As a type of shape-programmable soft materials, hard-magnetic soft materials (HMSMs) exhibit rapid and reversible deformations under applied magnetic fields, showing promise for soft robotics, flexible electronics, and biomedical devices. The realization of various controllable shape transformations is crucial to the rational design of relevant applications.
Many xeric plant leaves exhibit bending and twisting morphology, which may contribute to their important biological and physical functions adapted to drought and desert conditions. Revealing the relationships between various morphologies and functionalities can inspire device designs for meeting increasingly stringent environmental requirements.
Biological tissues with core–shell structures usually exhibit non-uniform curvatures such as toroidal geometry presenting interesting features containing positive, zero, and negative Gaussian curvatures within one system, which give rise to intriguing instability patterns distinct from those observed on uniformly curved surfaces. Such varying curvatures would dramatically affect the growing morphogenesis.
Smart soft materials have gained increasing attention in recent years because of their adaptive behaviors to external multi-physics stimuli, enabling diverse applications across multiple fields. Here, we show programmable wrinkling morphological patterns on liquid crystal network (LCN) bilayers bonded to compliant substrates under thermal load, by tuning the orientation of directors between LCN bilayers. We propose a solid-shell formulation that merges enhanced and natural assumed strain approaches to investigate the pattern formation and morphological transition of LCN bilayers.
Liquid crystal elastomers (LCEs), as a unique class of smart soft materials combining the properties of liquid crystals and hyperelasticity, are capable of rapid, anisotropic, and reversible deformations in response to mechanical, thermal or optical stimuli. Here, we report a hitherto unknown stretching-induced twisting behavior of LCE bilayer strips. Under uniaxial stretching, we reveal that due to the spontaneous mismatch strain arising from interlayer anisotropy, the bilayer strips exhibit notable twisting deformations.
Morphing soft matter, which is capable of changing its shape and function in response to stimuli, has wide-ranging applications in robotics, medicine and biology. Recently, computational models have accelerated its development. Here, we highlight advances and challenges in developing computational techniques, and explore the potential applications enabled by such models.
Yifan Yang, Fan Xu*
Nature Computational Science, 2024, https://doi.org/10.1038/s43588-024-00647-y
Dear Colleagues,
We would like to invite you to submit abstracts and attend the minisymposium titled "10.11 Morphing Matters: Inspiration, Mechanics, Computation, Design, Fabrication, and Applications" in the 2024 SES Annual Techinical Meeting, August 20-23, 2024, Hangzhou, China.
Abstract submissions are due April 1, 2024.
10.11 Morphing Matters: Inspiration, Mechanics, Computation, Design, Fabrication, and Applications
Hard-magnetic soft materials (HMSMs) consisting of an elastomer matrix filled with high remnant magnetic particles can exhibit flexible programmability and rapid shape changing under non-contact activation, showing promising potential applications in soft robotics, biomedical devices and flexible electronics. Precise predictions of large deformations of hard-magnetic soft materials would be a key for relevant applications.
Petals and leaves are usually curled and exhibit intriguing morphology evolution upon growth, which contributes to their important biological functions. To understand the underlying morphoelastic mechanism and to determine the crucial factors that govern the growth-induced instability patterning in curved petals and leaves, we develop an active thin shell model that can describe variable curvatures and spontaneous growth, within the framework of general differential geometry based on curvilinear coordinates and hyperelastic deformation theory.
The physical properties of graphene nanoribbons (GNRs) are closely related to their morphology; meanwhile GNRs can easily slide on surfaces (e.g., superlubricity), which may largely affect the configuration and hence the properties. However, the morphological evolution of GNRs during sliding remain elusive. We explore the intriguing tail swing behavior of GNRs under various sliding configurations on Au substrate. Two distinct modes of tail swing emerge, characterized by regular and irregular swings, depending on the GNR width and initial position relative to the substrate.
