Flexible MoS2 ‐CNCs/PVDF Piezoelectric Composites With Enhanced Crystalline Phase Transition for Robust Physiological Signal Monitoring

Fecha de publicación: --
Fuente: Journal of applied polymer
Lugar: RESEARCH ARTICLE
This work designs MoS2-CNCs/PVDF piezoelectric composites via ball milling and electrospinning with PVP as a dispersant, optimizes filler dispersion and PVDF's crystalline phase transition, characterizes the composite's structure, mechanical, and piezoelectric properties, and verifies its high-fidelity performance for wearable physiological signal monitoring.


ABSTRACT
Two-dimensional (2D) piezoelectric semiconductors, specifically molybdenum disulfide (MoS2), have emerged as premier candidates for next-generation nanoscale tactile sensors due to their exceptional electron mobility, high polarization rates, and low power consumption. However, the inherent rigidity and structural brittleness of MoS2 hinder its seamless integration into flexible, wearable platforms. Herein, we report a synergistic strategy combining mechanical ball milling and electrospinning to fabricate high-performance MoS2 carbon nanocrystal/polyvinylidene fluoride (MoS2-CNCs/PVDF) nanofibrous membranes on textile substrates. By utilizing polyvinylpyrrolidone (PVP) as a macromolecular surfactant, we achieved superior filler dispersion and optimized interfacial bonding within the polymer matrix. At an optimal PVP concentration of 10%, the composite exhibits a piezoelectric coefficient (d
33) of 34 pC/N—a 1.3-fold increase over pristine PVDF and delivers a peak output voltage of 2.12 V under a 0.5 N load with high linearity (R
2 > 0.93). Furthermore, the hierarchical composite architecture yields robust mechanical properties, including a tensile strength of 19 MPa and 100% elongation at break, effectively overcoming the traditional brittleness of inorganic MoS2 systems. Integrated into elastic textiles, the resulting sensor enables high-fidelity real-time monitoring of physiological signals, including radial pulse, respiratory rhythms, and joint kinematics. This work provides a scalable pathway for health diagnostics and human-machine interaction.