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 AccessThe development of elastic electronic technology has promoted the application of triboelectric nanogenerators (TENGs) in flexible wearable electronics. However, most of the flexible electronics cannot achieve the requirements of being extremely stretchable, transparent, and highly conductive at the same time. Herein, we report a TENG constructed using a double-network polymer ionic conductor sodium alginate/zinc sulfate/poly acrylic-acrylamide (SA–Zn) hydrogel, which exhibited outstanding stretchability (>10,000%), high transparency (>95%), and good conductivity (0.34 S·m–1). The SA–Zn hydrogel TENG (SH-TENG) could harvest energy from typical human movements, such as bending, stretching, and twisting, which could light up 234 green commercial LEDs easily. Additionally, the SH-TENG can be used to prepare a self-powered smart training band sensor for monitoring arm stretching motion. This work may provide an innovative platform for accessing the next generation of sustainable wearable and sports monitoring electronics.
Feifan Sheng, Jia Yi, Shen Shen, Renwei Cheng, Chuan Ning, Liyun Ma, Peng Xiao, Wen Deng, Kai Dong, Zhong Lin Wang (2021). Self-Powered Smart Arm Training Band Sensor Based on Extremely Stretchable Hydrogel Conductors. , 13(37), DOI: https://doi.org/10.1021/acsami.1c12378.
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
2021
Authors
10
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.1021/acsami.1c12378
Access datasets from 50,000+ researchers worldwide with institutional verification.
Get Free Access
