surface) distribution of pre-stretch modes, and specifically the use of kirigami concept make our system extremely versatile in the scope of soft morphing structures. To accurately predict the surface morphology, a sound computational model is required. We will combine theoretical (for weakly nonlinear problems) and numerical modelling using FEM (for highly nonlinear problems). In both cases we will develop our own models. For especially complex responses in large deformation regimes, we will employ advanced path-following techniques. These will be especially crucial in exploring the energy landscape of multistable configurations, which are of great interest to us for the use in advanced applications. We will also solve a significantly more difficult problem, where the final 3D form is known and the algorithm has to find the required geometric fabrication parameters. The inverse form finding problem will be based on the concept of generative neural networks; more specifically, the principles of a generative adversarial network. Breakthroughs in our design system will lead to building engineering structures on various length-scales, from meters to micrometers, with great fabrication simplicity. The prove that our concept works we will fabricate a simple pop-up shelter, which is rigid enough to support its own weight and provide protection from the elements, while being able to be erected instantly, as the elastic energy required for deployment is stored during packing. We will specifically use this concept to develop a soft-robotic crawler capable of travelling across granular media and soft-robotic swimmer – both will be made in-plane from one piece of the composite, where the actuation parts will be printed on. By precisely tailoring the functional properties of the layered composite (stretching modes and kirigami incisions), we will fabricate a periodic structure with controllable wavelength and amplitude. Since this structure reminds us of acoustic panels found e.g. in recording music studios we will test this idea for sound dispersion. Both domestic and international collaborations are planned.