Abstract
Irregular lattice structures offer the potential to unlock a wider spectrum of properties and innovative functional spaces. The in-plane wall thickness of the lattice, as a critical structural parameter, decisively governs the mechanical performance of irregular lattice structures, yet the current research on in-plane wall thickness optimization remains notably insufficient. Herein, we propose a robust data-driven framework to design novel irregular lattice structures with user-defined Poisson’s ratio and Young’s modulus. This framework involves the creation of a comprehensive dataset of irregular lattice structures, constructed through a randomized strategy that incorporates diverse stretching and bending dominance. On the basis of deformation characteristics of the structures, we analyze the impact of in-plane wall thickness on the mechanical properties of the unit cell. Furthermore, the inverse design process, employing genetic algorithms, effectively and precisely facilitates the generation of irregular lattice structures, thereby achieving customized targets for Young’s modulus and Poisson’s ratio. Specific inverse design cases are validated through the finite element method simulations and uniaxial tensile tests. By spatially assembling two distinct lattice structures, facial patterns were designed to form a “smiling face” and a “surprised face” under compression, demonstrating the capability of the proposed irregular structures in regulating deformation configurations. This research demonstrates its potential for practical applications in material science and engineering.