Multivariate analysis applied in biosensing greatly improves analytical performance by extracting relevant information or bypassing confounding factors such as nonlinear responses or experimental errors and noise. Plasmonic sensors based on various light coupling mechanisms have shown impressive performance in biosensing by detecting dielectric changes with high sensitivity. In this study, gold nanodiscs are used as metasurface in a Kretschmann setup, and a variety of features from the reflectance curve are used by machine learning to improve sensing performance.
View Article and Find Full Text PDFThis work demonstrates a novel strategy to improve the sensing performance of a prism-coupled surface plasmon resonance system by Gaussian beam shaping and multivariate data analysis. The propagation of the beam along the optical system has been studied using the Gaussian beam approximation to design the incident beam such that the beam waist is aligned precisely and that stability is assured at the metal-dielectric interface. This renders a collimated incident beam, hence least angular dispersion, yielding a stronger and sharper plasmonic resonance.
View Article and Find Full Text PDFLow cost, easy to use cell viability tests are needed in the pharmaceutical, biomaterial, and environmental industries to measure adverse cellular effects. We present a new methodology to track cell death with high resolution. Adherent cells commonly detach from the surface when they die, but some toxic compounds promote cell adhesion.
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