CoFe-NaYF4:Yb/Er@SMPC derived carbon film: integrated precise stimuli-responsive NIR photothermal sensing and shape-memory performance
Abstract
Photothermal fillers combined with shape-memory polymers (SMPs) enable light-triggered shape memory. The combination of metal particles and biomass-sourced carbon materials has emerged as a significant new research hotspot in the field of photothermal applications and sustainable development. By utilizing biomass-derived carbon films as flexible substrates and encapsulating SMPs, smart textiles based on photothermal-responsive shape-memory polymers can be developed. To date, this area has received limited attention from the research community. Furthermore, near-infrared (NIR) lasers have been widely applied in both remote military laser targeting and activating shape-memory (SM) behavior in polymers due to their relative safety with respect to human tissues and strong penetration capabilities. Nevertheless, the invisibility of NIR cannot be overlooked. Herein, NaYF4:99.5%Yb/0.5%Er can convert 980 nm NIR light into visible light and thermal energy, demonstrating its feasibility as a multifunctional photothermal filler. With the assistance of up-conversion at a low power density of 200 mW cm−2, the position of the laser beam on the SMP surface can be clearly detected, enabling remote targeting of specific deformation-triggering regions. By introducing acrylate polymers into cotton-derived carbon films loaded with CoFe alloy particles, the entangled fiber network provides ample chain mobility for the polymer, leading to the successful fabrication of functionalized light-responsive shape-memory polymers (CNSC-xYb). Upon NIR excitation, the surface temperature at the folded position of CNSC-99.5Yb reaches 127.2 °C within 3 s, and within the range of 0° to 90°, the maximum deformation angle is approximately 72°. This material not only exhibits excellent photothermal responsiveness but also rapid shape-changing ability. These characteristics enable precise triggering of SMPCs using invisible NIR, offering novel design concepts and application prospects for smart textiles, soft robotics, and remotely controllable intelligent material systems.