A systematic understanding of the toughening and self-healing mechanisms of artificial soft tissues is crucial for advancing their robust application in biomedical engineering. However, current models predominantly possess a phenomenological nature, often devoid of micromechanical intricacies and quantitative correlation between microstructure damage and macroscopic energy dissipation. To bridge this gap, we propose a novel energy dissipation mechanism-motivated network model that incorporates three unique physical ingredients with sound theoretical basis for the first time. These innovated features include the bond percolation-mediated network density and stiffness, the damage-induced energy dissipation and stress softening, and the entropic elasticity for the highly stretchable second network. The validity of this model was examined by implementing it within a meshfree peridynamic framework for artificial soft tissues subjected to simple tension and pure shear tests. We quantitatively correlated the dissipation with the network damage to reveal the effects of network density, the breaking stretch dispersion and the stiffness ratio. Our findings highlighted that the inhomogeneity and dispersion of materials properties play significant roles in the controllable progressive damage and dissipation, thereby offering valuable guidance for designing tougher artificial soft tissues. By reactivating the failed network, we further successfully captured the self-healing behaviors of artificial soft tissues. Our work provides an inspiring modeling framework for studying toughening mechanisms of artificial soft tissues.
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