Stress-memory polymeric filaments for advanced compression therapy

• Published in: Journal of materials chemistry. B, Materials for biology and medicine Materials for biology and medicine, 2017-03, Vol.5 (10), p.1905-1916
• Main Authors: Narayana, Harishkumar, Hu, Jinlian, Kumar, Bipin, Shang, Songmin, Han, Jianping, Liu, Pengqing, Lin, Tan, Ji, FengLong, Zhu, Yong
• Format: Article
• Language: English
• Subjects: Compressing; Fibers; Filaments; Melt spinning; Memory (computers); Strain; Stresses; Thermal properties
• ISSN: 2050-750X; 2050-7518
• DOI: 10.1039/c6tb03354g

Shape memory polymers are stimulus responsive smart materials that can be applied in several forms such as films, fibers, and foams for a wide range of applications. Novel stress-memory behavior at a fiber level is yet to be uncovered, which would be favorable to control stress in the broad horizon of smart materials for numerous functions. In this work, a semi-crystalline segmented polyurethane was synthesized to prepare filaments/fibres and films. A rational experimental design was established and the stress-memory behavior of both the films and filaments was systematically studied for comparison. Tensile stress-memory programming was performed at three strain levels (20%, 40%, and 60%) to record the memory stress response as a function of temperature with time. The characterization of the thermal and mechanical properties of the stress-memory programmed specimens has objectively proven the reason behind the higher stress response in the filaments than in the films. Melt spinning has induced perfect crystallization with ordered polymer packing and enabled maximum memory stress to be retrieved in the filaments. The evolution of memory stress follows a linear trend with an increase in strain and temperature (r = 0.91-1). In addition, pressure related studies were also carried out for smart filament integrative fabrics to realize stress-memory behavior. This unprecedented and novel approach of unveiling the memory behavior specifically at the filament level will enable material scientists to comprehend the fundamental aspects for precise optimization and control of memory stress in smart structures for applications such as compression stockings that require stimuli responsive force.