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The plasmonic nanostructures are widely used to design sensors with improved capabilities. The position of the localized surface plasmon resonance (LSPR) is part of their characteristics and deserves to be specifically studied, according to its importance in sensor tuning, especially for spectroscopic applications. In the visible and near infra-red domain, the LSPR of an array of nano-gold-cylinders is considered as a function of the diameter, height of cylinders and the thickness of chromium adhesion layer and roughness. A numerical experience plan is used to calculate heuristic laws governing the inverse problem and the propagation of uncertainties. Simple linear formulae are deduced from fitting of discrete dipole approximation (DDA) calculations of spectra and a good agreement with various experimental results is found. The size of cylinders can be deduced from a target position of the LSPR and conversely, the approximate position of the LSPR can be simply deduced from the height and diameter of cylinders. The sensitivity coefficients and the propagation of uncertainties on these parameters are evaluated from the fitting of 15500 computations of the DDA model. The case of a grating of nanodisks and of homothetic cylinders is presented and expected trends in the improvement of the fabrication process are proposed.
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http://dx.doi.org/10.1364/OE.21.002245 | DOI Listing |
ACS Sustain Resour Manag
August 2025
Aragón Institute for Engineering Research (I3A), Thermal Engineering and Energy Systems Group, University of Zaragoza, Agustín de Betancourt Building, C/María de Luna 3, Zaragoza 50018, Spain.
Global and local sensitivity analyses are essential for identifying key parameters in life cycle assessment models. However, due to limited information on parameter uncertainty, they are often overlooked. This paper's objective is to address this gap by proposing a methodological framework for defining input sensitivity, for midpoint and end point indicators, and a quantitative approach for determining input uncertainties.
View Article and Find Full Text PDFInd Eng Chem Res
August 2025
School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States.
Pervaporation, combined with other separation processes, can effectively remove water from fermentation product streams, making it highly suitable for purifying alcohols like 2,3-butanediol (BDO). In this study, a dense poly-(vinylidene fluoride) (PVDF) hollow fiber membrane module prototype was fabricated for BDO dehydration, achieving >0.2 LMH total flux and >95% BDO rejection.
View Article and Find Full Text PDFDiagnosis (Berl)
September 2025
Research Division, Instituto Dante Pazzanese de Cardiologia, São Paulo, SP, Brazil.
Objectives: Diagnostic reasoning in clinical medicine is permeated by uncertainty. This study aims to analyze how errors in the estimation of pre-test probability affect the application of Bayesian inference in diagnostic reasoning.
Methods: We examined the propagation of pre-test probability misestimation through Bayes' Theorem, focusing on its interaction with different likelihood ratios and pre-test probabilities.
Sensors (Basel)
August 2025
Politecnico di Milano, Department of Mechanical Engineering, Via Privata Giuseppe La Masa 1, 20156 Milano, Italy.
Reliable estimation of operational modal parameters is essential in structural health monitoring (SHM), particularly when these parameters serve as damage-sensitive features. Modern distributed monitoring systems, often employing digital MEMS accelerometers, must account for timing uncertainties across sensor networks. Clock irregularities can lead to non-deterministic sampling, introducing uncertainty in the identification of modal parameters.
View Article and Find Full Text PDFMaterials (Basel)
August 2025
School of Transportation, Southeast University, Nanjing 210018, China.
Permittivity measurements of concrete materials benefit from the application of high-frequency electromagnetic waves (HF-EMWs), but they still face the problem of being aleatory and exhibit epistemic uncertainty, originating from multi-phase heterogeneous materials and the limited knowledge of HF-EMW propagation. This limitation restricts the precision of non-destructive testing. This study proposes an evidential regression deep network for conducting permittivity measurements with uncertainty quantification.
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