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Paper-based platforms for microbial electrochemical cell-based biosensors: A review.
- Source :
-
Biosensors & Bioelectronics . Nov2021, Vol. 192, pN.PAG-N.PAG. 1p. - Publication Year :
- 2021
-
Abstract
- The development of low-cost analytical devices for on-site water quality monitoring is a critical need, especially for developing countries and remote communities in developed countries with limited resources. Microbial electrochemical cell-based (MXC) biosensors have been quite promising for quantitative and semi-quantitative (often qualitative) measurements of various water quality parameters due to their low cost and simplicity compared to traditional analytical methods. However, conventional MXC biosensors often encounter challenges, such as the slow establishment of biofilms, low sensitivity, and poor recoverability, making them unable to be applied for practical cases. In response, MXC biosensors assembled with paper-based materials demonstrated tremendous potentials to enhance sensitivity and field applicability. Furthermore, the paper-based platforms offer many prominent features, including autonomous liquid transport, rapid bacterial adhesion, lowered resistance, low fabrication cost (<$1 in USD), and eco-friendliness. Therefore, this review aims to summarize the current trend and applications of paper-based MXC biosensors, along with critical discussions on their field applicability. Moreover, future advancements of paper-based MXC biosensors, such as developing a novel paper-based biobatteries, increasing the system performance using an unique biocatalyst, such as yeast, and integrating the biosensor system with other advanced tools, such as machine learning and 3D printing, are highlighted. [Display omitted] • Studies related to paper-based MXC biosensors are summarized and reviewed. • Benefits of using paper-based platforms over traditional materials are listed. • Current applications and challenges of paper-based MXC biosensors are provided. • Field applicability of paper-based MXC biosensors is highlighted. • Opportunities to integrate 3D printing and machine learning are discussed. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 09565663
- Volume :
- 192
- Database :
- Academic Search Index
- Journal :
- Biosensors & Bioelectronics
- Publication Type :
- Academic Journal
- Accession number :
- 152465380
- Full Text :
- https://doi.org/10.1016/j.bios.2021.113485