Flexible Hybrid Electronics Nanofiber Electrodes with Excellent Stretchability and Highly Stable Electrical Conductivity for Smart Clothing

In this paper, a side-by-side, dual-nozzle electro spinning process was used to prepare a flexible hybrid electronics (FHE) material with excellent stretchable properties. A highly stable electrical conductivity was also imparted to the resulting membrane electrodes using silver nanoparticles (AgNPs) and carbon-based nanomaterials of different structures. The AgNP/carbon-based nanomaterials were coated onto bicomponent polymer nanofibers (composed of polyurethane (PU) and polyvinylidene difluoride (PVDF)) on the nanofiber membrane. The FHE nanofiber electrodes were finally integrated into clothing designed to accurately measure human body sensing signals (e.g., electrocardiography (ECG) and electromyography (EMG) signals). To effectively increase the high electrical conductivity, a polymer-type dispersant (polyisobutylene-b-poly(oxyethylene)- b-polyisobutylene, a triblock copolymer) was used to effectively and stably disperse AgNPs with different particle sizes and carbon- based nanomaterials with different geometric dimensions (e.g., zero-dimensional carbon black, one-dimensional carbon nanotubes, and two-dimensional graphene) through non-covalent adsorption. Moreover, the bicomponent PVDF-PU nanofibers were immersed in a mixed dispersant of AgNPs and carbon-based nanomaterials at low concentrations, and thermal post-treatment was conducted to improve the electrical conductivity. The AgNP/graphene oxide (GO) nanofiber electrode exhibited a continuous phase with a stable material microstructure after 5000 repetitions of 50% tension-tension fatigue testing. The waveform pattern obtained from the proposed AgNP/GO nanofiber electrode was compared with those of traditional ECG and EMG electrodes. The nanofiber web electrode treated with organic/inorganic mixed dispersants and verified via tests of its electrical and fatigue properties was found to be suitable for long-term ECG and EMG monitoring, and it has excellent potential in wearable smart sensors.