Cross-evaluation of stiffness measurement methods for hydrogels

Stiffness is a key property for hydrogels, affecting cellular adhesion, motility, and differentiation, the integrity of biomedical implants, and the flexibility of wound coverings. A hydrogel's stiffness is controlled by its synthesis conditions, whether by changing the polymer or crosslinking scheme used, increasing the concentration of polymer, or increasing the extent of crosslinking. However, no universal design scheme for controlling hydrogel stiffnesses has been previously proposed, and comparisons between different studies are limited by inconsistent measurement methods. Here, we used a structural model to make a priori predictions of the stiffness of eighteen poly(vinyl alcohol) hydrogel formulations and compared five independent stiffness measurement methods to establish broadly applicable standards for predicting and measuring the stiffness of hydrogels. Overall stiffness differences between the five measurement methods (tension, compression, shear rheology, macroindentation, and nanoindentation) were small, but each method provided distinct insights, including measurements of Poisson's ratio and viscoelasticity. The measured hydrogel stiffnesses increased with increasing initial polymer volume fractions ( φ 0 ) and decreased with increasing degrees of polymerization between junctions ( N j ), matching fundamental predictions. Strong correlations between swelling and stiffness in hydrogels suggested a mechanism for improving the accuracy of the predictive model. These results suggest that our predictive model is a powerful tool for the rational design of hydrogels with desirable stiffnesses for a variety of biomedical applications. • Predicted stiffness matches measured trends in eighteen hydrogel formulations. • Five independent measurement methods yield equivalent stiffness values. • Measured incompressibility and non-viscoelasticity justifies neo-Hookean model. • Strong swelling-stiffness correlation validates a rubberlike elasticity model.