Quantifying Measurement Fluctuations from Stochastic Surface Processes on Sensors with Heterogeneous Sensitivity
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Authors
Charmet, Jerome
Prasad, Abhinav
Thiruvenkathanathan, Pradyumna
Publication Date
2016-06-27Journal Title
Physical Review Applied
ISSN
2331-7019
Publisher
American Physical Society
Volume
5
Number
064016
Language
English
Type
Article
This Version
AM
Metadata
Show full item recordCitation
Charmet, J., Michaels, T., Daly, R., Prasad, A., Thiruvenkathanathan, P., Langley, R., Knowles, T., & et al. (2016). Quantifying Measurement Fluctuations from Stochastic Surface Processes on Sensors with Heterogeneous Sensitivity. Physical Review Applied, 5 (064016)https://doi.org/10.1103/PhysRevApplied.5.064016
Abstract
Recent advances in micro- and nanotechnology have enabled the development of ultrasensitive sensors capable of detecting small numbers of species. In general, however, the response induced by the random adsorption of a small number of objects onto the surface of such sensors results in significant fluctuations due to the heterogeneous sensitivity inherent to many such sensors coupled to statistical fluctuations in the particle number. At present, this issue is addressed by considering either the limit of very large numbers of analytes, where fluctuations vanish, or the converse limit, where the sensor response is governed by individual analytes. Many cases of practical interest, however, fall between these two limits and remain challenging to analyze. Here, we address this limitation by deriving a general theoretical framework for quantifying measurement variations on mechanical resonators resulting from statistical-number fluctuations of analyte species. Our results provide insights into the stochastic processes in the sensing environment and offer opportunities to improve the performance of mechanical-resonator-based sensors. This metric can be used, among others, to aid in the design of robust sensor platforms to reach ultrahigh-resolution measurements using an array of sensors. These concepts, illustrated here in the context of biosensing, are general and can therefore be adapted and extended to other sensors with heterogeneous sensitivity.
Sponsorship
We acknowledge funding from the W. D. Armstrong fund, Biotechnology and Biological Sciences Research Council, Newman Foundation, St. John’s College–University of Cambridge, and European Research Council.
Funder references
BBSRC (BB/J002119/1)
Identifiers
External DOI: https://doi.org/10.1103/PhysRevApplied.5.064016
This record's URL: https://www.repository.cam.ac.uk/handle/1810/256626
Rights
Attribution-NonCommercial 4.0 International, Attribution-NonCommercial 4.0 International, Attribution-NonCommercial 4.0 International
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