0 Datasets
0 Files
Get instant academic access to this publication’s datasets.
Yes. After verification, you can browse and download datasets at no cost. Some premium assets may require author approval.
Files are stored on encrypted storage. Access is restricted to verified users and all downloads are logged.
Yes, message the author after sign-up to request supplementary files or replication code.
Join 50,000+ researchers worldwide. Get instant access to peer-reviewed datasets, advanced analytics, and global collaboration tools.
✓ Immediate verification • ✓ Free institutional access • ✓ Global collaborationJoin our academic network to download verified datasets and collaborate with researchers worldwide.
Get Free AccessMotion tracking is of great importance in a wide range of fields such as automation, robotics, security, sports and entertainment. Here, a self‐powered, single‐electrode‐based triboelectric sensor (TES) is reported to accurately detect the movement of a moving object/body in two dimensions. Based on the coupling of triboelectric effect and electrostatic induction, the movement of an object on the top surface of a polytetrafluoroethylene (PTFE) layer induces changes in the electrical potential of the patterned aluminum electrodes underneath. From the measurements of the output performance (open‐circuit voltage and short‐circuit current), the motion information about the object, such as trajectory, velocity, and acceleration is derived in conformity with the preset values. Moreover, the TES can detect motions of more than one objects moving at the same time. In addition, applications of the TES are demonstrated by using LED illuminations as real‐time indicators to visualize the movement of a sliding object and the walking steps of a person.
Yi Fang, Long Lin, Simiao Niu, Jin Yang, Wenzhuo Wu, Sihong Wang, Qingliang Liao, Yue Zhang, Zhong Lin Wang (2014). Self‐Powered Trajectory, Velocity, and Acceleration Tracking of a Moving Object/Body using a Triboelectric Sensor. , 24(47), DOI: https://doi.org/10.1002/adfm.201402703.
Datasets shared by verified academics with rich metadata and previews.
Authors choose access levels; downloads are logged for transparency.
Students and faculty get instant access after verification.
Type
Article
Year
2014
Authors
9
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.1002/adfm.201402703
Access datasets from 50,000+ researchers worldwide with institutional verification.
Get Free Access