Stretching Training of Microgel-Reinforced Composite Hydrogel for Tunable Strain-Stiffening Property

Achieving tunable strain-stiffening in tough hydrogels via muscle-mimicking training remains a key challenge for nonlinear biomimetic mechanics. Microgel-reinforced composite hydrogels (MR-gels), combine rigid polyelectrolyte microspheres with a soft polyacrylamide matrix, offering an ideal platform for programming strain-stiffening behavior via hierarchical microsphere fracture. Here, we report that physical training controlling stretching amplitude and number of repetitions enables stable and tunable strain-stiffening in MR-gels. Unlike conventional expectations, a single stretch is insufficient, training equilibrium requires approximately 300 cycles. The resulting MR-gel exhibit stable and broadly tunable soft-to-stiff transition (0.4-3.1), strain-stiffening capacity (3.1-17.8), and modulus of the soft (240 to 40 kPa) and stiff (814 to 713 kPa) regimes, matching the nonlinear mechanics of diverse biological mechanicals. Mechanistically, the training mode achieves tunable strain-stiffening by controlling the degree of microgel fracture and entangled polymer chain sliding. At equilibrium, fragmented microgels form an interconnected string-like network via topological entanglements and covalent crosslinks, raising the fatigue threshold from 689.6 to 1269.8 J/m². Furthermore, the trained MR-gel enables full envelopment of a high-speed falling iron ball for effective deceleration and superior impact cushioning. This work establishes a versatile strategy for programming mechanical behavior in soft materials, with broad implications for soft robotics, wearable electronics, and biomedicine.