3D printing deep-trap hierarchical architecture-based non-contact sensor for multi-direction motion monitoring

Abstract

Non-contact sensors, intelligent electronics that interact with surrounding information with no physical contact, are highly desirable for human-machine interaction. Due to the increased sensing distance and expanded operation scope, it is anticipated the non-contact device exhibiting enhanced electrical output and detection range. Here, freeze-drying assisted 3D printing approach is employed to fabricate cellulose nanofiber (CNF)/MXene-based deep-trap hierarchical architecture for non-contact triboelectric nanogenerators, which exhibit excellent sensing performance for multi-direction motion monitoring. The intermolecular hydrogen bonding between CNF and MXene nanosheets facilitates the formation of a well-dispersed ink with suitable viscoelasticity for 3D printing. The incorporation of MXene nanosheets provides the printed scaffold with more open pores for increased charge generation. Meanwhile, the high electron trapping capability of MXene leads to a weakened electron escaping tendency and an increased decay time, which are beneficial for the device’s non-contact voltage output. Based on the as-prepared non-contact sensor, an all-printed sensing array and a 3D sensor are demonstrated for multi-site and multi-dimension motion trajectories monitoring, indicating its great potential in healthcare, safe navigation, and artificial intelligence.