Synthesis and Characterization of Liquid-Crystalline Networks: Toward Autonomous Shape-Memory Actuation

In this paper, epoxy-based shape-memory liquid crystalline lightly cross-linked networks (LCN) are synthesized and characterized with a view to the future development of two-way autonomous shape-memory actuators by coupling the LCN with an external epoxy-matrix. Carboxylic acids of different aliphatic chain lengths are used as curing agents for a rigid-rod epoxy-based mesogen. Thermal and liquid-crystalline (LC) properties of the LCN are investigated, through calorimetric and X-ray diffraction analysis on unstretched and stretched samples. Structural and thermomechanical properties are studied by means of tensile and dynamic-mechanical analyses and the shape-memory capabilities are analyzed in terms of actuation strain and stress under partially- and fully constrained thermomechanical procedures. The results possibility to obtain LCN with isotropization temperatures above 100 degrees C, controlled degree of liquid crystallinity, and high actuation stress and strain by simply varying the aliphatic chain length of the curing agent. Moreover, by properly adjusting the programming conditions (stress level), it is possible to optimize and stabilize the actuation performance. In addition, the effects of the liquid-crystalline domains on the network relaxation and their degree of orientation after programming at the different stress levels have been discussed. Overall, proper design of chain length and stress level allows strain actuation to be modulated from low, similar to 60%, to high, similar to 160% strain levels. The results evidence the possibility of finely tuning LCN with controlled and stable actuation protocols by balancing the aliphatic chain length and programming conditions.