Physical limits to sensing material properties
| Autor: | David K. Lubensky, Di Zhou, Farzan Beroz, Xiaoming Mao |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Medical diagnostic
Science General Physics and Astronomy Thermal fluctuations FOS: Physical sciences Biosensing Techniques Condensed Matter - Soft Condensed Matter Lambda 01 natural sciences Article General Biochemistry Genetics and Molecular Biology 03 medical and health sciences Biopolymers 0103 physical sciences Cell Behavior (q-bio.CB) Computer Science::Networking and Internet Architecture Physics - Biological Physics Statistical physics thermodynamics and nonlinear dynamics lcsh:Science 010306 general physics 030304 developmental biology Theory and computation Physics 0303 health sciences Multidisciplinary Uncertainty General Chemistry Disordered Systems and Neural Networks (cond-mat.dis-nn) Stimuli Responsive Polymers Condensed Matter - Disordered Systems and Neural Networks Elasticity Sensors and biosensors Structural heterogeneity Biological Physics (physics.bio-ph) FOS: Biological sciences Thermodynamics Quantitative Biology - Cell Behavior Soft Condensed Matter (cond-mat.soft) lcsh:Q Atomic physics Material properties |
| Zdroj: | Nature Communications, Vol 11, Iss 1, Pp 1-9 (2020) Nature Communications |
| DOI: | 10.48550/arxiv.1905.02503 |
| Popis: | All materials respond heterogeneously at small scales, which limits what a sensor can learn. Although previous studies have characterized measurement noise arising from thermal fluctuations, the limits imposed by structural heterogeneity have remained unclear. In this paper, we find that the least fractional uncertainty with which a sensor can determine a material constant λ0 of an elastic medium is approximately \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\delta {\lambda }_{0}/{\lambda }_{0} \sim ({\Delta }_{\lambda }^{1/2}/{\lambda }_{0}){(d/a)}^{D/2}{(\xi /a)}^{D/2}$$\end{document}δλ0/λ0~(Δλ1/2/λ0)(d/a)D/2(ξ/a)D/2 for a ≫ d ≫ ξ, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\lambda }_{0}\gg {\Delta }_{\lambda }^{1/2}$$\end{document}λ0≫Δλ1/2, and D > 1, where a is the size of the sensor, d is its spatial resolution, ξ is the correlation length of fluctuations in λ0, Δλ is the local variability of λ0, and D is the dimension of the medium. Our results reveal how one can construct devices capable of sensing near these limits, e.g. for medical diagnostics. We use our theoretical framework to estimate the limits of mechanosensing in a biopolymer network, a sensory process involved in cellular behavior, medical diagnostics, and material fabrication. At small scales, structural heterogeneities limit what a sensor can learn about the properties of a material. Here, the authors quantify these limits and determine the optimal measurement protocols, which depend on both the spatial resolution of the sensor and the number of probes. |
| Databáze: | OpenAIRE |
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