Development of a new Mobile Gas Sensing Technology aiming at distributed and networked mobile gas sensing for industrial, safety, and environmental monitoring applications.
Collaboration Aims to Develop a New Class of Miniaturized Optical Gas Sensors on a Chip, Enabling Low-Cost Distributed Sensing Nodes for the Internet of Things.
AMO GmbH, Senseair AB, KTH Royal Institute of Technology, Oxford Instruments Plasma Technology Ltd, Graphenea Semiconductor SL, Universität der Bundeswehr München, Catalan Institute of Nanoscience and Nanotechnology, and SCIPROM Sàrl announced today the launch of the ULISSES project, a European collaboration to develop a new class of miniaturized optical gas sensors on a chip. The project partners will collaborate to combine silicon photonics with 2D materials, to enable fully integrated optical gas sensing nodes for the Internet of Things (IoT) that can be manufactured in large volumes at low cost and achieve performance improvements in terms of size and power consumption. The development would enable personal gas sensors embedded in wearable devices, as well as installed in public infrastructure, such as in street lighting, on busses and in taxis, or even in small unmanned aerial vehicles. The new technology aims to empower the general public to monitor and put demands on their air quality.
Gas sensors are already widely used in industry and agriculture, to ensure safety of personnel and to monitor and automate processes. However, the rising general awareness of the importance of urban indoor and outdoor air quality is now driving demand for accurate, low-cost and mobile gas sensor technology. Optical gas sensors offer the highest sensitivity, stability and specificity in the market, however, their current cost, power consumption and size hinder them from being widely employed by the general public. ULISSES technology will enable compact, low-cost and low-power gas sensor nodes to be networked for comprehensive and real time monitoring of air quality in urban areas. This new approach will provide valuable information to city planners, employers and landlords to ensure a healthy indoor and outdoor environment.
By leveraging recent breakthroughs of the ULISSES partners on waveguide integrated 2D materials-based photodetectors, 1D nanowire mid-IR emitters, and mid-IR waveguide-based gas sensing, ULISSES targets a three-order-of-magnitude reduction in sensor power consumption, thus permitting maintenance-free battery powered operation for the first time. Furthermore, ULISSES will implement a new edge-computing self-calibration algorithm that leverages node-to-node communications to eliminate the main cost driver of low-cost gas sensor fabrication and maintenance.
AMO Director and RWTH Aachen University Professor Max Lemme looks forward to ULISSES: “This is a wonderfully challenging European project exactly in line with AMO’s mission to develop future Digital Hardware and to bring such new materials and technologies closer to applications. The project also fits very well into the range of activities of the Aachen Graphene & 2D Materials Center, set up between AMO GmbH and RWTH Aachen University.” Lemme adds: “We are excited to work with our partners on this endeavor because it has the potential to ultimately improve the quality of life for every citizen!“
Over the next 4 years, AMO will fabricate silicon photonics chips with integrated silicon waveguides and 2D material-based photodetectors, developed by KTH and AMO. The project is coordinated by Senseair AB, a leading gas sensor supplier, supported by SCIPROM. Oxford Instruments Plasma Technology will further develop its nanotechnology process tools. The 2D materials will be provided by the Universität der Bundeswehr München and Graphenea. Senseair will lead the different application demonstrators and prepare the sensors for IoT applications. ICN2 will provide modelling and simulation, in order to optimize sensor design and efficiency.
For more information on ULISSES, please visit www.ulisses-project.eu.
The ULISSES project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 825272 (ULISSES).