The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Mechanistic Challenges and Advantages of Biosensor Miniaturization into the Nanoscale
Abstract
Over the past few decades, there has been tremendous interest in developing biosensing systems that combine high sensitivity and specificity with rapid sample-to-answer times, portability, low-cost operation, and ease-of-use. Miniaturizing the biosensor dimensions into the nanoscale has been identified as a strategy for addressing the functional requirements of point-of-care and wearable biosensors. However, it is important to consider that decreasing the critical dimensions of biosensing elements impacts the two most important performance metrics of biosensors: limit-of-detection and response time. Miniaturization into the nanoscale enhances signal-to-noise-ratio by increasing the signal density (signal/geometric surface area) and reducing background signals. However, there is a trade-off between the enhanced signal transduction efficiency and the longer time it takes to collect target analytes on sensor surfaces due to the increase in mass transport times. By carefully considering the signal transduction mechanisms and reaction-transport kinetics governing different classes of biosensors, it is possible to develop structure-level and device-level strategies for leveraging miniaturization toward creating biosensors that combine low limit-of-detection with rapid response times.
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Drummond, T. G., Hill, M. G., & Barton, J. K. (2003) · Nature Biotechnology · doi:10.1038/nbt873 · Cited by 2,214
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Gold, L., Ayers, D., Bertino, J., Bock, C., Bock, A., Brody, E. N., Carter, J., Dalby, A. B., Eaton, B. E., Fitzwater, T., et al. (2010) · PLoS ONE · doi:10.1371/journal.pone.0015004 · Cited by 1,754
Non-invasive wearable electrochemical sensors: a review
Bandodkar, A. J., & Wang, J. (2014) · Trends in Biotechnology · doi:10.1016/j.tibtech.2014.04.005 · Cited by 1,247
Wearable Chemical Sensors: Present Challenges and Future Prospects
Bandodkar, A. J., Jeerapan, I., & Wang, J. (2016) · ACS Sensors · doi:10.1021/acssensors.6b00250 · Cited by 778
Kelley, S. O., Mirkin, C. A., Walt, D. R., Ismagilov, R. F., Toner, M., & Sargent, E. H. (2014) · Nature Nanotechnology · doi:10.1038/nnano.2014.261 · Cited by 398
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Metadata
- Authors
- Soleymani, L., & Li, F.
- Venue
- ACS Sensors
- Publisher
- American Chemical Society (ACS)
- Published
- 2017-04-03
- Volume
- 2
- Issue
- 4
- Pages
- 458-467
- ISSN
- 2379-3694 (ISSN-L)
- OpenAlex
- W2601832233
- Cited by
- 177
- References
- 5
- FWCI
- 4.25
- Type
- journal article
- Language
- en
- Open access
- closed
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