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 AccessPower generation from human sweat has attracted great attention due to its potential application in waste energy scavenging. However, the development of methods to generate sufficient electricity from sweat to power electronic devices for health monitoring remains a major challenge. Here, we report a wearable sweat-based electricity generator (SEG), in which the power generation mechanism is based on the redox reaction between sweat and electrodes. Due to the increase in oxygen adsorption, both the output current and power of SEG with single-walled carbon nanotubes modified electrode can be remarkably enhanced by 5.6 and 14.7 times compared to SEG with a nanotube-free electrode, respectively. The SEGs have been first utilized to power a wireless heart-rate sensor for sustainably transmitting heart-rate data to a smart phone. Moreover, self-powered sensing of lactic acid has been achieved by electric signals with the current sensitivity of 11.79 mmol·L–1·mA–1, demonstrating applications in human health care.
Heting Wu, Lin Xu, Yang Wang, Tongtong Zhang, Hainan Zhang, Chris Bowen, Zhong Lin Wang, Ya Yang (2020). Enhanced Power Generation from the Interaction between Sweat and Electrodes for Human Health Monitoring. , 5(12), DOI: https://doi.org/10.1021/acsenergylett.0c01992.
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
2020
Authors
8
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.1021/acsenergylett.0c01992
Access datasets from 50,000+ researchers worldwide with institutional verification.
Get Free Access
