CUED Publications database

Quantifying Measurement Fluctuations from Stochastic Surface Processes on Sensors with Heterogeneous Sensitivity

Charmet, J and Michaels, TCT and Daly, R and Prasad, A and Thiruvenkathanathan, P and Langley, RS and Knowles, TPJ and Seshia, AA (2016) Quantifying Measurement Fluctuations from Stochastic Surface Processes on Sensors with Heterogeneous Sensitivity. Physical Review Applied, 5.

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Abstract

© 2016 American Physical Society. 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.

Item Type: Article
Subjects: UNSPECIFIED
Divisions: Div C > Applied Mechanics
Div B > Solid State Electronics and Nanoscale Science
Div E > Production Processes
Div C > Materials Engineering
Depositing User: Cron Job
Date Deposited: 17 Jul 2017 19:34
Last Modified: 17 Oct 2017 01:38
DOI: