Order Parameter‐Programmed 2D‐to‐3D Morphing in Liquid Crystal Networks

Abstract Programmable deformation control underpins next‐generation intelligent morphing devices. Liquid crystal networks (LCNs) offer exceptional potential due to their inherent anisotropy and multi‐field responsiveness. However, current 3D morphological programming in LCNs lacks decoupled control over deformation direction and magnitude, fundamentally limiting complex shape‐morphing capabilities. In this work, a deformation programming strategy for LCNs based on grayscale polarized ultroviolet (UV) exposure is proposed, where light intensity and polarization direction are used to separately control the order parameter from dichroism S d (0.014‐0.426) and azimuthal angle (0‐π) of LCs, thereby enabling spatially independent regulation of deformation magnitude and direction. By combining a vertically aligned polyimide layer to form a splay configuration, a one‐to‐one mapping between exposure parameters and deformation metrics is established, where a broad curvature range Δ p of LCNs from 0‐0.125 to 0.149‐2.320 cm −1 is obtained. Furthermore, an inverse design algorithm is developed to convert arbitrary 3D surface geometries into 2D exposure maps. Thermally responsive liquid lenses and biomimetic fingerprints validate the broad adaptability and practical feasibility of this strategy in constructing complex functional 3D morphologies. This study presents a universal platform for reversible 3D shaping in LCNs with hundreds‐of‐microns precision, enabling applications in soft robotics, adaptive optics, and bioinspired systems.