In recent years, folding has attracted increasing interest for technological applications. A metric is developed to predict collisions and is used together with the reduced-order model to design self-folding structures that lock themselves into stable desired configurations.įolding and unfolding are one of the most important mechanisms for generating large deformation and motions in nature, with a plethora of examples such as the winged insects 1 and tree leaves 2, 3, 4. An important aspect of self-folding is the management of self-collisions, where different portions of the folding structure contact and then block further folding. A simplified reduced-order model is also developed to rapidly and accurately describe the self-folding physics.
Measurements of the spatial and temporal nature of self-folding structures are in good agreement with the companion finite element simulations.
This is demonstrated via a series of 3D printed structures that respond rapidly to a thermal stimulus and self-fold to specified shapes in controlled shape changing sequences. The time-dependent behavior of each polymer allows the temporal sequencing of activation when the structure is subjected to a uniform temperature. Here we demonstrate sequential self-folding structures realized by thermal activation of spatially-variable patterns that are 3D printed with digital shape memory polymers, which are digital materials with different shape memory behaviors. It finds technological applications including packaging of solar cells and space structures, deployable biomedical devices and self-assembling robots and airbags. Folding is ubiquitous in nature with examples ranging from the formation of cellular components to winged insects.