Hampel, B and Liu, B and Nording, F and Ostermann, J and Struszewski, P and Langfahl-Klabes, J and Bieler, M and Bosse, H and Güttler, B and Lemmens, P and Schilling, M and Tutsch, R (2018) Approach to determine measurement uncertainty in complex nanosystems with multiparametric dependencies and multivariate output quantities. Measurement Science and Technology, 29 (3). 035003. ISSN 0957-0233
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Abstract
In many cases, the determination of the measurement uncertainty of complex nanosystems provides unexpected challenges. This is in particular true for complex systems with many degrees of freedom, i.e. nanosystems with multiparametric dependencies and multivariate output quantities. The aim of this paper is to address specific questions arising during the uncertainty calculation of such systems. This includes the division of the measurement system into subsystems and the distinction between systematic and statistical influences. We demonstrate that, even if the physical systems under investigation are very different, the corresponding uncertainty calculation can always be realized in a similar manner. This is exemplarily shown in detail for two experiments, namely magnetic nanosensors and ultrafast electro-optical sampling of complex time-domain signals. For these examples the approach for uncertainty calculation following the guide to the expression of uncertainty in measurement (GUM) is explained, in which correlations between multivariate output quantities are captured. To illustate the versatility of the proposed approach, its application to other experiments, namely nanometrological instruments for terahertz microscopy, dimensional scanning probe microscopy, and measurement of concentration of molecules using surface enhanced Raman scattering, is shortly discussed in the appendix. We believe that the proposed approach provides a simple but comprehensive orientation for uncertainty calculation in the discussed measurement scenarios and can also be applied to similar or related situations.
Item Type: | Article |
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Subjects: | Open Archive Press > Computer Science |
Depositing User: | Unnamed user with email support@openarchivepress.com |
Date Deposited: | 10 Jul 2023 05:03 |
Last Modified: | 21 Mar 2024 04:32 |
URI: | http://library.2pressrelease.co.in/id/eprint/1732 |