The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Alveolus-Inspired Active Membrane Sensors for Self-Powered Wearable Chemical Sensing and Breath Analysis
Abstract
Abstract Fossil fuel internal combustion engines generate and release a huge amount of nitrogen dioxide, leading to respiratory and allergic diseases such as asthma, pneumonia, and possibly tuberculosis. Here we develop an alveolus-inspired membrane sensor (AIMS) for self-powered wearable nitrogen dioxide detection and personal physiological assessment. The bionic AIMS exhibits an excellent sensitivity up to 452.44%, a good linearity of 0.976, and superior selectivity under a NO2 concentration of 50 ppm. Furthermore, the AIMS can also be employed to diagnose human breath behaviors for breath analysis. The fundamental sensing mechanism is established using a combination of thermodynamic analysis, finite-element analysis, and phase-field simulations. It is found that the depolarization field inside the sensitive materials plays a crucial role in the self-powered gas-sensing performance. This work not only provides an efficient, low-cost, portable, and environmentally friendly means for active environmental assessment and personal biomonitoring but also provides a deep understanding of the gas-sensing mechanisms.
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Cites
Progress in triboelectric nanogenerators as a new energy technology and self-powered sensors
Wang, Z. L., Chen, J., & Lin, L. (2015) · Energy & Environmental Science · doi:10.1039/c5ee01532d · Cited by 2,174
Self-citationZhu, G., Su, Y., Bai, P., Chen, J., Jing, Q., Yang, W., & Wang, Z. L. (2014) · ACS Nano · doi:10.1021/nn5012732 · Cited by 565
Self-citationTriboelectric Nanogenerator Enabled Body Sensor Network for Self-Powered Human Heart-Rate Monitoring
Lin, Z., Chen, J., Li, X., Zhou, Z., Meng, K., Wei, W., Yang, J., & Wang, Z. L. (2017) · ACS Nano · doi:10.1021/acsnano.7b02975 · Cited by 494
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Cited by
Artificial intelligence biosensors: Challenges and prospects
Jin, X., Liu, C., Xu, T., Su, L., & Zhang, X. (2020) · Biosensors and Bioelectronics · doi:10.1016/j.bios.2020.112412 · Cited by 399
Wang, D., Zhang, D., Guo, J., Hu, Y., Yang, Y., Sun, T., Zhang, H., & Liu, X. (2021) · Nano Energy · doi:10.1016/j.nanoen.2021.106410 · Cited by 359
Manipulating Relative Permittivity for High-Performance Wearable Triboelectric Nanogenerators
Jin, L., Xiao, X., Deng, W., Nashalian, A., He, D., Raveendran, V., Yan, C., Su, H., Chu, X., Yang, T., et al. (2020) · Nano Letters · doi:10.1021/acs.nanolett.0c01987 · Cited by 319
Self-citationWearable Biosensors for Non-Invasive Sweat Diagnostics
Xu, J., Fang, Y., & Chen, J. (2021) · Biosensors · doi:10.3390/bios11080245 · Cited by 208
Self-citationDesign, manufacturing and applications of wearable triboelectric nanogenerators
Wang, H., Han, M., Song, Y., & Zhang, H. (2021) · Nano Energy · doi:10.1016/j.nanoen.2020.105627 · Cited by 179
Metadata
- Authors
- Su, Y., Wang, J., Wang, B., Yang, T., Yang, B., Xie, G., Zhou, Y., Zhang, S., Tai, H., Cai, Z., Chen, G., Jiang, Y., Chen, L.-Q., & Chen, J.
- Venue
- ACS Nano
- Publisher
- American Chemical Society (ACS)
- Published
- 2020-04-09
- Volume
- 14
- Issue
- 5
- Pages
- 6067-6075
- ISSN
- 1936-0851 (ISSN-L)
- 1936-086X
- OpenAlex
- W3016256527
- Cited by
- 351
- References
- 3
- FWCI
- 21.86
- Type
- journal article
- Language
- en
- Open access
- closed
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