Abstract
Hydrogels are soft, water-rich polymer networks whose mechanical behavior governs applications ranging from biomedicine to packed bed processes. In aerogel manufacturing, hydrogel particles represent an intermediate state in which mechanical stability determines scalability and process reliability. However, predictive particle-scale models for deformable matrix-fluid systems remain limited. Biopolymer-based hydrogel particles are investigated under uniaxial compression through monotonic, cyclic, and stress-relaxation experiments at compression rates of 0.1–3.0 mm/s. Apparent stiffness increased strongly with rate, followed by saturation above 0.5 mm/s, where the apparent Young’s modulus became rate independent. Within the elastic regime, the response is reproducible and hysteretic, whereas higher strains induced plastic deformation. Aging over one year led to additional stiffening, indicating ongoing structural evolution. To complement the experiments, a novel discrete-element-method framework based on tetrapod-shaped parcels is introduced. Tetrapods qualitatively represent the 3D polymer network and predominantly carry mechanical loads, while embedded spheres mimic the aqueous phase. Parameters are calibrated using a full-factorial design and Bayesian optimization. Simulations reproduce the force–strain response, apparent elastic properties, and particle deformation. Random packings produce comparable scatter, while stress relaxation and cyclic loading are reproduced qualitatively. The approach advances predictive modeling of deformable particles and provides a basis for solvent exchange and process-scale simulations.