Introduction:
Nature has long been a source of inspiration for material scientists, offering intricate designs and multifunctional properties. In recent years, biomimetic nanofibers have emerged as a promising class of materials for applications in healthcare, environmental sensing, and soft robotics. However, the limitations of conventional polymers in mimicking dynamic biological behavior have driven the search for next-generation materials that can adapt, respond, and evolve under varying stimuli.
Methods:
This study explores the literature about a novel family of stimuli-responsive copolymers synthesized through controlled radical polymerization, incorporating dynamic covalent cross-links and supramolecular motifs. Electrospinning techniques were employed to fabricate ultrafine fibers, simulating extracellular matrix architectures. A suite of characterization methods, including scanning electron microscopy (SEM), differential scanning calorimetry (DSC), and dynamic mechanical analysis (DMA), were used to assess structural fidelity, thermal behavior, and viscoelastic performance.
Results:
Relevant literature points out that the developed nanofibers exhibit significant responsiveness to pH, temperature, and ionic strength, enabling reversible shape transformations and tunable mechanical properties. Notably, fibers embedded with thermoresponsive domains demonstrate up to 60% contraction at mild physiological temperatures (37–42°C), while pH-sensitive segments showed self-healing capabilities under acidic conditions. Comparative analysis revealed a threefold increase in adaptability compared to conventional electrospun scaffolds.
Conclusions:
The integration of intelligent polymer architectures into nanofibrous formats paves the way for highly adaptive materials that closely emulate natural tissue behavior. These findings suggest strong potential for applications in regenerative medicine, wearable electronics, and responsive filtration systems. Future works are expected explore in vivo biocompatibility and long-term stability to advance toward translational applications.
