Inverse design of isotropic auxetic metamaterials via a data-driven strategy

times. Building on this mapping, Model III, optimized using a genetic algorithm, achieves an average MSE of just 0.05%, significantly outperforming the original structure (Model I) and a randomly perturbed structure (Model II) with an average MSE of 2.28% and 1.79%, respectively. Experimental validation and finite element analysis further confirm the accuracy of these results, demonstrating the successful realization of isotropic mechanical response designs. This study presented a data-driven inverse design method as a powerful and efficient tool for the precise design of auxetic metamaterials with isotropic mechanical responses. It holds particular promise for applications in flexible wearable devices and tissue engineering, providing a robust foundation for future innovations in these fields.