A high-sensitivity and multi-response magnetic nanofiber-aerogel sensor with directionally aligned porous structure based on triple network for interactive human–machine interfaces

Flexible multimodal sensors with a porous structure have attracted tremendous attentions due to their low density, high specific surface area, a wide detection range and satisfied deformability. However, pores disorder and maldistribution issues of these multimodal sensors are major concerns during their sensing response, which often cause poor linearity and unstable sensing characteristics. Herein, a facile and rapid approach was proposed to fabricate a multifunctional magnetic sensor with directionally aligned porous structure based on triple network by combining electrospun nanofibers, bidisperse magnetic particles and sodium alginate/chitosan foam. The electrospun nanofibers were employed as three-dimensional skeletons for the crystallization and vertical growth of ice crystals. Benefiting from the remarkable structure orientation, the homogenized nanofiber-aerogel scaffold possesses excellent flexibility, superior deformation recoverability and biocompatibility. The assembled sensors not only exhibit a high sensitivity (0.40 T−1), rapid response/recovery time and long stability under magnetic stimuli, but also displays satisfied cross-sensitivity, quick response and reliable durability (8000 cycles) in response to external mechanical functions. Importantly, the respective input stimuli could be clearly discriminated via outputting the electrical signals of opposite or different trends. Furthermore, the sensor could be employed as wearable skins to monitor various physiological signals and realize information translation by Morse mode for individuals with disabilities. Additionally, a wearable gesture recognition system with assistance of the deep learning algorithm was testified, with high average recognition accuracy of 99 %. The simple fabrication process and prominent multifunctional characteristics of the proposed sensor endow it with an extensive application prospect in the field of interactive human–machine interfaces.