2022
DOI: 10.3390/s22155789
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Optimization of Magnetoplasmonic ε-Near-Zero Nanostructures Using a Genetic Algorithm

Abstract: Magnetoplasmonic permittivity-near-zero (ε-near-zero) nanostructures hold promise for novel highly integrated (bio)sensing devices. These platforms merge the high-resolution sensing from the magnetoplasmonic approach with the ε-near-zero-based light-to-plasmon coupling (instead of conventional gratings or bulky prism couplers), providing a way for sensing devices with higher miniaturization levels. However, the applications are mostly hindered by tedious and time-consuming numerical analyses, due to the lack o… Show more

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Cited by 2 publications
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“…Furthermore, computer-aided optimization of the sensor design can be performed with artificial intelligence algorithms, which may not only improve resolution, but also the sensitivity of MO-HMM nanostructures. 167…”
Section: ■ Hmm and Enz For Sensing Applicationsmentioning
confidence: 99%
See 1 more Smart Citation
“…Furthermore, computer-aided optimization of the sensor design can be performed with artificial intelligence algorithms, which may not only improve resolution, but also the sensitivity of MO-HMM nanostructures. 167…”
Section: ■ Hmm and Enz For Sensing Applicationsmentioning
confidence: 99%
“…In comparison to conventional HMM, achieving FOM up to 590, the use of MO-HMM enables a way to obtain highly enhanced resolution for biosensing applications. Furthermore, computer-aided optimization of the sensor design can be performed with artificial intelligence algorithms, which may not only improve resolution, but also the sensitivity of MO-HMM nanostructures …”
Section: Hmm and Enz For Sensing Applicationsmentioning
confidence: 99%