ULISSES

01/01/2019 – 30/06/2023
Grant agreement ID: 825272

Henrik Rödjegård
Coordinator,  Senseair

DOI: Parhizkar, S., Prechtl, M., Giesecke, A. L., et al. (2022), Two-Dimensional Platinum Diselenide Waveguide-Integrated Infrared Photodetectors. ACS Photonics acsphotonics.1c01517. 

DOI: Jo, G., Edinger, P., Bleiker, S. J., et al. (2022), Wafer-level hermetically sealed silicon photonic MEMS. Photonics Research 10, A14.

DOI: Lemme, M. C., Akinwande, D., Huyghebaert, C., Stampfer, C. (2022), 2D materials for future heterogeneous electronics. Nature Communications 13, 1392.

DOI: Antidormi, A. & Cummings, A. W. All-carbon approach to inducing electrical and optical anisotropy in graphene. AIP Advances 11, 115007.

DOI: Prechtl, M., Parhizkar, S., Hartwig, O., et al. (2021), Hybrid Devices by Selective and Conformal Deposition of PtSe 2 at Low Temperatures. Advanced Functional Materials 2103936.

DOI: Canto, B., Otto, M., Powell, M. J., et al. (2021), Plasma-Enhanced Atomic Layer Deposition of Al 2 O 3 on Graphene Using Monolayer hBN as Interfacial Layer. Advanced Materials Technologies 2100489.

DOI: Lukas, S., Hartwig, O., Prechtl, M., et al. (2021), Correlating Nanocrystalline Structure with Electronic Properties in 2D Platinum Diselenide. Advanced Functional Materials 2102929.

DOI: Parhizkar, S., Prechtl, M., Giesecke, A. L., et al. (2021), Waveguide-Integrated Photodetectors based on 2D Platinum Diselenide. Device Research Conference (DRC) 1–2 (IEEE, 2021).

DOI: Antidormi, A. & Cummings, A. W. Optimizing the Photothermoelectric Effect in Graphene. Physical Review Applied 15, 054049.

Ultra low-power integrated optical sensor systems for networked environmental multichannel gas Sensing

The ULISSES project specializes at realizing miniaturized, low-power, networked gas sensors for distributed air quality monitoring. Compared to the existing sensors, which are too bulky and expensive, ULISEES wants to develop the optical gas sensors with the highest sensitivity, stability, and specificity considering the cost effectiveness of the technology.

ULISSES brings together three academic institutions with five companies contributing to the project with their expertise and resources. The ULISSES consortium is building an integrated optical gas sensor and the networking technology required to bring it onto the Internet of Things (IoT). By leveraging mid‏-IR waveguide-based gas sensing, 2D materials-based photodetectors, and nanowire mid-IR emitters, project partners target a low-power optical gas sensor for maintenance-free battery-powered operation. Hence, ULISSES will deliver the mass production methods necessary to produce volumes of millions of sensors per year, with a dramatic reduction of the sensor cost. Finally, a new edge-computed self-calibration algorithm will be presented.

With such a dense mesh of mobile sensors measuring the quality of the air in real time that ULISSES is aiming to bring to the market, people will make better informed decisions in their everyday life. This will further lead to the improved air quality in cities and health of citizens in the long run.

Good air is important for our health, and air quality in cities varies dramatically in time and from one block to another. A dense mesh of mobile sensors measuring the quality of the air in real time would help us make informed decisions in our everyday life and improve air quality in the long run. Optical gas sensors offer the highest sensitivity, stability, and specificity, but the existing sensors are too bulky and expensive. The ULISSES project aims at realizing miniaturized, low-power, networked gas sensors for distributed air quality monitoring.

In ULISSES, we are developing an integrated optical gas sensor and the networking technology required to bring it onto the Internet of Things (IoT). By leveraging mid‏-IR waveguide-based gas sensing, 2D materials-based photodetectors, and nanowire mid-IR emitters, we target a low-power optical gas sensor for maintenance-free battery-powered operation. ULISSES will also deliver the mass production methods necessary to produce volumes of millions of sensors per year, with a dramatic reduction of the sensor cost. Finally, we will develop a new edge-computed self-calibration algorithm leveraging node-to-node communication and demonstrate air quality monitoring with a network of Cloud-connected mobile sensors on taxis.