Technology Overview

This technology offer presents a chip-scale mid-infrared (MIR) spectroscopic sensor based on the integration of silicon-on-calcium fluoride (SOCF) waveguide sensor and graphene photodetector. The sensor can discriminate and quantify numerous chemical and biological molecules in a label-free and surface-functionalization-free manner through their absorption fingerprints in the MIR spectrum. The waveguide-integrated photodetector on-chip converts optical sensing signal to electrical signal, which can be directly collected for analysis. Our device can be employed for various in-situ chemical and bio-sensing applications (such as environmental monitoring, industrial process control, medical diagnostics, etc.) and further, the construction of internet of things (IoT) sensor networks.

Technology Features, Specifications and Advantages

This technology realizes the world’s first chip-scale photodetector-integrated sensor in the MIR beyond 4 μm, a spectral range that extensively overlaps with the absorption fingerprints of most chemical and biological molecules. This is enabled by the synergy between a high-yield transfer printing method and graphene photodetectors. The former flexibly integrates waveguide and substrate materials, thus solves the bottom cladding absorption limitation in conventional waveguide platforms and provides broadband low losses. The latter possess broadband photoresponse across the whole IR range and layered lattice structure easing their direct integration with waveguides. Molecules and their mixtures can be conveniently identified and quantified in real-time by tracking their absorption fingerprint wavelengths, without the need for molecule labeling and sensor surface functionalization. As a proof-of-concept, on-chip detection of toluene, a typical volatile organic compound (VOC) with massive usage in chemical industries and indicative property for lung cancer, has been successfully demonstrated with the lowest limit of detection (LoD) among reported on-chip MIR sensors. The sensor would have broad applicability in MIR spectroscopic sensing due to its broadband behavior and the inherent selectivity of MIR absorption spectroscopy. The chip-scale, low-cost, and low-power-consumption features enable massive in-situ deployment of this sensor for diversified IoT sensing applications.

Potential Applications

The sensor can discriminate and quantify numerous chemical and biological molecules and their mixtures on-chip, as long as they register absorption fingerprints within the broad MIR working wavelength range of our sensor. Thus, the sensor can be potentially adopted in widespread IoT chemical and bio-sensing applications including but not limited to the following:

• Environmental monitoring. For example, the detection of various greenhouse gases, such as CO₂, CH₄, N₂O, etc.; and the monitoring of air quality, such as formaldehyde in the home.
• Industrial process control. Many chemicals have wide industrial use and may cause severe pollution and accidents if not well monitored and controlled.
• Healthcare and medical diagnostics. For example, detection of the volatile organic compound (VOC) biomarkers in exhaled breath has been a non-invasive, rapid, in-situ, and easy-to-use diagnostic method for many diseases, such as toluene for lung cancer, ethyl butanoate for COVID-19, etc.

Customer Benefit

The chip-scale integration minimizes the sensor size, cost, and power consumption. Thanks to the CMOS compatibility, the sensor could be potentially mass-produced in wafer-scale with low cost. The graphene photodetector is designed to work at zero bias, which further reduces the power consumption. The chip-scale, low-cost, and low-power-consumption features allow the sensor to be massively deployed in-situ. Meanwhile, the broadband behavior and the inherent selectivity of MIR absorption spectroscopy enable our sensor with versatile sensing capabilities, which enlarges the application scenarios and reduces the deployment cost. All the above-mentioned advantages benefit the construction of IoT sensor networks for the realization of smart home, smart industry, and smart city.