5. Plasmonic Biosensors

Plasmonic devices consist of nanometer and micrometer sized particles and surfaces, which are comparable in size to many biological substances such as cells, anti-bodies, anti-gens and even DNA. Therefore plasmonic sensors offer a good platform to interface with bio-molecules as the typical decay lengths of the enhanced fields are of the same order as the investigated molecules. The plasmonic structures can be fabricated in bio-compatible materials such as Gold (Au), Silica (SiO_2) and Silicon (Si), which makes them suitable for in-vitro and in-vivo applications. On top of that, different mature types of chemical functionalizations can be applied on these materials in order to make the sensors specific to the desired analyte molecules.

Surface Plasmon Polariton (SPP) sensing

SPP sensing is one of the most widely spread plasmon based commercial platforms (e.g. Biacore) in life sciences. The sensing principle is illustrated in figure 1. The analyte solution flows through a channel which is in contact with a (functionalized) gold surface. A P-polarized beam excites plasmons on the gold surface by SPP coupling in the Kretschmann configuration. Two configurations are typically used: (1) The wavelength is fixed while the angle of incidence is scanned (angular approach); (2) The angle of incidence is fixed while the wavelength is scanned (spectral approach); In both cases, a dip in the reflection spectrum is observed at the angular/spectral position where SPPs are excited. These propagating SPPs are prone to changes in the dielectric environment and as a result an angular/spectral shift will be observed for changes in the analyte solution or binding events at the gold surface. Typically with increasing concentration of the analyte or upon binding events on the gold layer, (local) refractive index is increased, resulting in a shift of the spectral/angular position to larger values. The electric field of the propagating SPP decays exponentially with the distance from the gold surface, with typical decay lengths of a few 100 nanometers. Therefore SPP-based sensors are sensitive to concentration changes in the bulk and to binding events at the gold surface.

SPRsensing
Figure 1: (a) Schematic overview of an SPP sensing experiment. (b) Example of a measurement for an SPP-based sensor showing both intensity and phase based signals in configuration (1).

As shown here, it is possible to measure both the intensity and phase of the SPP resonance (see fig 1 (b)), and the resulting line widths differ tremendously, allowing to reach detection limits which are 2 orders of magnitude smaller for phase-based SPR sensing.

Localized Surface Plasmon Resonance (LSPR) sensing

Localized surface plasmon resonances are highly susceptible to their dielectric environment and show pronounced red-shifts of the plasmon resonance as the refractive index of the surrounding medium is increased. Due to the strong confinement of LSPRs, the field enhancement around the plasmonic structure is limited to the near field, with decay lengths in the order of a few tens of nanometers (depending on the resonance wavelength and the nanostructure itself). Therefore LSPR-based sensors are only sensitive to changes in the immediate environment of the nanoparticles and less sensitive to bulk refractive index changes than SPP-based sensing platforms. The sensor response is largely dominated by “hot-spots”, the regions around the nanostructures where the field enhancements are maximized. In optimizing the sensor performance, it is important to maximize the sensing volume and the contact area with the sensing solution, as these parameters determine the final sensor sensitivity.

LSPRsensing
Figure 2: Schematic overview of an LSPR sensing experiment on a gold nanodisk. The extinction spectra are shown for the bare gold nanodisk (1), the disk functionalization with a self-assembled monolayer (SAM)(2), antibodies coupled to the SAM (3) and antigens captured by the antibodies (4).

Characterization of sensor performance

In this section we introduce the most important parameters that quantify the sensor performance for plasmonic sensors based on refractive index changes. Some of these parameters are inherent to the plasmonic structure, while others show a strong dependence on the surface functionalization and the chemical reactions that take place in (bio-) sensing experiments.

The tunability of plasmon resonances can be exploited in optimizing the sensor performance. The intrinsic properties of the plasmon resonance play a key role in the efficiency of the sensor for practical applications. The geometric design of the plasmon resonator determines the position of hot spots and its accessibility for the analyte solutions. A proper design of the plasmonic structure results in high values for the sensitivity (S): the observed red shift of the plasmon resonance (\Delta \lambda_{res}) per refractive index unit (RIU), which is given in units of nm/RIU.

(1) S = \frac{\Delta \lambda_{res}}{\Delta n}

The sensitivity largely depends on the nanostructure and takes different values for different plasmonic modes. Larger values for S are expected for plasmon resonances at at longer wavelengths. Each plasmonic mode is also characterized by a certain line width (\Gamma) which is defined as the full width at half maximum value of the plasmon line shape. The line width is a measure for the damping of the plasmon resonance, which depends strongly of the nature of the plasmon resonance. Dipolar modes radiate strongly and the resulting line widths are broad while dark higher order modes radiate less and the resulting line widths are much more narrow. As the line width also strongly depends on the resonant wavelength, a \emph{quality factor (Q-factor)} of the resonance is introduced, which is given by the ratio of the resonant wavelength and its width.

(2) Q = \frac{\lambda_{res}}{\Gamma}

The value of the Q-factor determines the line width of the plasmon resonance (relative to its spectral position) and higher Q-factors allow to observe smaller spectral shifts of plasmon resonances with increased accuracy. Therefore in terms of sensing the sensor performance is often expressed in a Figure Of Merit (FOM), which relates the line width to the sensitivity of the sensor.

(3) FOM = \frac{\frac{\Delta \lambda_{res}}{\Delta n}}{\Gamma}

The FOM is in general a good measure for the intrinsic sensor performance, and higher FOM values allow a more accurate determination of the resonance position, which implies that smaller spectral shifts can be observed. The smallest refractive index change (\Delta n) that can be observed with the sensor, which is called the detection limit (DL) and expressed in RIUs.

Surface functionalization

The typical dimensions of plasmonic structures are matched pretty well with the sizes of biological molecules, cells and even DNA, which makes them really useful for biological sensing applications. It is critical to bring the analyte molecules in the vicinity of the plasmonic sensors in order to obtain accurate measurement results. To that extent, chemical functionalization of the plasmonic structures is very important to obtain the best possible interfacing properties between the sensors and the analytes. The typical sample structures used in this thesis are fabricated in gold and silica, which can both be chemically functionalized. Gold surfaces show a high affinity for thiol (SH-groups) while silica and silicon surfaces show a high affinity for silane (Si-O-groups). Both thiol and silane based chemistry can be exploited to form self-assembled monolayers (SAMs) on gold and silicon-based structures with nearly perfect sample coverage. These SAMs can be tailored at will for a specific application: one side is designed to realize the coupling with the sensor surface, while the other can be tailored to couple analyte molecules or antibodies (bio-functionalization). Typically the molecules making up the SAM consist of two functional end-groups and a (long) chain of atoms in between them which can form Van-Der-Waals bonds with the neighboring SAM molecules, resulting in rather densely packed monolayers on the functionalized substrates. For most applications the SAMs are formed upon exposure of the samples to a solution of the SAM molecules which can then self-assemble onto the sample surface.

Other types of plasmonic biosensors

Next to refractive index based plasmonic biosensors the most promising application is surface-enhanced Raman spectroscopy (SERS). In SERS the strong field enhancement of plasmonic resonances is exploited to enhance Raman signals of molecules bound to or in the vicinity of the surface of a nanostructure. The major advantage of SERS is that it is a label-free technique in which the obtained spectrum yields a molecular footprint containing Raman peaks that are specific to the molecule that is detected. Due to the strong local field enhancements near plasmonic structures the sensitivity can go down to the single-molecule level.