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Chemically cross-linked thermoset shape memory polymers (TSMPs) are an important branch of smart materials due to their potentially wide applications in deplorable structures, soft robots, damage self-healing, and 4D printing. Further development and design of TSMP structures call for constitutive models. Although the Arruda–Boyce eight-chain model has been very successful and widely used for entropy-driven TSMPs, recent studies found that some new TSMPs, such as those using enthalpy as the primary driving force, show unit cells different from the eight-chain model. Considering that these new epoxy-based TSMP networks consist of a plenty of four-chain features, this study proposes a four-chain tetrahedron structure as the unit cell of the network to construct the constitutive model. In this model, Gibbs free energy is used to formulate the thermodynamic driving force. Then, by introducing a transition of the molecule deformation mechanism from that dominated by bond stretch to that dominated by bond angle opening, the traditional Langevin chain model is modified. It is found that this model can well capture the dramatic modulus change for the new TSMP in the thermomechanical experiments. Moreover, it shows that the original Treloar four-chain model and Arruda–Boyce eight-chain model underestimate the driving force for the enthalpy-driven TSMPs, and thus cannot well capture the thermomechanical behaviors. It is also found that under certain conditions, our four-chain model produces the same Cauchy stress as the eight-chain model does. This study may help researchers understand the thermomechanical response and design a special category of TSMPs with high recovery stress.

A Mechanism-Based Four-Chain Constitutive Model for Enthalpy-Driven Thermoset Shape Memory Polymers With Finite Deformation