A silicon photonic evanescent-field sensor architecture using a

fixed-wavelength laser
Lukas Chrostowskia,b , Leanne Diasa , Matthew Mitchellb , Connor Mosqueraa , Enxiao Luana ,
Mohammed Al-Qadasia , Avineet Randhawae,f , Hassan R. Mojaverc , Eric Lyalle , Antoine
Gervaisd , Raphael Dubé-Demersd , Kashif Awanb , Steven Goub , Odile Liboiron-Ladouceurc ,
Wei Shid , Sudip Shekhara , and Karen C. Cheunge,a,f
a
Electrical and Computer Engineering, University of British Columbia, V6T 1Z4, Vancouver,
Canada
b
Stewart Blusson Quantum Matter Institute, University of British Columbia, V6T 1Z4,
Vancouver, Canada
c
McGill University, H3A 0G4, Montréal, Canada
d
Université Laval, G1V 0A6, Québec, Canada
e
School of Biomedical Engineering, University of British Columbia, V6T 1Z3, Vancouver,
Canada
f
Centre for Blood Research, University of British Columbia, V6T 1Z3, Vancouver, Canada

ABSTRACT
Commercial silicon photonic (SiP) biosensor architectures rely on expensive swept-tunable lasers that limit their
use for widespread, point-of-care applications. An alternative is the use of fixed wavelength lasers integrated
directly on a silicon photonic platform. This study investigates the design considerations of such architectures.
Keywords: biosensors, silicon photonics, point of care, evanescent field sensors

1. INTRODUCTION
Biosensors that can be used in point-of-care settings and disposable tests will play an increasingly large role, not
only in routine monitoring or screening, but also in public health. Medical diagnostic testing has taken renewed
importance in light of the COVID-19 pandemic. As governments struggle to ensure public safety without
imposing restrictions that cause economic harm, fast and accurate COVID-19 testing on a massive scale is
necessary for informed decision making. This clearly motivates the need for high-volume, low-cost diagnostic kit
production for the detection of COVID-19 and variants. However, there are numerous other applications for such
sensors, including other infectious diseases, biomarkers for autoimmune diseases such as arthritis, early cancer
detection, health and wellness monitoring, water quality monitoring, oil monitoring, etc. Accurate diagnosis may
require monitoring and testing the levels of several biomarkers, using a multiplexed sensor. Sensor arrays can
generate multidimensional data, detecting not only multiple analytes but also giving unique signatures that can
indicate disease state. A multi-antigen serology panel has been recently demonstrated by Genalyte which has
been used for research studies.1 Label-free biosensors based on evanescent-field operation are capable of such
performance. Nevertheless, the two commercial technologies, surface plasmon resonance (SPR) biosensors and
microring resonator (MRR) biosensors with swept-tunable lasers, are expensive and not amenable to low-cost,
high-volume deployment.
In this work, we propose a new biosensor technology – a resonator-based biosensor that uses a fixed-wavelength
laser, integrated within the chip. The performance of commercial MRR biosensors can be retained, while the
cost and form-factor may be reduced by orders of magnitude. This architecture overcomes the disadvantages of
prior-art MRR sensors by eliminating the swept-tunable laser and replaces the necessary precision coupling to
the silicon photonic chip with low-cost photonic wirebond integration.
Further author information: (Send correspondence to L.C.)
L.C.: E-mail: [email protected], Telephone: 1 604 822 8507
2. REVIEW OF COMMERCIAL BIOSENSOR ARCHITECTURES
Many label-free photonic biosensing platforms have been commercialized in the last two decades.2 However, the
quest to miniaturize those bulky, laboratory-use instruments to a portable form factor, and reduce the cost for
mass adoption without sacrificing the performance (sensitivity, multiplexing) is still on going. We briefly review
SPR, the gold standard for studying binding affinity and kinetics between biomolecular species, then review
silicon photonic MRR sensors.

2.1 Review of SPR technology

Leveraging the high sensitivity to changes in surface optical properties (i.e., refractive index), SPR has prompted
considerable development in commercial detection platforms. With 20 years of development, the SPR biosensor
has become an important research tool in life sciences and pharmaceutical fields across multiple stages of drug
discovery and development. Currently, the most widely used SPR spectroscopic instruments are the Biacore series
developed by Biacore Life Sciences,3 which deliver high-quality affinity and kinetics data for small molecule and
biotherapeutic screening and characterisation.4
SPR is a charge-density oscillation that exists at the interface of two media with opposite sign dielectric
constants.5 When light’s wavevector component that propagates in parallel to the metal-dielectric interface,
namely the p-polarized light, matches the propagation constant of the surface plasmon mode, a surface plasmon
wave can be excited, which is an evanescent wave with the intensity of its electric field reaching a maximum
at the interface and decaying exponentially into both the metal and dielectric media.6 SPR biosensors use this
phenomenon to monitor biomolecular binding events occurring at the metal-dielectric interface. The formation
of this organic layer causes a change of refractive index at the interface, resulting in a change in the propagation
constant of the surface plasmon. This change of propagation constant alters the coupling condition between the
light and the surface plasmon waves, which can be measured as a change in one of the characteristics of the
optical wave interacting with the surface plasmon.6 Compared with traditional interaction technologies such as
ultracentrifugation, fluorescence, or calorimetry, SPR biosensors have the following remarkable advantages: (i)
real-time detection; (ii) no need for sample labelling and pre-treatment; (iii) minimal sample volume required;
(iv) quick detection with high sensitivity; (v) high-throughput, high-quality data analysis; (vi) suitable for turbid,
opaque or coloured solutions. A point-of-care biosensor has also been recently demonstrated.7 However, SPR
sensing technology still has some shortcomings, especially compared with immunological detection techniques,
in terms of (a) detection cost, (b) instrument integration, (c) ease of use, (d) requirement for thermal stability,
and (e) requirement for mechanical stability. SPR biosensors use gold surfaces, bulky parts such as rotatable
polarized light sources and prisms, and charged-coupled device cameras as detectors. These shortcomings provide
the motivation for lower-cost, highly-integrated, simple-to-use, portable alternative biosensor platforms.

2.2 Review of architectures in silicon photonic sensors platforms

Planar integrated optical sensing configurations have been investigated in past decades as alternatives to SPR
biosensors, since they offer the potential to integrate all components on a single chip, such as optofluidic inte-
grations for microfluidics and optoelectronic integrations for light sources and detectors which are usually bulky
parts in SPR biosensors.

2.2.1 System operation and limitations

The most common method for analyte detection in silicon photonics consists of a swept tunable laser, a silicon
photonic MRR sensor, and a photodetector to measure the wavelength (or phase) shift in the transmission
spectrum of the sensor. This is done by repeatedly scanning the input wavelength to the sensor and monitoring
transmission shifts over time, illustrated in Fig 1. The use of an off-chip swept tunable laser significantly
complicates the sensing system in two ways. Firstly, requiring an off-chip tunable laser adds tremendous cost to
the sensor system. By leveraging advanced CMOS fabrication technologies, the cost of manufacturing the silicon
photonic sensor chip is extremely low when produced at high volume. However, since the cost of a tunable
laser is quite high, requiring it in the system suppresses the savings gained from the low cost of the sensor.
Secondly, because the laser is off chip, it adds complexity and cost to the system by requiring repeatable and
precise techniques to couple light into the sensor chip. One such technique, implemented by Genalyte,8 uses a
Figure 1. Principle of evanescent field detector for a silicon photonic biosensor (a) The evanescent field around the
waveguide is sensitive to the RI change caused by biological binding events at the waveguide’s surface. (b) Optical
transmission spectra of the sensor before (blue) and after (red) the analyte interaction, resulting in a shift in resonance
wavelength. (c) Sensorgrams of the sensor in bulk (blue) and surface (red), where the signals are recorded as a function
of time.

Figure 2. Difference between SWG (top) and SWG-assist/fish-bone (bottom) waveguides, including strip-SWG taper
transitions

mechanical mirror system to focus the laser light onto a grating coupler for each sensor. While tunable lasers
have remained the standard for silicon photonic biosensors, their continued use impedes implementation of an
affordable sensing platform.
Because of the cost inefficiency of tunable lasers, some alternative approaches have been researched. One
option is to use broadband light sources, such as LEDs, SLEDs, or ASEs.9–11 While cheaper than tunable
lasers, these sources are also difficult to integrate on chip and therefore suffer from the same optical coupling
complications as lasers.

2.2.2 MRR sensor operation and limitations

In resonant microcavity designs, light is coupled into the microcavity by the evanescent field. The light then
continues travelling in the cavity with multiple round trips, which creates interference at specific wavelengths.
The resonance condition is given by:

2πr × neff
λres = (1)
m
where λres is the resonant wavelength, r is the radius of the resonator, neff is the resonator effective refractive
index, and m is an integer. When the microcavity is exposed to a sample, the position of the resonant wavelength
will shift due to the change in neff . The effective interaction length of the light with the sample is characterised
by the quality factor (Q-factor), which describes how long the photon energy stays within the resonator.12
Microcavity resonators are a promising option due to their compact size, enabling high-density integration on
chip. While the sensitivity of a resonator structure cannot be improved with increasing size, various waveguide
structures can be implemented to help increase the sensitivity, and reduce the losses on-chip and increase the
Q-factor.

2.2.3 Resonator waveguide type

Sub-wavelength grating (SWG) waveguides have been demonstrated as excellent waveguides for sensing appli-
cations,13 but they present a challenge for manufacturing the oxide open window required to expose these small
silicon structures for sensing. Namely, an over etching of the oxide open window may cause the isolated silicon
blocks to get detached from the buried oxide layer, which is a risk for the manufacturing process. As an alternative
that has similar sensitivity as sub-wavelength waveguides is the fish-bone sub-wavelength grating waveguide.14, 15
The fish-bone structure (Fig 2) is less challenging in terms of fabrication, because it maintains the waveguide as
a homogeneous piece of silicon hence is less likely to be etched away in fabrication. Additionally, the continuity
of the taper strip throughout the fish-bone waveguide keeps the effective index transition continuous throughout
the structure, thus avoiding additional unwanted losses and reflections from the taper interface. In contrast, in
conventional SWG waveguide transitions, the taper end widths need to be specifically designed to minimize the
index mismatch.

2.2.4 Performance metrics for silicon photonics resonator sensors

Some of the most important metrics for characterising the performance of a sensor are the bulk sensitivity (Sb ),
surface sensitivity (Ss ), and the bulk intrinsic limit of detection (iLoDb ).
Bulk sensitivity is defined as the change in resonance wavelength (∆λres ) due to a change in the surrounding
refractive index of the device (∆nclad , a unit-less quantity, referred to as Refractive Index Unit, RIU):16

∆λres λres ∂neff λres · Swg−f rac λres · Swg
Sb = = = = · ff (2)
∆nclad ng ∂nclad ng ng

where ng is the group index of the resonator and Swg is waveguide mode sensitivity. For resonator sensors where
only a portion of the resonator path length acts in a sensing capacity, the waveguide mode sensitivity in Eq. 2
should be scaled by the percentage of the resonator path that is used for sensing, known as the fill factor f f .
This quantity is called the fractional sensitivity Swg−f rac = Swg · f f . The group index ng in Eq. 2 refers to the
effective refractive index of the entire resonator, which can be extracted via the free spectral range (FSR) as:

λ2
ng = (3)
L · F SR
where λ is the resonance wavelength and L is the length of the entire resonator.
The quality factor (Q) is used as a measure of how long energy stays within a resonator, which can give
a sense as to how the losses in the system affect the performance. Approximated by the ratio of the resonant
wavelength to the FWHM, the upper limit for Q is expressed as:17

2π · ng · 4.34
Q= (4)
λres · α(dB/m)

where α(dB/m) is the propagation loss within the resonator in decibels per metre.
The system Limit of Detection (LoD) is the smallest possible refractive index change which can be measured.
This is limited by the noise levels of instrumentation and environmental fluctuations, and the accuracy to which
the resonator wavelength may be determined, on the order of 1 pm, which is a small fraction of the resonator
linewidth. For easier comparison between different sensors, an alternative figure of merit is the bulk intrinsic
Limit of Detection, iLoDb , which provides a simple calculation for the minimum detectable change in the bulk
refractive index. It is defined as the index of refraction change required to shift the resonator wavelength by one
linewidth:16

λres
iLoDb = (5)
Q · Sb

A summary of sensitivity, Q-factor, and iLoDb of published silicon photonic-based sensing devices is presented
in Fig 3. This plot illustrates the design parameter trade-off between a high waveguide sensitivity (achieved by
maximizing interaction with the solution) and a high quality factor resonator (achieved by minimizing interaction
with the solution since water absorption is the dominant loss mechanism). Numerous sensor design approaches –
1) utilizing different waveguides such as strip waveguides operating in the quasi-TM mode, slot waveguides, and
This work

Figure 3. Reported silicon photonic resonator sensors performance comparison in terms of the bulk sensitivity (nm
wavelength shift per refractive index unit, RIU), the quality factor and the intrinsic limit of detection (iLoD). Except for
the design labeled at 1310, the designs operate at a wavelength of approximately 1.55 µm. The sensors include Ring-
TE-1310,13 Ring-TM-1310,13 Multi-box ring,16 Slot ring-TE,18 Substrate overetch SOE SWG,19 SWG ring-TE,20 SWG
ring-TM,21 Ring-TE,13 Thin ring-TE,22 Thin ring-TM,23 Ring-TM,23 Bragg-1310 (TM),13 Slot Bragg,24 Bragg-TE,25
Multi-box Bragg,26, 27 Disk-TE,28 Disk-TM,28 Photonic Crystal PHC-ring,29 PHC-TE,30 and SWG PHC.31

sub-wavelength grating waveguides, and 2) utilizing different resonators such as disks, rings, photonic crystals,
and Bragg gratings — have thoroughly explored this design space, illustrating that optimized designs yield a
bulk intrinsic limit of detection of approximately 5 × 10−4 RIU . The slight variations are a result of different
wavelengths, different fabrication processes (different scattering losses), and different amounts of deterministic
excess losses in the design (mode-mismatch losses, bend waveguide radiation losses). The best intrinsic limit
of detection was achieved in a straight waveguide configuration (minimizing bend loss), and operating at a
wavelength that minimizes water absorption (1.3 µm).13 The coupling coefficient to the resonator also affects
the quality factor, and the iLoDb . For example, a highly under-coupled resonator (such as the 1.3 µm TM Bragg
grating sensor13 ) will have a Q-factor that is 2× higher than a critically coupled resonator. Under-coupling is
undesirable for practical applications, however, since the reduced transmission through the resonator will reduce
the multiplexing potential due to optical power budget limited by laser power and detector sensitivity.

2.2.5 Comparison of swept-tunable and fixed wavelength laser platforms

Biosensor platforms with fixed-wavelength lasers are a promising approach to silicon photonic sensors due to
their low cost and simple integration on chip. However, previous designs utilized multiple lasers set a different
wavelengths to get several points along the transmission spectrum, and used to curve fit and reconstruct the
resonance peak of a sensor,32, 33 or requiring intricate electronics for readout and signal processing.34–36 De-
spite these complexities, the affordability and ease of implementation of fixed-wavelength lasers motivates their
realization in lab-on-chip sensor systems.
3. ARCHITECTURE WITH A FIXED WAVELENGTH LASER
3.1 Concept of a prototype
Traditional photonic biosensors such as the Genalyte system rely on an expensive tunable wavelength laser and
opto-mechanics to shape and steer the input light to each component on the SiP sensor chip,8, 37 as illustrated
conceptually in Fig. 4(a). By using fixed-wavelength lasers instead, they can be integrated on-chip as shown
in Fig. 4(b). When combined with a tunable detection scheme this will enable a completely on-chip, and cost-
effective solution.

Figure 4. Comparison of traditional tunable laser and fixed-wavelength laser approach for a silicon photonic biosensor.
(a) The traditional approach requires a tunable laser and beam shaping and steering optics to couple light into and out
of the silicon photonic biosensor. Due to the size of the tunable laser and optics these components are off-chip. (b) By
using a fixed-wavelength laser architecture combined with photonic wire bonding, all major components can be integrated
on-chip.

3.1.1 On-chip laser integration

We propose to utilize wafer-scale fabrication to create 1000’s of integrated SiP sensors on an SOI wafer. Cost-
effective distributed feedback (DFB) lasers will be bonded to each, which will be integrated with the SiP circuit
using photonic wire bonds. Photonic wire bonding uses direct two-photon polymerization writing of a negative-
tone photoresist to 3D print a polymer waveguide.38, 39 Integrating III-V lasers with SiP is a very active area of
research due to the lack of a room-temperature silicon laser. As such, many impressive techniques for integrating
lasers on chip also exist. Unfortunately, the growth and integration of III-V materials on SOI is not yet widely
available in SiP foundries and current laser and fibre bonding techniques require relatively complex fabrication
methods that limit scalability. As such, we have opted for the photonic wire bonding approach,40 which allows for
the integration of components without the need for high-precision/active alignment techniques41, 42 or on-chip
wave-steering optics such as micro-mirrors and lenses43, 44 and enables connecting components with arbitrary
mode fields in an automated fashion.45 The insertion loss of photonic wire bonds in the C-band have also been
shown to be as low as 0.7 dB46 and is expected to be similar for O-band, making this technique an attractive
method for scalable integration of photonic components and chips. Lasers in the C-band are more difficult to
manufacture and thus more expensive compared to those in the O-band,47 which is an important factor when
considering the desire for low-cost, high volume production of such sensors. The other consideration between the
two bands is that the absorption of water is about ten times greater in the C-band,48 meaning O-band sensors
of the same circuit architecture have better performance.
Laser integration is being pursued using the Vanguard SONATA1000 photonic wire bonding tool. There are
some considerations when connecting two components using this approach. The first is that the working distance
of the objective lens used for the confocal microscope is 250 µm, and as such the two components that will be
connected must not have a height difference greater than 250 µm. Secondly, in order to avoid excess insertion
Figure 5. Wafer scale integration of fixed wavelength lasers. (a) By utilizing SiP foundries many sensors can be fabricated
on a wafer, with pre-defined areas blocked off for integrating the DFB lasers via photonic wire bonding. (b) Isometric and
cross section view of how the lasers can be integrated on-chip. (c) Proof-of-principle SiP samples fabricated to characterise
the laser die attach process and photonic wire bonding process.

loss, care should be taken to maximize the radius of curvature of the wire bond, by achieving rough alignment of
the components to be bonded in all three dimensions. However, this alignment can be performed manually. As
the DFB lasers in this project are ∼ 100 µm thick, in order to achieve a low loss photonic wire bond, we will etch
a recess into the SiP chip in which to place the laser. This also improves the thermal heat sinking of the laser
die by avoiding the buried oxide layer of the SOI wafer. As our lasers have one electrical contact on the bottom
of the die, the cavity must be metalized, as shown in Fig. 5(b). By etching a cavity with a large sidewall angle
and depositing metal via electron beam evaporation, a connection can be made to the surface of the chip for
electrical wire bonding. Alternatively, provided it is feasible to do so, an electrical bond pad could be defined in
the cavity for electrical wire bonding. Lastly, the photonic wire bond should be cladded in a UV-curable epoxy
for optimal single-mode operation, mechanical stability, and protection from the environment. Due to the close
proximity of the electrical and photonic wire bonds, this cladding material will likely need to encase both the
electrical and photonic wire bonds. Some examples of lasers that have been attached to a SiP chip are shown
in Fig. 5(c), which are proof-of-principle samples fabricated to characterise the laser attach and photonic wire
bonding process.

3.1.2 Tunable sensor design

To enable the use of a fixed-wavelength laser we propose an architecture that utilizes photoconductive waveguide
heater-detectors (PCHD) integrated into a ring resonator.49 By locating the heaters far from the sensing region
the refractive index of the resonator can be varied in order to tune the central wavelength of the SiP ring
resonator – analogous to changing the length of a mechanical pendulum – without causing temperature shifts in
the sensing region. For biosensing purposes, this achieves the same effect as sweeping the input laser wavelength
across the resonance. The PCHD also acts as an in-resonator detector, which measures the optical power in the
resonator.
Prototype devices were fabricated by Applied Nanotools Inc., using electron beam lithography.50 Fig. 6
shows the transmission spectrum of the resonator sensor, showing a quality factor of 44k. Based on experimental
measurements of the quality factor, and simulated fractional waveguide bulk sensitivity (see Table 1), the bulk
intrinsic limits of detection is 3.77 × 10−4 RIU, similar to results previous reported for SWG microring resonators
by Huang et al.21 as well as Flueckiger et al.20

-20

-25

FWHM
-30
Power (dBm)

-35 ER

-40
Measured data
Lorentzian fit
-45

-50
1268.44 1268.48 1268.52 1268.56 1268.6
Wavelength (nm)
Figure 6. Resonance notch with fitted Lorentzian curve. The full-width at half-maximum (FWHM) and extinction ratio
(ER) are labelled on graph. The Q-factor is approximated to 44,345 using the FWHM = 28.6 pm.

Q-factor (measured) Fractional Sensitivity (simulated) iLoDb

44,354 76.0 nm/RIU 3.77e-4 RIU
Table 1. Preliminary Results Summary

3.1.3 Microfluidic integration, sensor functionalization, and sample delivery

The delivery of reagents for surface functionalization of silicon photonic biosensors, as well as delivery of samples
containing the analytes, is often done using microchannels that are aligned over the sensor arrays. This can be
readily realized through soft lithography replication of silicone microchannels that are reversibly sealed onto the
chip surface. Polydimethylsiloxane (PDMS) has seen widespread adoption in the microfluidics community owing
to its low cost and relative ease of fabrication as well as manipulation.51 3D printed molds are now widely used
to cast PDMS microchannels.52 In this simple approach, the same set of microfluidic channels is used for both
the immobilization of the surface chemistries as well as the analysis.
We used a Formlabs Form2 SLA 3D printer to create moulds supporting two parallel 300-micron-wide mi-
crofluidic channels separated by a 450-micron gap. These channels were used to deliver 1) the surface function-
alization chemistry, as well as 2) the samples containing the analytes. The microfluidics test setup is illustrated
in Fig. 7.
In the literature, several other strategies have been used to functionalize the surface of the biosensors so
that ligands are immobilized onto the surface to create active binding sites. Although bulk immersion of the
entire sensor array would be simple, this would not allow multiplex sensing chemistry. The most commonly used
method remains microfluidic masking, wherein different reagents are flowed through adjacent microchannels that
are positioned on top of the sensors. Washburn et al. functionalized microring sensors using flow-through mi-
crochannels created from a laser-cut Mylar gasket.53 A fluidic gasket has been used in the Genalyte system37, 54
for multiplex detection. While simple, challenges with microfluidic masking include the increasing complexity
with increasing number of sensors, and thus increasing functionalization chemistries, in an array used for mul-
tiplex sensing. The microfluidic channel or gasket layer may require a multi-layer design in order to deliver
Figure 7. Diagram (left) and image (right) of biosensor testing set-up. An acrylic washer is secured over the PDMS gasket,
sealing the microfluidic channels to the chip surface. The sensor chip sits in a machined recess in the aluminum base plate
to ensure proper alignment

an increased number of individually addressable locations to a sensor array. A multi-layer design, with smaller
channels near the sensor chip surface with fluidic vias to upper layers in the gasket with larger dimensions, may
be necessary to permit fan-out of the fluidic inlets and outlets for the flow-through design: inlet and outlet ports
typically comprise syringe needles with outer diameter in the range from 500 to 700 µm. The minimum practical
space from edge to edge of these fluidic interconnects would be in the range of 300 µm, especially as the needles
will be connected to tubing, while a realistic spacing would be in the range from 1 to 3 mm, thus necessitating
multi-layer gaskets for the fluidic interconnect for increasing numbers of individually addressable channels. Ad-
ditionally, the sealing footprint of the channels, to confine the different chemistries, may be a limitation as the
distance between sensors is decreased; readily achievable and robust sealing walls between channels may be on
the order of 400 µm as created using casting from 3D printed moulds, while the distance between sensors in an
array can easily be smaller.
Kirk et al. developed an inkjet approach55 for scalable, non-contact deposition of the functionalization
chemistries with high spatial precision. In this work, the microring resonators (30 µm in diameter) with ap-
proximately 200 µm centre-to-centre spacing, were successfully functionalized with printed spot precision around
5 µm. The piezoelectrically actuated inkjet dispenser can produce droplets in the range of 350 pL, and thus func-
tionalizing arrays of sensors can require only nanoliters of reagent. This contrasts favourably with the volumes
required for functionalization using flow-through microchannels, which can be in the range of tens to hundreds
of microliters.
The continuous flow microspotter system developed by Gale et al.56, 57 (Wasatch Microfluidics, now Carterra
Bio) features a network of microfluidic channels that can vertically print proteins onto a surface such as a SPR
sensor chip. Their 96-channel printhead permits simultaneous flow-based immobilization of up to 96 different
proteins. Each spot created using this continuous flow print head was a 250-µm square, and the spots are more
uniform compared to contact pin-printed spots. The continuous-flow microspotter approach compares favourably
to contact-pin and inkjet methods because the continuous-flow system permits recirculation to give high-density,
or high protein concentration, spots. The continuous flow also avoids the rapid drying that can cause protein
denaturation.
Bog et al. combined dip-pen nanolithography with a stamping approach,58 wherein a 2D array of ink spots is
first created using dip-pen nanolithography on a stamp pad to functionalize an array of whispering gallery mode
microgoblet cavities in parallel. This approach allowed the goblets, that had 100 µm center-to-center distance,
to have different functionalization chemistries.
Overall, reagent delivery into and out of biosensors has still required benchtop instrumentation59 in the
laboratory, with external pumps and valves to provide precise, controlled fluid and reagent delivery.60 Further
work will also consider the required sample preparation, and how to reduce or eliminate the need for pumps and
valves, possibly through the use of open-channel microfluidic capillary systems or digital microfluidic systems.
A truly portable biosensor will require optimization of the fluid handling, packaging, and electronics integration.
PCB

Reference
Power Supply

Sensor
Clock Generator

Analog Front End Digital Unit

DSP Interfacing
Differential Compute
Laser TIA ADC
Engine I2C

SRAM

LUT
Laser and Sensor BLE
Control Circuits

Silicon Photonic Chip CMOS Chip

Raw Curve Δ𝜆
Signal Fitting Extraction
Figure 8. Interfacing a low-cost fixed-wavelength silicon photonic sensors with CMOS electronics and external smart
devices

3.1.4 Electronics
Building the sensing electronics for an optical biosensor is dictated by the operating principle of the sensor. Fig. 8
illustrates a possible approach to interface a silicon photonic sensor with electronics and smart devices. Based
on an MRR circuit implementation, the surface or bulk interaction of the sensed substance with the exposed
sensing waveguide leads to a shift in the resonance wavelength of the ring which can be detected by the CMOS
electronics. To cancel the ambient noise and common mode drifts due to temperature or pressure variations,
another unexposed ring is used to provide a reference signal. The modulated optical signals from the sensor and
reference MRRs are guided to photodetectors (PDs). A differential trans-impedance amplifier (TIA) converts
the photocurrent to voltage which is then fed to an analog to digital converter (ADC). The bandwidth of the
TIA is a function of the modulation speed, which is typically ≤ 20 kHz, as well as the sensor’s surface binding
chemistry. The TIA must meet the gain, minimum input referred noise (IRN), and the linearity requirements
set by the subsequent stages. The TIA should provide enough gain to amplify the minimum detectable signal to
values equal or greater than the minimum least significant bit (LSB) of the ADC.
While iLoDb is optimized to improve the resolution of the detected signals, the noise contributed by the
PD, TIA and other analog front-end (AFE) circuits can also pose a limitation. The minimum overall detectable
signal of the biosensor should be above the overall noise floor at the input of the AFE. The desired current signal
is given by
∆IM DS = R∆PM DS (6)
where R and ∆PM DS are the photodetectors sensitivity to the signal’s optical wavelength and the minimum
intensity change due to the biosensors interaction with the measurands. The expression for noise at the input of
the AFE is given as:
iADC-irn
iAFE-noise = iPD-noise + iTIA-irn + (7)
ZTIA
where iPD-noise , iTIA-irn , iADC-irn and ZTIA stands for the current noise of the PDs, the input referred noise of the
TIA, the input referred noise (IRN) of the ADC and the TIA’s gain, respectivey. It can be concluded from (6)
that high transimpedance gain is desired to suppress the IRN for the upcoming stages. The noise floor can be
significantly reduced by averaging the signal over many cycles, and this averaging can be carried out digitally in
a digital signal processing (DSP) unit.
The DSP unit is also used to fit the measured spectral curve to a Lorentzian shape to extract the wavelength
shift from the Lorentzian minima. Using curve fitting relaxes the need for a highly linear AFE because the tails
of the measured curve experience less fluctuations over time which makes extracting the minima from the fitted
Lorentzian shape easier and more accurate. For such a processing scheme, an ADC of < 8 bits of quantization
can be shown to satisfy the need to detect < 1pm of wavelength shifts.
On-chip DSP is an integral part of detection in completely standalone point of care devices. However,
interfacing the biosensor chip with smart devices can enable off-loading the bulk of the DSP after transmission,
which can reduce the complexity of on-chip digital circuits. The Interfacing unit, as shown in Fig. 8, can either
use a wireline serial or a wireless Bluetooth transmission. For either case, a digital logic unit encapsulates the
data information extracted by the on-chip DSP into a serial protocol compliant data stream, which is then fed
to wireline drivers or radio-frequency (RF) circuits.

4. CONCLUSION
Since they were first commercialized by Genalyte, researchers in silicon photonic sensors have made great progress
exploring different sensor geometries and configurations, thereby improving performance metrics such as waveg-
uide sensitivity and limit of detection. Most silicon photonic sensors to date were based on passive optical chips,
where the only function implemented on-chip was evanescent field interaction with the analyte. Such designs do
not take advantage of the strengths of silicon photonics – integration. The instrumentation was implemented
off-chip using numerous costly and bulky components.
Silicon photonic circuits offer the potential of integrating all photonic and electronic functionality on a
chip. This could significantly reduce the bill of materials in sensor systems, and tilt the design trade-offs
away from the presently commercial approach of a low-cost sensor cartridge with an expensive instrument
(Fig. 4a), towards a slightly higher-cost complete-system disposable sensor (Fig. 4b). Our previous work aimed
at integrating germanium detectors on chip and solving the electrical fan-out issue;61, 62 however, the tunable
laser and the nanopositioners for coupling the optical fibres to the grating couplers remained. The work presented
in this manuscript proposes an alternative where the laser is integrated on-chip, and the tuning requirements are
transferred from the swept-tunable laser onto the silicon photonic circuit.
There remain several challenges in commercializing silicon photonic biosensors based on the presented fixed-
wavelength sensor:
The first challenge is in terms of the limit of detection. Sufficient sensitivity of silicon photonic biosensors
has been demonstrated for virus detection: previous work has successfully detected the Herpes simplex virus
(96 MDa, Young interferometer, 850 viral particles/mL)63 and bean pod mottle virus (7 MDa, Micro-Ring
Resonators, 10 ng/mL).64 However, a high sensitivity (or low limit of detection), i.e., a low false negativity, is
dependent not only on the biosensor transducer architecture but also on sample collection, sample preparation,
and the chemistry that provides the functionalization of the sensor surface.
Second, in order for sensors to be widely deployed, a high specificity, i.e., low false positivity, will be important.
This can be achieved by using a multiplexed sensor for several biomarkers that generates multidimensional data
and a unique signature for analytes. Multiplexing will contribute to confidence in the sensor result, paving the
way for wide uptake and acceptance. In this proposed approach, a single laser can power 2M sensors using a
splitter tree; the number of sensors on a chip will be limited by a) the available optical power budget (laser
power, required optical power at the detector), b) and the spacing of the sensors in the array (limited by the
functionalization chemistry printing process). While the presented design uses 24 = 16 sensors, it should be
possible to design a 256 sensor chip while meeting the above constraints. Alternatively, the sensor could use
active switching and time-division multiplexing to increase the number of sensors.
Finally, cost is a key factor contributing to wide deployment of these sensors. While the swept-tunable laser
was the most expensive component in passive-only sensor chip architectures, it can be eliminated by using a
fixed laser, which will play a significant role in lowering the cost of the biosensor. The next important cost
reduction to consider is in the microfluidics assembly. Solving these problems should enable small form-factor
sensor systems, with a tight integration of all functionality – lasers, silicon photonics, electronics, microfluidics,
and chemistry.

ACKNOWLEDGMENTS
This research was supported by the Natural Sciences and Engineering Research Council of Canada, Canada’s
Digital Technology Supercluster, and the SiEPICfab consortium, http://www.siepic.ca/fabrication. We
thank Applied Nanotools for fabricating prototype sensor chips for this work, MACOM for providing the lasers,
Hossam Shoman for design review, and Loic Laplatine and Justin Bickford for feedback and discussions.

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