Nano-bio-systems

(version française)

Nano-bio-systems

SPR sensors

Person in charge :

Guy LOUARN (associate professor)

Contributors:

Malak KANSO (Post graduate student)
Tahereh MAKIABADI (Post graduate student)

Summary:

Introduction
How does-it work ?
Formalism and results
Prospects
Publications

Introduction

Surface plasmon resonance (SPR) is a very sensitive technique for determining small refractive index changes at the interface between a metallic layer and a dielectric medium (analyte). This technique is widely used as a detection principle for many sensors that operate in different areas such as gas detection or bio- and chemical-sensing]. SPR has shown great potential for biomolecular interaction study, allowing real time analysis without the use of labeled molecules. SPR is one of the most widely used technologies for biomolecular interaction observations. During the last twenty years, several companies have commercialized SPR sensor equipment. Generally, these equipments were built from an optical system made of a transducer that analyzes the (bio)chemical activity and transfers this information to the optical setup and an electronic system, which allows for data processing. Biological targets are generally transported through a microfluidic system by a buffer fluid or a carried fluid. With SPR sensors, when the transducing media (ligands) react with the target molecules present in the analyte, the refractive index changes and this change is determined by optical interrogation.

In spite of this fact, the SPR is an established technique that has been used to satisfy the recent need for miniaturization and integration. In this manner, new alternative configurations are still being developed by creative engineering. Similar to fluorescence for surface interaction analysis and biosensing, recent developments in optical fibers and waveguiding-based SPR devices will increase the use of SPR.

In this context, surface plasmon resonance curves of an optical fiber based sensor were investigated. From an experimental and theoretical perspective, the response curves were analyzed and discussed.

Schematic illustration of the light path in the optical fiber SPR sensor.

Precisely, such curves were calculated by modeling the analyte/metallic layer interface using a multi-layer system, including the effects of roughness. Then, the experimental response curves observed in solutions with different refractive indices were compared to the simulated curves. Good agreement was obtained with respect to the resonance peak location and the shape of the curves. Consequently, these results enabled us to predict the ideal functioning conditions of the sensor, i.e. the working parameters corresponding to the best sensitivities of detection.

How does it work ?

Formalism and results

The response curves of the optical fiber-based sensor are computed. After, the location of the lowest transmitted power as well as the width of the dip were extracted and compared to the experimental data. To achieve this goal, we developed modeling for the reflectance R of the light in the optical fiber, based on the Fresnel transfer matrix formalism. We calculate the transmission of the sensing fiber by computing the multiple reflexions of the incident ray in the fiber.

A matrix method developed for analysis of thin film optical filters has been used to compute the reflexion coefficients. This part, which is based on the calculation of the light propagation through a multilayer medium is detailed in the publications.

Numerical predictions and experimental values T_min as a function of the refractive index. T_min values correspond to the minimum of the transmitted power (in the inset, typical response curve is presented).

Simulated (straight lines) and experimental (dashed lines) SPR response curves as a function of the wavelength of four refractive indices: a) 1.3335 (─) ; b) 1.3668 (─) ; c) 1.3844 (─) and d) 1.4018 (─).

Note that roughness of the gold surface was directly included into the calculation as a very thin layer to which we associated a thickness d and an effective complex permittivity e_eff. The values of these two parameters were previously determined from AFM images of gold surface: q = 0.51, d = 5.75nm].

Numerical simulations of T_min as a function of d for three values of volume fraction q

Prospects

Generally, biological targets are generally transported through a microfluidic system by a buffer fluid or a carried fluid. The realization of OF-SPR sensors are based on a similar concept, specifically a chemical ligand is fixed to the metallic fiber surface. Then, the analyte flows in the microfluidic channel and the target molecules bind to the ligands, creating a thicker layer that can be sensed by a tiny change in the refractive index.

The most important differences concern the axy-symmetric geometry and the fact that reflexions occur frequently on the optical fiber surface. This complicates the theoretical treatment of the system. An experimental set up and multiphysic modelisations are presently under develpment.

Multiphysic modelisation od the OF-SPR responses : (i) FEM modelisation of the concentration as a function of the laminar flow, (ii) response of the SPR signa as a function of time and analyte oncentration .

Publications

Experimental realization and numerical simulation of wavelength-modulated fibre optic based on surface plasmon resonance, K. Balaa, Malak Kanso, S. Cuenot, T. Minéa, G. Louarn, Senors &. Actuators B, 2006, (Available online 28 December 2006).
Roughness effect on the SPR measurements for an optical fibre configuration: experimental and numerical approaches, Malak Kanso, S. cuenot, G. Louarn, Journal of Optics A : Pure and Applied Optics, 9 (2007) 586–592
Experimental measurements and modelling of the sensitivity of fibre optic sensor based on surface plasmon resonance, M.Kanso, S. cuenot, G. Louarn, Plasmonics, 3 (2008)
Plasmon resonance micro-sensor for droplets analysis, M. Chaigneau, K. Balaa, T. Minea, and G. Louarn soumis à Optic Letters, 32 (2007) 2435-2437