Size-selective analyte detection with a Young interferometer sensor using multiple wavelengths

We present a method to discriminate between analytes based on their size using multiple wavelengths in a Young interferometer. We measured the response of two wavelengths when adding 85 nm beads (representing specific binding), protein A (representing non-specific binding) and D-glucose (inducing a bulk change) to our sensor. Next, the measurements are analysed using a approach based on theoretical analysis, and a ratio-based analysis approach to discriminate between bulk changes and the binding of the different sized substances. Moreover, we were able to discriminate binding of 85 nm beads from binding of protein A (~2 nm) in a blind experiment using the ratio-based approach. This can for example be used to discriminate specific analyte binding of larger particles from nonspecific binding of smaller particles. Therefore, we believe that by adding size-selectivity we can strongly improve the performance of the Young interferometer sensor and integrated optical interferometric sensors in general. ©2016 Optical Society of America OCIS codes: (120.3180) Interferometry; (130.0130) Integrated optics; (130.6010) Sensors. References and links 1. K. Cottier, M. Wiki, G. Voirin, H. Gao, and R. E. Kunz, “Label-free highly sensitive detection of (small) molecules by wavelength interrogation of integrated optical chips,” Sens. Actuators B Chem. 91(1-3), 241–251 (2003). 2. G. D. Kim, G. S. Son, H. S. Lee, K. D. Kim, and S. S. Lee, “Integrated photonic glucose biosensor using a vertically coupled microring resonator in polymers,” Opt. Commun. 281(18), 4644–4647 (2008). 3. M. Iqbal, M. A. Gleeson, B. Spaugh, F. Tybor, W. G. Gunn, M. Hochberg, T. Baehr-Jones, R. C. Bailey, and L. C. Gunn, “Label-free biosensor arrays based on silicon ring resonators and high-speed optical scanning instrumentation,” IEEE J. Sel. Top. Quantum Electron. 16(3), 654–661 (2010). 4. H. Zhu, I. M. White, J. D. Suter, and X. Fan, “Phage-based label-free biomolecule detection in an opto-fluidic ring resonator,” Biosens. Bioelectron. 24(3), 461–466 (2008). 5. N. Skivesen, A. Têtu, M. Kristensen, J. Kjems, L. H. Frandsen, and P. I. Borel, “Photonic-crystal waveguide biosensor,” Opt. Express 15(6), 3169–3176 (2007). 6. S. C. Buswell, V. A. Wright, J. M. Buriak, V. Van, and S. Evoy, “Specific detection of proteins using photonic crystal waveguides,” Opt. Express 16(20), 15949–15957 (2008). 7. A. Brandenburg, R. Krauter, C. Künzel, M. Stefan, and H. Schulte, “Interferometric sensor for detection of surface-bound bioreactions,” Appl. Opt. 39(34), 6396–6405 (2000). 8. C. Stamm, R. Dangel, and W. Lukosz, “Biosensing with the integrated-optical difference interferometer: dualwavelength operation,” Opt. Commun. 153(4-6), 347–359 (1998). 9. K. Schmitt, B. Schirmer, C. Hoffmann, A. Brandenburg, and P. Meyrueis, “Interferometric biosensor based on planar optical waveguide sensor chips for label-free detection of surface bound bioreactions,” Biosens. Bioelectron. 22(11), 2591–2597 (2007). 10. A. Ymeti, J. S. Kanger, R. Wijn, P. V. Lambeck, and J. Greve, “Development of a multichannel integrated interferometer immunosensor,” Sens. Actuators B Chem. 83(1-3), 1–7 (2002). #257853 Received 5 Feb 2016; revised 14 Mar 2016; accepted 15 Mar 2016; published 12 Apr 2016 © 2016 OSA 18 Apr 2016 | Vol. 24, No. 8 | DOI:10.1364/OE.24.008594 | OPTICS EXPRESS 8594 11. R. G. Heideman and P. V. Lambeck, “Remote opto-chemical sensing with extreme sensitivity: design, fabrication and performance of a pigtailed integrated optical phase-modulated Mach–Zehnder interferometer system,” Sens. Actuators B Chem. 61(1-3), 100–127 (1999). 12. C. Worth, B. B. Goldberg, M. Ruane, and M. S. Unlu, “Surface desensitization of polarimetric waveguide interferometers,” IEEE J. Sel. Top. Quantum Electron. 7(6), 874–877 (2001). 13. G. H. Cross, A. A. Reeves, S. Brand, J. F. Popplewell, L. L. Peel, M. J. Swann, and N. J. Freeman, “A new quantitative optical biosensor for protein characterisation,” Biosens. Bioelectron. 19(4), 383–390 (2003). 14. R. A. Abram and S. Brand, “Some theory of a dual-polarization interferometer for sensor applications,” J. Phys. D Appl. Phys. 48(12), 125101 (2015). 15. H. K. P. Mulder, A. Ymeti, V. Subramaniam, and J. S. Kanger, “Size-selective detection in integrated optical interferometric biosensors,” Opt. Express 20(19), 20934–20950 (2012). 16. P. Kozma, F. Kehl, E. Ehrentreich-Förster, C. Stamm, and F. F. Bier, “Integrated planar optical waveguide interferometer biosensors: a comparative review,” Biosens. Bioelectron. 58, 287–307 (2014). 17. S. Ohnishi, M. Murata, and M. Hato, “Correlation between surface morphology and surface forces of protein A adsorbed on mica,” Biophys. J. 74(1), 455–465 (1998). 18. M. C. Coen, R. Lehmann, P. Gröning, M. Bielmann, C. Galli, and L. Schlapbach, “Adsorption and bioactivity of protein A on silicon surfaces studied by AFM and XPS,” J. Colloid Interface Sci. 233(2), 180–189 (2001).


Introduction
Integrated optical (IO) sensors are demonstrated to be a good analysis and detection tool for biosensing, mainly because of their high sensitivity, and their ability to measure real-time and label-free.Examples of IO sensors are grating couplers [1], resonant optical microcavity sensors [2][3][4], photonic crystal waveguide sensors [5,6] and interferometric sensors [7][8][9][10][11].Interferometric biosensors use the evanescent field to detect refractive index (RI) changes induced by analyte binding.Extremely high RI sensitivities (~10 −8 refractive index units (RIU)) are reported with interferometric sensors like the Mach-Zehnder interferometer [11] and the Young interferometer (YI) [9,10].However, it is often not possible to fully use the high sensitivity capabilities of the sensor, because any RI change within the evanescent field will contribute to the measured signal.Next to the specific signal arising from specific binding of the analyte, signals originate from non-specific bound particles and RI changes in the fluid covering the waveguide (bulk).To discriminate specific binding from non-specific binding, selective chemical binding techniques are used in combination with washing steps.Differential measurements are used to cancel out bulk changes.Nevertheless, successful application of IO biosensors is still hampered by non-specificity due to bulk effects or nonspecific adhesion.Therefore, a method was developed to reduce the contribution of nonspecific binding to the measured signal [12].The response to non-specific binding was reduced by a factor of hundred or more by tuning the evanescent fields of two different polarization modes such that the first 20-30 nm of the evanescent field were desensitized to reduce the contribution of non-specific binding.However, any RI change in this layer cannot be detected, resulting also in a reduction of the contribution due to specific binding.Moreover, a dual wavelength operation of an IO difference interferometer was used to distinguish binding of molecules from bulk changes or temperature changes [8].Alternatively, dual polarization interferometry can be used to determine both the thickness and density (RI) of an adlayer [13,14].Finally, we presented a theoretical description of a method called sizeselective detection which can be used to discriminate between RI changes from binding of different sized particles and bulk changes (e.g.due to temperature changes) simultaneously [15].Our theoretical analysis showed that it is possible to determine RI changes from multiple layers above the surface waveguide by measuring RI changes in the evanescent field at multiple wavelengths.Here, we present the experimental realisation of this theoretical analysis.We also present a new, more pragmatic, analysis approach which can be used to discriminate binding of particles from bulk changes and distinguish binding between different sized particles.

Young interferometer with multiple wavelengths
For the general theory of the working of the YI and how it can be used to determine multiple RI changes based on measurements with multiple wavelengths we refer to our theoretical article (Mulder et al. 2012).That article also showed that adding size-selectivity negatively affects the precision of the measured RI change.However, using three wavelengths to discriminate between RI changes at three different layers within the evanescent field and assuming a phase precision of 10 −4 fringes and current waveguide specifications, the retained theoretical sensitivity is 1x10 −6 RIU corresponding to 0.8 pg/mm 2 , which is still comparable to the detection limits of other existing methods [16].In the measurements shown in this contribution we discriminate between two substances of different sizes inducing a RI change by measuring the effective refractive index change eff N Δ at two wavelengths (457 and 660 nm).Measurements with three wavelengths also showed that we could discriminate between three substances (see Appendix C), however results of n Δ became very noise because of enhancement of artefacts due to boundary effects of the shifting interference pattern (see Noise, drift and artefacts in measurements).For a successful application of these analysis approaches used to determine three independent n Δ 's, artefacts and drift in eff N Δ should be reduced significantly.All the experimental details about the setup are given in Appendix A.

Measurement protocol
When a substance (with a different RI than the initial solution) is added to the evanescent field in the sensing window, this results in a RI change n Δ resulting in a eff N Δ .This eff N Δ is determined by reading out the ϕ Δ (in fringes) and multiplying it by the wavelength of the light source and dividing it by the sensing window length of the chip.This is done for the three wavelengths such that a eff N Δ is determined for each wavelength.The substances that we measure with the sensor are 85 nm carboxylated polystyrene beads which bind to the sensor surface (representing specific binding of e.g.viruses which approximately this size), protein A (representing non-specific binding) which also binds to the sensor surface but is smaller (≈2 nm [17,18]) and D-glucose which hardly binds to the sensor surface but induces a bulk change.These substances induce n Δ 's at different places within the evanescent field and can therefore be discriminate from each other.In this case we discriminate between substances of different materials, but it is also possible to discriminate between substances of the same material as long as they are different in size.All the measurements are done using a 1x phosphate buffered saline (PBS) buffer to which the different samples were added.The measurements start with a baseline of approximately 400 s to determine the drift of eff N Δ signal (can be caused e.g. by temperature fluctuations causing relative movement between chip and CCD camera or causing directly a n Δ at the sensing windows) which results in drift in n Δ (see Appendix E).Next, the measurements continue with a characterization step, containing an addition of 6.16 mg/ml D-glucose for 500 s to the PBS, which can be used to verify that the sensor responds as expected or to fit a theoretical model by changing waveguide parameters such that the determined curves of n Δ fulfil the expectations.

Theory
Usually, a YI is used to determine a Here, we shortly describe two analysis approaches which can be used for this: an approach based on theoretical analysis and a ratio-based analysis approach.A more detailed description of the ratio-based approach can be found in Appendix B. layer is determined and therefore this method is less suitable for situations where n Δ 's are induced in the same layer by different substances.However, assuming a low concentration of analytes, for example bulk effects can be cancelled out by subtraction of n Δ determined from multiple layers to finally arrive at an analyte concentration [15].Nevertheless, this method requires tuning of many parameters to determine the correct values for the sensitivity coefficients that are required to determine the absolute value of n Δ .Hence, this method is exact but in practice difficult to implement because of the many parameters that have to be tuned.This approach also requires more input than actually required, so therefore we developed a much more practical and easy to use ratio-based approach.

Ratio-based approach
Here, we present the ratio-based analysis approach which uses the ratios of .
RI changes of multiple substances inducing different ratios can be discriminated from each other as a function of the measured ratios using (see Appendix B information for derivation):  3), we can use this equation.for analysis of a real experiment in which we add multiple substances simultaneously to the sensor to find the contribution of each substance independently.
An advantage of the ratio-based method is that direct discrimination between different substances is possible, also when s n Δ 's occur in same layer in the evanescent field, as long as the ratios in wavelengths are different from each other and as long as the substances do not influence each other's response of the sensor.The analysis of two substances which induce a s n Δ is relatively easy as only two ratios are determinable parameters which determine the shape of the signal of s n Δ over time.For three substances inducing a s n Δ , already six ratios need to be determined, illustrating the rapidly increasing complexity when increasing the number of distinguishable substances inducing a s n Δ .However, these ratios can be determined independently for each substance to discriminating these substances from each other.
The absolute value of s n Δ can be determined by combining the ratio-based approach with the theoretical model used for the approach based on the theoretical analysis.In this way 1 − Θ can be determined.However, this requires again tuning of a lot of parameters.Therefore, it might be easier to determine scaling parameters for s n Δ using calibration experiments, which are usually also carried out by a single wavelength.Alternatively, this method can also be used as a quick screener, providing only a yes or no answer on the presence of the analyte and which therefore does not require knowing the absolute values of s n Δ .

Results and discussion
First, we present the measured ratios / m k l s R λ λ for the individual substances which are used for the ratio-based approach to discriminate between these different-sized substances.Second, we present measurements in which two substances simultaneously induced a n Δ and the corresponding results obtained from both the approach based on theoretical analysis and the ratio-based analysis approach.Third, we demonstrate the power of the ratio-based approach in a blind experiment were the binding of 85 nm beads was discriminated from binding of protein A.

Ratios of individual substances
Here, we present the measured ratios of eff N Δ measured at different wavelengths for each individual substance which are used for the ratio-based approach in order to discriminate between these substances in the measurements presented in the next sections.We measured the ratios for two different wavelengths The error margins of the ratios are determined by twice the standard deviation (95% confidence interval) of the measured ratios from different experiments.A more detailed description of how these ratios are determined is found in the Appendix B. The spread in the measured ratios might be caused by artefacts in the measurements (see section 4.4) or slightly different sensor surface properties from run-to-run due to unequal cleaning which can result in changes in binding as we use non-specific binding of the protein A and 85 nm beads.The ratios of the different substances are in principle independent of the substance concentration as long as the resulting surface concentrations are much smaller than a full monolayer coverage.When substances bind on top of each other this will result in a different ratio and therefore the proposed method is not valid anymore.

Discrimination between two different-sized substances
In this section we present measurements where two of the three named different-sized substances (protein A, 85 nm beads and D-glucose which induces a homogeneous n Δ in the whole evanescent field of a few hundreds of nanometres) are discriminated from each other.First, 6.16 mg/ml D-glucose and 2.0 μg/ml protein A were added simultaneously to the sensor (see Fig. 1 λ is higher than at 2 λ which is expected since shorter wavelengths are more confined to the core of the waveguide and have a relative larger field near the surface compared to the longer wavelengths.Therefore, the shorter wavelengths are more sensitive to changes close to the surface compared to longer wavelengths.Figure 1(d) shows a similar experiment where after addition of only 6.16 mg/ml D-glucose, 6.16 mg/ml D-glucose was added simultaneously with 1.0 μg/ml 85 nm beads.Figure 1(g) shows a similar measurement where after addition of only 6.16 mg/ml Dglucose,1.0 μg/ml protein A was added simultaneously with 2.0 μg/ml 85 nm beads respectively.protein A and D-glucose and g) protein A and 85 nm carboxylated polystyrene beads and corresponding determined n Δ using the approach based on theoretical analysis (b, e, h) and the ratio-based analysis approach (c, f, i).Corresponding determined n Δ using the theoretical and ratio-based analysis method is shown in respectively e) and f).

Protein A and beads
For the measurement of simultaneous addition of beads and protein A the approach based on theoretical analysis is not very suitable, especially because 2 l n Δ is far from homogeneous as the evanescent field penetrates deeper than the thickness of the bead.Moreover, the expected end levels of the protein A and the beads are not known which was known for the bulk effect of the D-glucose.Consequently, the fitting of d 1 is not feasible.Using the ratio-based approach it is possible to discriminate between the protein A and the beads.The result based on ratios of ratios measured for the individual substances is shown in Fig. 1(i , where the added beads concentration was two times lower.The differences might be explained that different chips and different stock solutions were used for the different measurements.Furthermore, all the measurements are based on the non-specific adhesion of the protein A and the beads to the sensor surface.Therefore, small differences between sensor surfaces can make a large difference.The result from D-glucose in which no binding is involved, the signals were in nice agreement with each other.Determined RI changes due to non-specific binding of particles and between different measurements should not be compared if not all the conditions (chip, stock solution, analysis parameters) of the measurements are the same.
Besides, Fig. 1(i) shows that using two ratios, excluding glucose 660/ 457 R , it is not possible to suppress the first D-glucose step from the protein and beads signal.Three wavelengths are required to discriminate between protein A, 85 nm beads and D-glucose in a single measurement, as presented in the Appendix C.

Blind experiment
To approve the usability and verify the correctness of the ratio-based approach a blind experiment was carried out.Six combined samples of protein A (in the range of 0.1 -1.0 μg/ml) and 85 nm beads (in the range of 0.4 -4.0 μg/ml) were made and labelled by an independent person.Before measuring, the samples were carefully mixed to ensure homogeneous solutions.Next, the samples were measured in two measurement sets performed on the same waveguide using three measurement channels and one reference channel.In between the measurement sets the waveguides were cleaned using a cleaning protocol with can be found in Appendix G.A D-glucose characterization step was applied to verify the correct response at the different wavelengths.This resulted in a different ratio of the measured eff N Δ 's of 1.263 compared to the 1.218 ± 0.016.This can be explained by the fact that we used a different chip for this measurement which can have for example a slightly different d core .To correct for this deviation, we changed the average measured ratios of the individual substances by multiplying them by 1.263 / 1.218 and used this for the ratio-based approach to analyse this experiment.For visibility reasons, the data points A and F of the applied protein concentration are slightly offset but they both correspond to 0.9 μg/ml.
The applied bead concentration and the determined bead n Δ show a linear trend which means the bead n Δ was determined correctly using the ratio-based approach, assuming a linear relation between the number of beads in the sample and response of the sensor.Moreover, it shows that it is possible to do a calibration experiment to find the relations between the beads concentration and the response of the sensor.Furthermore, also a linear trend is seen between the measured protein n Δ and the applied protein concentration.Only at higher applied protein A concentrations, the determined protein n Δ flattens off, which can be explained by the fact that for these measurements the surface was saturated with protein A which can be seen in Fig.

Noise, drift and artefacts in measurements
Here, we shortly discuss the influence noise, drift and artefacts in To be able to use this method for three wavelengths to solve three independent n Δ 's, the artefacts in the measurement should be reduced by for example testing if larger optical components reduce the artefacts.'s to discriminate between three different substances inducing a n Δ , the result became more noisy.For a successful application of these analysis approaches used to determine three independent n Δ 's, the artefacts (due to boundary effects of the shifting interference pattern, see Appendix D) in eff N Δ should be reduced significantly.Alternatively, other techniques to improve specificity can be used next to size-selective detection.For example, to discriminate the binding of beads from binding of protein A and bulk changes due to D-glucose, D-glucose can also be added to the reference channel to cancel out the contribution due to D-glucose.In that case only two wavelengths are required to discriminate between binding of beads and proteins, resulting in less enhancement of noise.Application of a approach based on theoretical analysis made it possible to discriminate between n Δ 's occurring in different layers in the evanescent field, assuming a homogeneous n Δ in each layer.However, to determine the correct value for n Δ , this method requires multiple parameters (e.g. the waveguide core thickness, waveguide RIs, layer thicknesses, wavelengths) to be tuned that is difficult and labour-intensive.Therefore, also a much more pragmatic ratio-based analysis approach is presented to discriminate between n Δ 's induced by different substances.Moreover, this approach can be used for different substances inducing a n Δ in overlapping layers, which is not always possible with the approach based on theoretical analysis.Information on the absolute amplitude of s n Δ is lost using the ratio-based approach, however for determining an analyte concentration calibration measurements can be performed which are usually also required using an YI with a single wavelength.85 nm beads, D-glucose and protein A were discriminated from each other using this ratio-based approach.The working of the ratio-based approach was verified by a blind experiment with different samples containing different concentrations of protein A and beads.We could discriminated bead n Δ from protein n Δ , resulting in an expected linear trend of the bead n Δ with the applied concentration.So here we discriminate between protein A (≈2 nm large) and 85 nm beads, but this can raise the question what would be the minimal size difference of discriminable substances.It is very difficult to say something general about this as the minimal discriminable size difference depends on a number of parameters such as the amplitude of the signals of the substances and the amplitude of the noise, artefacts and drift of the phase signal.When a certain application is identified, then the sensor should be optimized to determine the limits of the device for the specific application in mind.Size-selective analyte detection can for example be used to discriminate specific analyte binding of larger particles from non-specific binding of smaller particles.Therefore, we believe that with measuring size-selectivity we can strongly improve the performance of our YI sensor and IO interferometric sensors in general.Especially the ratio-based approach is an easy approach to discriminate between different substances causing a n Δ .

Appendix A: Experimental details
In this section we describe the experimental details of the setup which was used for the measurements presented in the main text and in the rest of the appendices.

A.1 Sample transportation
Samples are degassed by a 4-channel Degassi Classic degasser and transported to the sensor surface by a 4-channel Ismatec® Reglo Digital Peristaltic Pump with a flow rate of 100 μl/min towards the sensing windows of the waveguide structure.On top of these sensing windows a 100 μm high fluid cuvette is placed to transport the sample to the sensor with a laminar flow, which means that in the evanescent field that is used for detection the velocity is nearly zero and transport of the different substances is determined by diffusion.

A.2 Hardware
Measurements are performed in a 4-channel single-mode ridge waveguide YI sensor.The waveguide consists three layers: a PECVD SiO 2 layer covering a LPCVD Si 3 N 4 70 nm thick core on top of a thermal SiO 2 substrate.A sensing window with a length l of 4 mm is created by etching away the PECVD SiO 2 cover.Measurements are done with one single waveguide structure (chip) which is cleaned after each measurement (see Appendix G).The wavelengths 457, 561 (only used when discriminating between three substances) and 660 nm are chosen such that only zero order TE modes (in height) fit into the waveguide and such that wavelengths are well spread, which is required to achieve a good precision [15].The different light sources are coupled into a single mode polarization maintaining (SMPM) fiber which can be positioned with respect to the waveguide using an xyz-stage to be able to quickly and sufficiently couple all wavelengths into the waveguide.The fiber tip is strengthened with a glass ferule which is positioned against the waveguide with a matching index gel in between them to prevent reflections at the interfaces which resulted in a oscillations of the phase signal.Figure 3 shows a schematic overview of the hardware of the setup.Next, Thorlabs, BB1-E02 visible broadband dielectric mirrors (M1-M4) and a Semrock Di01-R561-25x36 dichroic mirror (D1) and a Semrock Di01-R442-25x36 dichroic mirror (D2) are used to overlap the three lasers which are subsequently coupled into a Thorlabs PM460-HP single mode polarization maintaining (SMPM) fiber using a Schäfter + Kirchhoff GmbH 60FC-4-RGBV11-47 apochromatic fiber collimator (F).This fiber is positioned on a ULTRAlign Precision XYZ Positioning Stage (XYZ) with DS-4F High Precision Adjusters to position the fiber with respect to the YI waveguide (W) in order to efficiently couple the light via butt-end coupling into this 4-channel single-mode ridge waveguide.After the light is coupled out of the waveguide it will form an interference pattern which is collimated in the horizontal plane using a Thorlabs, ACY254-075-A cylindrical achromatic lens (C1).Subsequently, the interference pattern passes a Thorlabs LPVISE100-A linear polarizer with 400-700 nm N-BK7 protective windows (P) to filter out possible converted TM polarized light.
Next, the light is directed to a Thorlabs, GT-25-03 25mm x 25mm 300 lines/mm visible transmission grating (G) to separate the different wavelengths after which it passes a Thorlabs ACY254-050-A cylindrical achromatic lens (C2) which images the interference patterns on a Alta U30-OE CCD camera (CCD).

A.3 Analysis
A Fast Fourier Transform (FFT) is applied to the interference patterns detected with the CCD camera.Different windows were applied to the interference patterns to prevent boundary effects (see Appendix D).Subsequently, spatial frequency peaks of the interference pattern are determined such that the phase change ϕ ) of each channels pair can be read out.For the measurements we only use one channel pair combination (one measurement channel and one reference channel) and the rest is neglected, expect for the blind experiment for which we use all channels.λ =561 nm and 3 λ =660 nm), and for three different substances: 85 nm carboxylated polystyrene beads, protein A and D-glucose (see Table 1), representing specific binding, nonspecific binding and bulk changes respectively.Figure 4 shows an example of a measurement with D-glucose and 85 nm beads measured at 1 λ =457 nm and 3 λ =660 nm, illustrating the difference in 660/ 457 R for both substances.A single value for the ratio for a given substance is determined by calculating the mean value of the ratios over the time interval in which the ratios have a relatively stable value for that substance.In practice it was found that the time intervals that show a stable ratio correspond to intervals in which 1 , eff N λ was between 80 -100% of its maximum value for D-glucose, 20 -100% for 85 nm beads and 10 -100% for protein A. Therefore these intervals were applied for determination of all ratios.

B.2 Theory of ratio-based analysis method
Here, we derive Eq. ( 3) of the manuscript.When a substance s m is added to the sensor it induces a Assuming that substances do not influence each other's response of the sensor, multiple substances inducing different ratios can be discriminated from each other using: where the vector where we neglect the dispersion in  7) can be rewritten as:

Appendix C. Discrimination between three different-sized substances
To test if both analysis approaches are also applicable when using three wavelengths to discriminate three n Δ 's induced by three different substances, D-glucose (6.16 mg/ml), 85 nm carboxylated polystyrene beads and protein A were added to the sensor after each other.The  Δ , illustrating the complexity and limits of the approach based on theoretical analysis.Therefore, we ratio-based approach is better used for this analysis.starting with a PBS buffer, adding 6.16 mg/ml D-glucose at t 1 resulting in higher eff N Δ for the longer wavelengths as expected.After applying a washing step at t 2 ,1.0 μg/ml 85 nm beads was added at t 3 .The response of the shorter wavelengths is now larger.After washing again with PBS at t 4 , 2.0 μg/ml protein A was added at t 5 resulting in a relatively stronger response of the shorter wavelengths.After applying a washing step at  , but also in a small increase of glucose n Δ .Therefore, the ratios were also optimized by analysing the measurement based on two wavelengths/substances.An example is shown in Fig. 6 .All these values fall within the error margins of the experimentally determined ratios of the individual substances presented in Table 1.Using the slightly changed ratios, the three substances are nicely decoupled, illustrating that it is possible to discriminate between three different substances.However, the enhanced drift and artefacts in s n Δ makes it difficult to analyse these results.Moreover, when substances were added simultaneously (data not shown here) fitting based on two substances/two wavelengths is not possible.Therefore, the ratios used for the analysis should be measurable from measurements with the single substances and not be tuned afterwards.To realise this the spread in ratios should be reduced.More research is required to determine what the origin of the spread of the ratios is.In order to do this, it should be investigated if the spread can be explained by the artefacts or other noise sources of the measurements, the cleaning of the surfaces of the chip (larger spread is seen in binding of substances compared to bulk changes due to D-glucose) or the substances self (spread in protein A is smaller compared to beads).At least it is required to reduce the aforementioned artefacts which are enhanced too much when using three wavelengths to discriminate between three substances.

Appendix D. Artefacts in signal due to boundary effects of shifting interference pattern
Computer generated images of interference patterns (based on our four channel Young interferometer) were used to verify the correct working of the Labview program which is used to collect interference patterns and determine the corresponding phase changes during an experiment, to investigate artefacts when determining a phase change from a finite interference pattern and to test windowing functions to reduce artefacts.Calculations of the generated interference patterns are based on four point sources distanced at 60 μm, 80 μm and 100 μm, an imaged distance of 17.5 cm, and wavelengths of 457 nm and 660 nm.The generated images have a width of 1024 pixels, a height of 100 pixels and a dynamic range of 60000 counts and include shot noise (Poisson noise).To simulate a real experiment, a time varying eff N Δ (~ϕ Δ ) is introduced (see Fig. 7(a)).For each corresponding time point an image is calculated and stored for later analysis.Next, the Labview program loads the images, adds up the selected number of rows on which the interference patterns are imaged and subsequently adds 1024 zeros to increase spatial frequency resolution to improve phase readout.Optionally, a windowing function is applied before a Fast Fourier Transform (FFT) is executed.From the resulting spectrum, the phase and amplitude of the six different spatial frequencies are determined of which we now analyse one peak belonging to one channel pair.Δ measured at the spatial frequencies (sf) belonging to the channel combination in which a n Δ was generated in one of the channels as well as from the channel combinations in which no n Δ occurred (cross-talk, CT).To demonstrate the effect of windowing, results are plotted for different type of windows.For example, applying a Blackman-Nuttall or a Dolph-Chebyshev window, both CT and NE can be completely suppressed down to the shot-noise level as the artefacts were not visible above the shot-noise level.
Next, the use of different windows on real experimental data is evaluated.The mean pk-pk values of CT are similar to the mean pk-pk values of NE.Therefore, the mean pk-pk values of CT are used as a measure for the pk-pk values of NE for the real experiments, as it is not possible to determine the fluctuations in the measured signal of The analysis of an experiment with a two channel YI (two channels were blocked with a mask) showed similar artefacts as for a four channel YI, which means the artefacts are in the measured signal itself and not only induced by CT as there is only one spatial frequency peak for a two-channel YI.Binding, drift 457 nm, 660 nm: 2x10 -8 s -1 Bulk, drift 457 nm, 660 nm: 2x10 -8 s -1 Binding, drift 457 nm, 660 nm: -2x10 -8 s -1 Bulk, drift 457 nm, 660 nm: -2x10 -8 s -1 the end-result on the parameter values.Figure 11 shows an experiment where first only Dglucose and later both 85 nm carboxylated polystyrene beads and D-glucose were added to the sensor, which is used for this investigation, and the corresponding determined n Δ which the approach based on the approach based on the theoretical analysis and the ratio-based analysis approach.λ = 660 nm for addition of 6.16 mg/ml Dglucose only and addition of 6.16 mg/ml D-glucose and 1.0 μg/ml 85 nm beads simultaneously, b) the determined n Δ with the approach based on theoretical analysis and c) determined n Δ with the ratio-based approach.

F.1 Approach based on theoretical analysis
The input parameters of the approach based on the theoretical analysis that were varied are d core and d 1 .Varying the d core results in a varying level of both the value of n Δ of layer 1 and layer 2 at the D-glucose step.Independent of the layer thickness d 1 , the n Δ at the addition of only D-glucose should be the same in both layers, which is realized by choosing d core = 63 nm.Subsequently, the end level of both signals can be tuned by varying d 1 .The end level of the bulk should be zero, because there was no n Δ for the bulk compared to the starting situation were the bulk was also PBS.In the case of linear drift, the end level will not be zero but in line with the linear drift.This was realized with a d 1 = 65 nm, assuming a d core = 63 nm.l l n n Δ −Δ stays within the 20%.We assume that this deviation is acceptable but off course the limits of the acceptable deviation might be different for each application.For the d core this means that it should be determined with an maximal deviation of approximately ±1 nm.When this value is accurately determined it can be seen that the value of d 1 is less critical (a range of approximately 50 nm is fine).It should be noted that these deviations are determined for this specific case and at one time point.Deviations can be different when substances are different.Moreover, deviations in terms of percentage might be much larger when  R should be between 1.192 and 1.254 (see dotted lines in Fig. 13(a)).This results in an difference of 0.062 which is higher than the deviation measured in glucose 660/ 457 R of 0.032 (= ±0.016, see of 20%.The difference of 0.066 is lower than the response of the beads between measurements of 0.090 (= ±0.045, see Table 1).So the spread measured in 660/ 457 bead R is not acceptable when we assume a maximal deviation in bead n Δ of 20%.Therefore, more research is required to determine what the origin of the spread of the ratios is in order to reduce this spread.It should be investigated if the spread can be explained by the artefacts or other noise sources of the measurements, the cleaning of the surfaces of the chip (larger spread is seen in binding of substances compared to bulk changes due to D-glucose) or the substances self (spread in protein A is smaller compared to beads).Again, it should be determined for each application what the maximally allowed deviation is and it should be noted these deviations are determined for this specific case and at one time point in the graph of Fig. 11  # wavelength.Consequently, an average n Δ is determined, based on any n Δ in the whole evanescent field.Measuring the eff N Δ at multiple different wavelengths enables discrimination between multiple different n Δ 's.
wavelengths, enables the discrimination between n Δ 's originating from two arbitrarily chosen layers within the evanescent field [15], using the following equation: RI change in the j th layer (index l stands for layer), the elements S are the theoretical sensitivity coefficients, which are the derivatives of eff N at the i th wavelength with respect to n occurring in the j th layer and the element , i th wavelength.The sensitivity coefficients are determined by the structure of the waveguide (core thickness and RIs of the various layers of the waveguide), the wavelengths, the polarization and two arbitrarily chosen layers (within the evanescent field).The l n Δ can be determined by measuring eff N Δ and multiplying this by the inverse of matrix S .A homogeneous l n Δ per by n Δ 's originating from different substances s n Δ .Each substance with a different size which causes a s n Δ in the evanescent field results in different eff N Δ 's for each wavelength because of the different electric field distributions of the respective wavelengths.The ratio of the eff N Δ measured at two different wavelengths k λ and l λ , induced by a substance s m , is defined as: , , / procedure is now as follows.First a characterization step is required to determine matrix R by measuring the response of the sensor for each individual substance.The matrix 1 −Θ can be regarded as a scaling matrix that allows to get absolute values of s n Δ .When the coefficients of this matrix are unknown, , is required.Now that we know the matrices of Eq. (

Fig. 1 .
Fig. 1.Two substances discriminated from each other.The

Figure 1 (R 2
Figure 1(b) shows the n Δ corresponding to Fig. 1(a) determined with the approach based on theoretical analysis.Assuming a homogeneous n Δ in the whole evanescent field for the Dglucose characterization step, the determined 1 l n Δ should be the same as ).As was mentioned, amplitudes between protein 1(c).In Fig.1(i) half of protein A was added to the sensor, but the measured protein n Δ is only 1.6 times lower.An even lower signal of protein n Δ is expected as now also beads can cover part of the surface where beads can bind.Furthermore, the bead n Δ of Fig. 1(f) is approximately 2.6 times higher compared to bead n Δ of Fig. 1(i)

Figure 2 (Fig. 2 .
Fig. 2. Blind experiment with six samples (A-F) containing 85 nm beads and protein A. a) The measured eff N Δ over time of one measurement of the set of blind experiments b) the corresponding determined 2(b).That the signal of bead n Δ still increases might be explained by the beads replacing the protein A of the surface.The be able to compare bead n Δ and protein n Δ , the signals were both read out at the same time point.The blind experiment illustrates that the determined substance n Δ can be compared with the substance n Δ of a different experiment, when using the same measurement conditions (chip, stock solution, analysis parameters).
the above named approaches, which means that they are stronger visible in n Δ .This can be explained by the matrix becoming more singular, resulting in enhancement of all kind of noise sources.Linear drift measured in eff N Δ 's (e.g.due to temperature changes causing relative movement between chip and CCD camera or causing directly a n Δ at the sensing windows) results in linear drift in n Δ of both layers (see Appendix E).For the measurements we assume linear drift and take this into account when fitting/ m k l s R λ λ or waveguide parameters.Moreover, artefacts (fluctuations e.g.seen in Fig. 1(f) at t ≈500 s and 1000 s in protein n Δ , but better visible at discrimination between three substances using three wavelengths, see Appendix C) show up in n Δ .These artefacts are present in the signal of the eff N Δ 's, but are not visible because of the relatively higher slopes of eff N Δ due to the fast addition of the sample.The artefacts are caused by boundary effects of the shifting interference pattern (see Appendix D).When inducing a linear ϕ Δ in the interference pattern this results in a oscillation in the amplitude of the spatial frequency as it is not constant when the fringes move.It also results in a oscillation in ϕ Δ which is directly related to eff N Δ .Using a proper windowing function (e.g.Blackman-Nuttall) we were able to remove the oscillations from simulated shifting interference patterns.However, this was not sufficient for the measured data, possibly because of non-ideal properties of the lenses, the grating and beam shape (see Appendix D).Therefore, the artefacts in or waveguide parameters.The spread in the determined d core , d layer and / can be caused by especially the artefacts, resulting in a wrongly determined n Δ .The signal of n Δ becomes especially very noisy in the case when discriminating between three n Δ 's based on three eff N Δ 's (see Appendix C).
wavelengths it was possible to discriminate between two different substances inducing a n Δ in the evanescent field of the sensor.The binding of 85 nm beads or protein A was discriminated from D-glucose and the binding of 85 nm beads was discriminated from the binding of protein A. Using three eff N Δ

Fig. 3 .
Fig.3.Setup.Schematic overview of the setup where L1-L3 are a 50 mW Cobolt Twist 457 nm Single Longitudinal Mode (SLM) Diode-Pumped Solid State (DPSS) laser, a 50 mW Cobolt Jive 561 nm SLM DPSS laser and a 50 mW Cobolt Flamenco 660 nm SLM DPPS laser respectively of which the power is regulated using Thorlabs NDC-100C-4M mounted variable ND filters (N1-N3) of which the reflected light is directed to Thorlabs BT500 beam dumps.Next, Thorlabs, BB1-E02 visible broadband dielectric mirrors (M1-M4) and a Semrock Di01-R561-25x36 dichroic mirror (D1) and a Semrock Di01-R442-25x36 dichroic mirror (D2) are used to overlap the three lasers which are subsequently coupled into a Thorlabs PM460-HP single mode polarization maintaining (SMPM) fiber using a Schäfter + Kirchhoff GmbH 60FC-4-RGBV11-47 apochromatic fiber collimator (F).This fiber is positioned on a ULTRAlign Precision XYZ Positioning Stage (XYZ) with DS-4F High Precision Adjusters to position the fiber with respect to the YI waveguide (W) in order to efficiently couple the light via butt-end coupling into this 4-channel single-mode ridge waveguide.After the light is coupled out of the waveguide it will form an interference pattern which is collimated in the horizontal plane using a Thorlabs, ACY254-075-A cylindrical achromatic lens (C1).Subsequently, the interference pattern passes a Thorlabs LPVISE100-A linear polarizer with 400-700 nm N-BK7 protective windows (P) to filter out possible converted TM polarized light.Next, the light is directed to a Thorlabs, GT-25-03 25mm x 25mm 300 lines/mm visible transmission grating (G) to separate the different wavelengths after which it passes a Thorlabs ACY254-050-A cylindrical achromatic lens (C2) which images the interference patterns on a Alta U30-OE CCD camera (CCD).

Figure 5
and their mean and corresponding 95% confidence interval (error bars, twice the standard deviation).The ratios / and corresponding confidence intervals are also listed that the response of the sensor has a linear relationship with the amount of s m that is added to the sensor, this can be written as: coefficient of the sensor for a RI change induced by s m .
Θ is a matrix with theoretical sensitivity coefficients of which the elements are given by , ≠ , and the coefficients of matrix R are given by

Figure 6 ( 1 λ with 2 λ and 1 λ with 3 λ
Figure 6(b) shows the n Δ corresponding to Fig 6(a) determined with the approach based on theoretical analysis after fitting the d core , d 1 and d 2 based on analysing the results based on two wavelengths.An example of this is shown in Fig. 6(c) where d core and d 2 were determined as 62.7 nm and 64 nm respectively, based on 1 λ and 3 λ .It can be seen that at the D-glucose step

Fig. 6 .
Fig. 6.Three substances discriminated from each other.a) The t 6 the signal decreases due to desorption of the protein A, b) the corresponding layer n Δ determined with the approach based on theoretical analysis fitting d core , d 1 and d 2 based on analysing the measurement with two wavelengths (see example shown in c)), the substance n Δdetermined with ratio-based approach based on d) the ratios measured with the individual substances and e) after tuning the ratios based on analysing the measurement with two wavelengths and two substances of which an example is given in f).

Figure 6 (
Figure 6(d) shows the determined

Figure 7 ( 5
a) shows an example of the induced and calculated eff N Δ for the two wavelengths.The same figure also shows the difference in eff N Δ between the induced and determined values.Figure 7(b) shows the determined amplitude and Fig. 7(c) shows the substance n Δdetermined with the ratio-based approach based on the induced (ind) and determined (det) Feb 2016; revised 14 Mar 2016; accepted 15 Mar 2016; published 12 Apr 2016 © 2016 OSA 18 Apr 2016 | Vol. 24, No. 8 | DOI:10.1364/OE.24.008594 | OPTICS EXPRESS 8611 substance n Δ of a real measurement.Similar fluctuations (which we call artefacts) are seen in in the amplitude and substance n Δ when no windowing is applied on the simulated interference patterns.These artefacts are most prominent during (fast) changes in the induced

Fig. 8 .
Fig. 8.The effect of applying different windows on the data on the error in the determined phase change (~e ff N Δ ).a)

Fig. 9 .
Fig. 9. Typical camera image illustrating three measured interference patterns from three different wavelengths, 660 nm, 561 nm and 457 nm, from top till bottom.

Fig. 11 .
Fig.11.Measurement where D-glucose and 85 nm beads are added to the sensor analysed with approach base on theoretical analysis and with ratio-based approach.a) Effective refractive index change over time at 1 λ = 457 nm and 2 λ = 660 nm for addition of 6.16 mg/ml D- Figure 11(b) shows the optimal result for n Δ based on d core = 63 nm and d 1 = 65 nm.Next, the d core and d 1 were varied and the change in (black dotted line in Fig. 11(b)) at t = 1900 s was determined.Consequently, the deviation in terms of percentage compared to the correct value at t = 1900 s (based on d core = 63 nm and d 1 = 65 nm) was determined, which is shown in Fig. 12.When we assume the deviation in should be maximally 10% and we fix the parameters d core or d 1 and vary the other, this results in the dotted lines in Fig. 12.When both d core and d 1 result in a deviation of 10% then the final deviation in 1 2 Fig. 12. Deviation in

F. 2
Ratio-based approachHere, we determined the influence of the ratios 660/ 457 220, having a zero level for the beads when only D-glucose was added.To fit the end level of the D-glucose with the expected value, assuming a constant linear drift, the t = 1900 s) in terms of percentage compared with optimal fitted results are determined and shown in Fig.13.When we assume a deviation in bead

Table 1 . Measured effective refractive index ratios. Experimentally determined
in Table1.

Table 1 )
, which means that the spread bead n Δ . from measurement to measurement is lower than the required 0.090, so sufficient.should be reduced.As was stated before, more research is required to determine the origin of the spread. R 257853 Received 5 Feb 2016; revised 14 Mar 2016; accepted 15 Mar 2016; published 12 Apr 2016 © 2016 OSA 18 Apr 2016 | Vol. 24, No. 8 | DOI:10.1364/OE.24.008594 | OPTICS EXPRESS 8618