ZnO Nanowall Network-Based Tactile/Gesture Sensors and Prediction with Machine Learning.

In low-dimensional material systems, augmented physical and chemical properties may be witnessed through a unique morphological evolution. Here, we report the development of an optimized nanowall network of ZnO for the fabrication of a flexible single-electrode triboelectric nanogenerator (STENG)-based tactile and gesture sensors. The chemically grown nanowall network with an adequate pore area endows superior triboelectric output (current ∼0.

PVDF-HFP encapsulated WSnanosheets in droplet-based triboelectric nanogenerators for possible detection of human Na/Kion concentration.

Here we report the liquid-solid interaction in droplet-based triboelectric nanogenerators (TENG) for estimation of human Na/Klevels. The exploitation of PVDF-HFP encapsulated WSas active layer in the droplet-based TENG (DTENG) leads to the generation of electrical signal during the impact of water droplet. Comparison over the control devices indicates that surface quality and dielectric nature of the PVDF-HFP/WScomposite largely dictates the performance of the DTENG.

Flexible triboelectric nanogenerators of Au-g-CN/ZnO hierarchical nanostructures for machine learning enabled body movement detection.

Here we report the development of triboelectric nanogenerator (TENG) based self-powered human motion detector with chemically developed Au-g-CN/ZnO based nanocomposite on common cellulose paper platform. Compared to bare g-CN, the nanocomposite in the form of hierarchical morphology is found to exhibit higher output voltage owing to the contribution of Au and ZnO in increasing the dielectric constant and surface roughness. While generating power ∼3.