Advances in Experimental and Computational Methods for Studying Mechanical Properties of Double Network Hydrogels

Double network (DN) hydrogels have emerged as a transformative class of soft materials, successfully resolving the trade-off between high water content and mechanical robustness. Their exceptional toughness stems from a sacrificial mechanism wherein a rigid network fractures to dissipate energy, while a ductile matrix network maintains structural integrity. Despite progress in synthesis, fully capturing the complex, nonlinear mechanical behaviors of DN gels often requires advanced characterization techniques and even computational modeling. To address this, this review systematically summarizes recent advances in experimental and computational methods for studying the mechanical behavior of DN gels. We discuss experimental techniques ranging from standard macroscopic tests to emerging non-contact methods, alongside computational methods such as molecular dynamics, network simulations, finite element methods and machine learning. The paper concludes by identifying current challenges and outlining future directions for the field.