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Xiaoyuan Ying

Publications and source records attributed to Xiaoyuan Ying.

2 recordsLinked to original sources

Instability-induced bistable shape-morphing kirigami structures

Deployable shape-morphing structures that transform from flat sheets into stable three-dimensional configurations are highly desirable for applications ranging from soft robotics and biomedical devices to adaptive architecture and aerospace systems. Existing kirigami-based morphing systems primarily rely on isotropic deployment, compliant soft materials, or external constraints to maintain deployed shapes, which limits geometric programmability, structural integrity, and applicability in rigid-material systems. Here, we present an inverse design framework for anisotropic bistable kirigami structures that enables programmable shape morphing through controlled geometric frustration and instability-induced deployment. The framework combines a semi-analytical mechanical model with geometry to establish a direct connection between geometric transformation and the underlying energy landscape. We show that instability-induced shape morphing leads to tunable bistability and directional deployment in anisotropic kirigami structures. The results are validated through finite element simulations and experiments, demonstrating stable deployed configurations and programmable anisotropic morphing. The proposed framework further provides a general design strategy that can be integrated with various active actuation systems, enabling broader engineering applications.

cond-mat.soft↗

Inverse design of programmable shape-morphing kirigami structures

Shape-morphing structures have the capability to transform from one state to another, making them highly valuable in engineering applications. In this study, it is propose a two-stage shape-morphing framework inspired by kirigami structures to design structures that can deploy from a compacted state to a prescribed state under certain mechanical stimuli -- although the framework may also be extended to accommodate various physical fields, such as magnetic, thermal, and electric fields. The framework establishes a connection between the geometry and mechanics of kirigami structures. The proposed approach combines the finite element analysis (FEA), genetic algorithm (GA), and an analytical energy-based model to obtain kirigami designs with robustness and efficiency.

cond-mat.soft↗