4D printing of shape memory polymer with continuous carbon fiber

Abstract

AbstractShape memory polymer composites (SMPCs) have gained attention for their shape memory effects and wide-ranging applications. Understanding the bending shape recovery characteristics of 3D printed SMPCs is crucial for optimizing their performance. This study focuses on investigating the influence of different fiber orientations of continuous carbon fiber (CCF) in thermally stimulated SMPC. By controlling printing parameters and fiber orientation during the 3D printing process, we fabricate tailor-made rectangular composite test specimens. These specimens are subjected to controlled bending above the glass transition temperature of the polymer, inducing temporary deformation. The subsequent shape recovery process is carefully captured through high-speed video. Precise measurements of the bending curvature over time are obtained using the row-by-row image processing technique and analyzed. The shape recovery rate, shape recovery ratio, and shape fixity ratio of the test specimens were evaluated as a function of three CCF layout arrangements as well as fiber infill density embedded in Shape Memory Polymer (SMP) test specimens. The results revealed that the addition of CCF in the polymer matrix has a significant impact on shape memory behavior. Vertically aligned CCF in the SMP matrix improves the shape recovery ratio (92.97% compared to 78.77% of the pure SMP sample), while horizontal alignment of CCF ensures maximum shape fixity ratio (91.78% compared to 66.22% of the pure SMP sample). The cross-aligned CCF sample provides good recovery as well as fixity values. Further, it was observed that the horizontal alignment of CCF yields the fastest recovery performance. The outcome confirms that optimizing the fiber orientation enhances shape memory performance. Also, 40% of fiber infill density had greater shape fixity and overall recovery performance when compared to 30% and 50%. These findings have implications for tailored and high-performance SMPCs in biomedical devices, aerospace components, and robotics. Understanding temporal curvature behavior enables optimizing the design of materials with precise control over shape recovery. This research contributes to the design and optimization of SMPCs for diverse applications.