**3. Refractive index sensing using photonic crystal waveguides**

A straight-forward way to to test the possibility of using these band edge fringes to perform biosensing, is to carry out a simple refractive index sensing experiment, for instance using several dilutions of ethanol in DIW. Dilution concentrations are (in mass %): pure DIW, ethanol 2% in DIW, and ethanol 4% in DIW, whose refractive indices at λ ≈ 1550 nm and T = 25ºC are 1.3173, 1.3186, and 1.3200, respectively (García-Rupérez et al., 2010).

For carrying out the RI sensing experiments, a flow cell is required in order to flow the target substances over the chip. In this case, a 2-port flow cell with a fluidic cavity of size 5.5mm x 2mm x 0.5mm (length x width x depth) is placed on the top of the chip. For pumping the liquid passing through the flow cell, an automatic syringe pump in withdrawal mode connected to one of the ports of the flow cell using silicone tubing is used. The liquid is flowed at a rate of 15 μl/min. Tubing from the second port of the flow cell is placed into a vial with the liquid to be flowed over the chip. This configuration is used in order to avoid having to replace the syringe to change the liquid to be flowed: with this configuration, the liquid is drawn from vials, enabling an easier handling of the tubes when manual changing between them is performed. The TE transmission spectrum of the PCW in the vicinity of the guided band edge (shown in Fig. 5) is continuously acquired using a tunable laser with a sweep resolution of 10 pm, and a cubic interpolation is used to increase the wavelength accuracy on the determination of the position of the peak's maximum. Fig. 9 shows the temporal evolution of the position of the maximum of the FP peak located around 1563.3 nm for the different ethanol-DIW dilutions flowed.

Fig. 9. Temporal evolution of the FP peak for the different ethanol-DIW dilutions flowed.

Label-Free Biosensing Using Photonic Crystal Waveguides 247

The transmission spectrum for the TE polarization is obtained for the bio-functionalized PCW when having PBS 0.1x as upper cladding, and is shown in Fig. 11, where the band edge is now located around 1542 nm. A closer look at the spectral area close to the band edge is given in Fig. 11.(b), where sharp peaks appearing in this region are once again

> -62 -60 -58 -56 -54 -52 -50

Fig. 11. (a) Spectrum of the PCW in the region of the band edge when PBS 0.1x is flowed. (b) More detailed view of the transmission spectrum close to the band edge. Transmission peaks in this region are marked with dashed red circles and their approximated wavelength

Fig. 12 shows the temporal evolution of the peak shift for the first four peaks depicted in Fig. 11.(b) (peaks at 1542.1nm, 1543.5nm, 1544.2nm and 1544.7nm) during the whole experiment. The initial baseline is obtained by continuously flowing the PBS 0.1x buffer. Once a stable baseline is achieved, anti-BSA antibody at a concentration of 10 μg/ml in PBS 0.1x solution is flowed over the chip, which will bind to the BSA probes attached to the PCW surface thus inducing a shift in the peak position. The anti-BSA is flowed long enough to achieve a monolayer on the top of the BSA-functionalized chip, as indicated by the saturation in the shift of the PCW response. Then, the flow is switched back to the PBS 0.1x buffer to remove any anti-BSA which has not specifically bound to probes on the surface of the PCW, thus only the net shift due to the binding of the anti-BSA to the BSA probes is obtained. Finally, a control step is done by flowing an anti-digoxigenin (anti-DIG) antibody 15 μg/ml in PBS 0.1x dilution to check that the shift previously obtained for the anti-BSA antibody flow is only due to a specific binding to the BSA probes and not due to absorption or any other mechanism. Because of the low affinity between the anti-DIG and the BSA probes, a very slight peak shift is observed during this flow. Later, PBS 0.1x is flowed again to finish the

One can see from Fig. 12 that the temporal evolution is almost the same for all the tracked peaks, reaching a plateau for the anti-BSA flow, indicating the formation of a monoloayer. Concerning the total shift when the anti-BSA is flowed, it is slightly different for each peak, as shown in Table 2. The shift is higher as we move to peaks closer to the band edge (i.e., from peak #1 to peak #4). This is due to the reduction of the group velocity of the guided mode and was already observed in the 3D-FDTD simulations for RI sensing. However, peak #3 does not follow this trend and shows a wavelength shift smaller than peak #2 (this fact

power (dBm)

1541 1542 1543 1544 1545 1546

1544.2nm

1544.7nm

1545.4nm

1542.1nm

(a) (b)

1543.5nm

wavelength (nm)

observed.


experiment.

will be commented later).

positions are depicted.

power (dBm)

<sup>1525</sup> <sup>1535</sup> <sup>1545</sup> <sup>1555</sup> -65

wavelength (nm)

Fig. 10 shows the relative peak shift for the three ethanol-DIW concentrations used in the experiments, where a linear behavior is observed, with a sensitivity of 118 pm/% calculated with respect to the ethanol concentration. Considering the almost linear RI variation for this ethanol concentration range (Δn ≈ 6.75x10-4/%), a sensitivity to RI variations of S = /n = 174.8 nm/RIU is obtained. This value is 2.2x the value obtained in 3D-FDTD simulations, and this difference can be attributed to the discretization step of the PCW used for the FDTD simulations, which may have lead to a non accurate modelling of the optical field which senses the variation of the refractive index of the cladding. The reason for this high sensitivity value is also the higher interaction with the target analyte due to the reduction of the group velocity in the band edge, where the FP fringes used to sense are located.

Fig. 10. Blue circles depict the wavelength shift of the position of the maximum of the peak for the different ethanol-DIW dilutions. The linear fit of the data is depicted with dashed red line.

We can then use the standard deviation of the peak position for a continuous flow of an ethanol-DIW dilution, which is 0.6 pm, as the noise level, and use it to calculate the theoretical detection limit DL, which is defined as DL = /S. A value as low as DL = 3.5x10-6 RIU is obtained.

#### **4. Antibody sensing using photonic crystal waveguides**

Once the origin of band edges fringes is modeled and the possibility of using them for sensing purposes is checked by performing RI sensing experiments, they are used for labelfree antibody sensing. A different PCW sample (with the same nominal parameters) from another fabrication run is used for this. In order to give specificity to the antibody sensing, the PCW sensing device needs to be bio-functionalized with proper antigen probes which will act as receptors for the target analyte. In this case, anti-BSA (bovine serum albumin) antibody is used for the sensing experiments, so BSA antigen probes need to be immobilized on the surface of the photonic sensor. This bio-functionalization process consists in the activation of the surface of the chip with pure ICPTS (3-isocyanatepropyl triethoxysilane) vapour, the deposition and incubation of BSA antigen 10 μg/ml in PBS 0.1x, and a final blocking step with ovoalbumin protein (OVA) 1% in PBS 0.1x (García-Rupérez et al., 2010). The flow cell and the tubing used for the experiments are also blocked with OVA to avoid the absorption of the flowed molecules.

Fig. 10 shows the relative peak shift for the three ethanol-DIW concentrations used in the experiments, where a linear behavior is observed, with a sensitivity of 118 pm/% calculated with respect to the ethanol concentration. Considering the almost linear RI variation for this ethanol concentration range (Δn ≈ 6.75x10-4/%), a sensitivity to RI variations of S = /n = 174.8 nm/RIU is obtained. This value is 2.2x the value obtained in 3D-FDTD simulations, and this difference can be attributed to the discretization step of the PCW used for the FDTD simulations, which may have lead to a non accurate modelling of the optical field which senses the variation of the refractive index of the cladding. The reason for this high sensitivity value is also the higher interaction with the target analyte due to the reduction of

the group velocity in the band edge, where the FP fringes used to sense are located.

0 1 2 3 4

ethanol concentration in DIW (%)

Fig. 10. Blue circles depict the wavelength shift of the position of the maximum of the peak for the different ethanol-DIW dilutions. The linear fit of the data is depicted with dashed red line.

We can then use the standard deviation of the peak position for a continuous flow of an ethanol-DIW dilution, which is 0.6 pm, as the noise level, and use it to calculate the theoretical detection limit DL, which is defined as DL = /S. A value as low as DL = 3.5x10-6

Once the origin of band edges fringes is modeled and the possibility of using them for sensing purposes is checked by performing RI sensing experiments, they are used for labelfree antibody sensing. A different PCW sample (with the same nominal parameters) from another fabrication run is used for this. In order to give specificity to the antibody sensing, the PCW sensing device needs to be bio-functionalized with proper antigen probes which will act as receptors for the target analyte. In this case, anti-BSA (bovine serum albumin) antibody is used for the sensing experiments, so BSA antigen probes need to be immobilized on the surface of the photonic sensor. This bio-functionalization process consists in the activation of the surface of the chip with pure ICPTS (3-isocyanatepropyl triethoxysilane) vapour, the deposition and incubation of BSA antigen 10 μg/ml in PBS 0.1x, and a final blocking step with ovoalbumin protein (OVA) 1% in PBS 0.1x (García-Rupérez et al., 2010). The flow cell and the tubing used for the experiments are also blocked with OVA to avoid


**4. Antibody sensing using photonic crystal waveguides** 

0

0.2

peak shift (nm)

the absorption of the flowed molecules.

RIU is obtained.

0.4

0.6

The transmission spectrum for the TE polarization is obtained for the bio-functionalized PCW when having PBS 0.1x as upper cladding, and is shown in Fig. 11, where the band edge is now located around 1542 nm. A closer look at the spectral area close to the band edge is given in Fig. 11.(b), where sharp peaks appearing in this region are once again observed.

Fig. 11. (a) Spectrum of the PCW in the region of the band edge when PBS 0.1x is flowed. (b) More detailed view of the transmission spectrum close to the band edge. Transmission peaks in this region are marked with dashed red circles and their approximated wavelength positions are depicted.

Fig. 12 shows the temporal evolution of the peak shift for the first four peaks depicted in Fig. 11.(b) (peaks at 1542.1nm, 1543.5nm, 1544.2nm and 1544.7nm) during the whole experiment. The initial baseline is obtained by continuously flowing the PBS 0.1x buffer. Once a stable baseline is achieved, anti-BSA antibody at a concentration of 10 μg/ml in PBS 0.1x solution is flowed over the chip, which will bind to the BSA probes attached to the PCW surface thus inducing a shift in the peak position. The anti-BSA is flowed long enough to achieve a monolayer on the top of the BSA-functionalized chip, as indicated by the saturation in the shift of the PCW response. Then, the flow is switched back to the PBS 0.1x buffer to remove any anti-BSA which has not specifically bound to probes on the surface of the PCW, thus only the net shift due to the binding of the anti-BSA to the BSA probes is obtained. Finally, a control step is done by flowing an anti-digoxigenin (anti-DIG) antibody 15 μg/ml in PBS 0.1x dilution to check that the shift previously obtained for the anti-BSA antibody flow is only due to a specific binding to the BSA probes and not due to absorption or any other mechanism. Because of the low affinity between the anti-DIG and the BSA probes, a very slight peak shift is observed during this flow. Later, PBS 0.1x is flowed again to finish the experiment.

One can see from Fig. 12 that the temporal evolution is almost the same for all the tracked peaks, reaching a plateau for the anti-BSA flow, indicating the formation of a monoloayer. Concerning the total shift when the anti-BSA is flowed, it is slightly different for each peak, as shown in Table 2. The shift is higher as we move to peaks closer to the band edge (i.e., from peak #1 to peak #4). This is due to the reduction of the group velocity of the guided mode and was already observed in the 3D-FDTD simulations for RI sensing. However, peak #3 does not follow this trend and shows a wavelength shift smaller than peak #2 (this fact will be commented later).

Label-Free Biosensing Using Photonic Crystal Waveguides 249

peak. A surface mass density detection limit of <2.1 pg/mm2 is obtained from the

The total mass detection limit can also be obtained from the surface mass density detection limit. If the active region of the PCW is considered for the calculations, since it is where the optical field is confined and where the interaction with the target anti-BSA is actually taking place (around two-three rows of holes at each side of the linear defect, which is around 100 μm2 considering the internal surface of the holes too), a total mass detection limit of ~0.2 fg

Concerning the improvement because of the reduction of the group velocity, Table 2 shows how calculated values for the sensitivity and the detection limit slightly improve as we move closer to the band edge (peak #3 is the only which does not follow this trend and also has a higher noise level, suggesting that it has a poorer quality than the other peaks used in the experiments), although only a 10% improvement is obtained when moving from peak #1 to #4. This is the same increase that was predicted by the 3D-FDTD simulations when taking

The high sensitivity values which are achieved when working in the wavelength region close to the band edge of the PCW, together with the device's small footprint, make it

For label-free DNA sensing, the experimental protocol is similar to the one previously described for antibody sensing, but now the goal of the experiment is to detect DNA hybridization events occurring on the sensor surface, so single DNA strands (ssDNA) need to be immobilized on the PCW. To do so, the chip's surface is still activated with pure ICPTS as described for the antiBSA sensing in the previous section, then an intermediate layer of streptavidin is deposited on the chip (a concentration of 0.1 mg/ml in 0.1x PBS is used), and finally biotinylated ssDNA probes 10 μM in PBS 0.1x are incubated on the sample, which will bind to the streptavidin layer thanks to the high affinity between the streptavidin and the biotin molecules (Toccafondo et al., 2010). Fig. 13 shows the TE transmission spectrum of the PCW with a PBS 0.1x upper cladding, where FP fringes are shown. In this case, the peak marked with dashed red line has been used for sensing. Fig. 14 shows the steps to be carried out in the experiment and Fig. 15 shows the temporal evolution of the peak position for the different solutions flowed. First of all PBS 0.1x is flowed to obtain the baseline of the measurement. Then a solution containing the complementary ssDNA to that immobilized on the chip, with a concentration of 0.5 μM, is flowed. Binding of the complementary DNA is effectively shown, which induces a shift in the peak position of ΔλDNA = 47.1 pm. The noise level in this experiment is estimated to be σ = 1.865 pm, thus giving an estimated

The strand-end of the complementary ssDNA chosen for this experiment is marked with digoxigenin, in order to allow to perform a control step and confirm the hybridization events. Therefore, after the complementary ssDNA is detected, anti-DIG 10ppm, which has a high affinity with DIG, is flowed. Its binding to the DIG marker of the target ssDNA causes a permanent shift in the peak position of 0.246 nm, which confirms the specific

into account only the four peaks closest to the band edge.

suitable for the detection of very small amounts of analyte.

**5. DNA sensing using photonic crystal waveguides** 

detection limit of 19.8nM for ssDNA hybridization detection.

binding of the target DIG-marked ssDNA on the chip.

calculations.

is obtained.

Fig. 12. Wavelength shift vs time for the different solutions flowed in the experiment. Each line (color and style identified in the legend) correspond to the relative shift of each tracked peak respect its initial wavelength position. The time instants when the flowed solution is switched are depicted in the figure.

The surface density for a close-packed anti-BSA monolayer when considering a 100% binding efficiency is ρanti-BSA = 1.7 ng/mm2, which is calculated from the molecular mass and the size of the anti-BSA molecule (as described in (Barrios et al., 2008)), and will give us an upper limit for the detection limit of the device (in the real situation there is no close-pack monolayer as binding efficiency is below 100%). The sensitivity for the anti-BSA detection is given by Santi-BSA = Δλanti-BSA/ρanti-BSA; calculated values for each peak are shown in Table 2.


Table 2. Parameters characterizing the performance of the FP resonances used for the sensing experiments.

The noise level values obtained in the tracking of each peak, which correspond to the standard deviation of the peak position (σ) for the stable PBS 0.1x cycle flowed after the anti-BSA, are shown in Table 2. It can be seen that the noise level is very low (σ = 1.5pm), except for peak #3, for which the noise level is twice this value (σ = 3.1pm). With these noise values and the sensitivities previously calculated for each peak, the surface mass density detection limits (given by DLanti-BSA = σPBS/Santi-BSA) are calculated, which are shown in Table 2 for each

PBS 0.1x

anti-BSA 10g/ml

anti-DIG 15g/ml

0 20 40 60 80 100 120 140

peak 1 (1542.1nm) peak 2 (1543.5nm) peak 3 (1544.2nm) peak 4 (1544.7nm)

PBS 0.1x

time (min)

Fig. 12. Wavelength shift vs time for the different solutions flowed in the experiment. Each line (color and style identified in the legend) correspond to the relative shift of each tracked peak respect its initial wavelength position. The time instants when the flowed solution is

The surface density for a close-packed anti-BSA monolayer when considering a 100% binding efficiency is ρanti-BSA = 1.7 ng/mm2, which is calculated from the molecular mass and the size of the anti-BSA molecule (as described in (Barrios et al., 2008)), and will give us an upper limit for the detection limit of the device (in the real situation there is no close-pack monolayer as binding efficiency is below 100%). The sensitivity for the anti-BSA detection is given by Santi-BSA = Δλanti-BSA/ρanti-BSA; calculated values for each peak are shown in Table 2.

#1 1542.128 1.123 0.661 1.5 2.3 0.23 0.114 #2 1543.471 1.17 0.688 1.5 2.2 0.22 0.108 #3 1544.235 1.142 0.672 3.1 4.6 0.46 0.128 #4 1544.75 1.2 0.706 1.5 2.1 0.21 0.1

Table 2. Parameters characterizing the performance of the FP resonances used for the

The noise level values obtained in the tracking of each peak, which correspond to the standard deviation of the peak position (σ) for the stable PBS 0.1x cycle flowed after the anti-BSA, are shown in Table 2. It can be seen that the noise level is very low (σ = 1.5pm), except for peak #3, for which the noise level is twice this value (σ = 3.1pm). With these noise values and the sensitivities previously calculated for each peak, the surface mass density detection limits (given by DLanti-BSA = σPBS/Santi-BSA) are calculated, which are shown in Table 2 for each

**σPBS (pm)** **DLanti-BSA (pg/mm2)**  **DLanti-BSA (fg)** 

**Δλanti-DIG (nm)** 

**Santi-BSA (nm/ng/mm2)** 


switched are depicted in the figure.

**Peak** 

**λinitial (nm)** 

sensing experiments.

0

PBS 0.1x

**Δλanti-BSA (nm)** 

0.2

0.4

0.6

peak shift (nm)

0.8

1

1.2

1.4

peak. A surface mass density detection limit of <2.1 pg/mm2 is obtained from the calculations.

The total mass detection limit can also be obtained from the surface mass density detection limit. If the active region of the PCW is considered for the calculations, since it is where the optical field is confined and where the interaction with the target anti-BSA is actually taking place (around two-three rows of holes at each side of the linear defect, which is around 100 μm2 considering the internal surface of the holes too), a total mass detection limit of ~0.2 fg is obtained.

Concerning the improvement because of the reduction of the group velocity, Table 2 shows how calculated values for the sensitivity and the detection limit slightly improve as we move closer to the band edge (peak #3 is the only which does not follow this trend and also has a higher noise level, suggesting that it has a poorer quality than the other peaks used in the experiments), although only a 10% improvement is obtained when moving from peak #1 to #4. This is the same increase that was predicted by the 3D-FDTD simulations when taking into account only the four peaks closest to the band edge.

The high sensitivity values which are achieved when working in the wavelength region close to the band edge of the PCW, together with the device's small footprint, make it suitable for the detection of very small amounts of analyte.
