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Optimised layer systems for immunosensors based on the RIFS transducer

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Abstract

Several approaches to direct affinity sensing are currently under investigation. Prominent approaches based on optical transducers are surface plasmon resonance (SPR), grating couplers and interferometers. In this paper, investigations on the reflectometric interference spectroscopy (RIFS), a transducer based on thin dielectric films, are presented and discussed. The main advantages of the RIFS transducer are its ruggedness, the small active area and simple construction. However limits of detection so far achieved are only in the medium range. One way to improve detection is to increase the signal-to-noise ratio (s/n) in the primary signal (i.e. the reflectance spectra of the transducing film). The influence of the s/n-parameter was investigated by systematic variation of measurement parameters in a given system. A linear relationship between baseline noise of the transducer and s/n ratio of the primary signal was found with an offset value of about 1 pm rms. As the s/n value in the primary signal depends strongly on the optical properties of the transducing layer system, several single and two layer systems have been investigated for theoretical and experimental performance. An up to five-fold increase in signal intensity was achieved as compared to conventional single layer systems. In addition the improved layer systems can be prepared on low refractive index substrates (float glass), producing disposable transducers and giving improved optical systems. The experimental results indicate a thickness resolution of as low as 1 pm rms corresponding to protein coverages below 10 pg/mm2. In applications where only moderate detectivity is required, these results offer the possibility for further miniaturisation of the device.

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Brecht, A., Gauglitz, G. Optimised layer systems for immunosensors based on the RIFS transducer. Fresenius J Anal Chem 349, 360–366 (1994). https://doi.org/10.1007/BF00326600

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  • DOI: https://doi.org/10.1007/BF00326600

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