No abstract

Photonic integration has seen tremendous progress over the previous decade, and several integration platforms have reached industrial maturity. This evolution has prepared the ground for miniaturized photonic sensors that lend themselves to efficient analysis of gaseous and liquid media, exploiting large interactions lengths of guided light with surrounding analytes, possibly mediated by chemically functionalized waveguide surfaces. Among the various sensor concepts, phase-sensitive approaches are particularly attractive: offering a flexible choice of the operation wavelength, these schemes are amenable to large-scale integration on mature technology platforms such as silicon photonics or silicon nitride ( S i 3 N 4 ) that have been developed in the context of tele- and data-communication applications. This paves the path toward miniaturized and robust sensor systems that offer outstanding scalability and that are perfectly suited for high-volume applications in life sciences, industrial process analytics, or consumer products. However, as the maturity of the underlying photonic integrated circuits (PICs) increases, system-level aspects of mass-deployable sensors gain importance. These aspects include, e.g.,  robust system concepts that can be operated outside controlled laboratory environments as well as readout schemes that can be implemented based on low-cost light sources, without the need for benchtop-type tunable lasers as typically used in scientific demonstrations. It is, thus, the goal of this tutorial to provide a holistic system model that allows us to better understand and to quantitatively benchmark the viability and performance of different phase-sensitive photonic sensor concepts under the stringent limitations of mass-deployable miniaturized systems. Specifically, we explain and formulate a generally applicable theoretical framework that allows for a quantitatively reliable end-to-end analysis of the overall signal chain. Building upon this framework, we identify and explain the most important technical parameters of the system, comprising the photonic sensor circuit, the light source, and the detector, as well as the readout and control scheme. We quantify and compare the achievable performance and the limitations that are associated with specific sensor structures based on Mach–Zehnder interferometers (MZIs) or high-Q optical ring resonators (RRs), and we condense our findings by formulating design guidelines both for sensor concepts. As a particularly attractive example, we discuss an MZI-based sensor implementation, relying on a vertical-cavity surface-emitting laser (VCSEL) as a power-efficient low-cost light source in combination with a simple and robust readout and control scheme. In contrast to RR-based sensor implementations, MZIs can be resilient to laser frequency noise, at the cost of a slightly lower sensitivity and a moderately increased footprint. To facilitate the application of our model, we provide a MATLAB-based application that visualizes the underlying physical principles and that can be readily used to estimate the achievable performance of a specific sensor system. The system-level design considerations are complemented by an overview of additional aspects that are important for successful sensor system implementation such as the design of the underlying waveguides, photonic system assembly concepts, and schemes for analyte handling.

Waveguide-based biochemical sensors exploit detection of target molecules that bind specifically to a functionalized waveguide surface. For optimum sensitivity, the waveguide should be designed to mediate maximum influence of the surface layer on the effective refractive index of the guided mode. In this paper, we define a surface sensitivity metric which quantifies this impact and which allows to broadly compare different waveguide types and integration platforms. Focusing on silicon nitride and silicon-on-insulator (SOI) as the most common material systems, we systematically analyze and optimize a variety of waveguide types, comprising simple strips, slot and double slot structures, as well as sub-wavelength gratings (SWG). Comparing the highest achievable surface sensitivities, we provide universal design guidelines and physically interpret the observed trends and limitations. Our findings allow to select the appropriate WG platform and to optimize sensitivity for a given measurement task.

Early and efficient disease diagnosis with low-cost point-of-care devices is gaining importance for personalized medicine and public health protection. Within this context, waveguide-(WG)-based optical biosensors on the silicon-nitride (Si3N4) platform represent a particularly promising option, offering highly sensitive detection of indicative biomarkers in multiplexed sensor arrays operated by light in the visible-wavelength range. However, while passive Si3N4-based photonic circuits lend themselves to highly scalable mass production, the integration of low-cost light sources remains a challenge. In this paper, we demonstrate optical biosensors that combine Si3N4 sensor circuits with hybrid on-chip organic lasers. These Si3N4-organic hybrid (SiNOH) lasers rely on a dye-doped cladding material that are deposited on top of a passive WG and that are optically pumped by an external light source. Fabrication of the devices is simple: The underlying Si3N4 WGs are structured in a single lithography step, and the organic gain medium is subsequently applied by dispensing, spin-coating, or ink-jet printing processes. A highly parallel read-out of the optical sensor signals is accomplished with a simple camera. In our proof-of-concept experiment, we demonstrate the viability of the approach by detecting different concentrations of fibrinogen in phosphate-buffered saline solutions with a sensor-length (L-)-related sensitivity of S/L = 0.16 rad nM−1 mm−1. To our knowledge, this is the first demonstration of an integrated optical circuit driven by a co-integrated low-cost organic light source. We expect that the versatility of the device concept, the simple operation principle, and the compatibility with cost-efficient mass production will make the concept a highly attractive option for applications in biophotonics and point-of-care diagnostics.