Abstract
Chemical sensors based on metal oxides (MOx) are one of the most promising gas sensing devices due to their high sensitivity to numerous gases, fast response, miniaturization, and simple production. The detection principle of these sensors is a conductivity change of the MOx-sensing material due to the chemical reactions of gases with surface molecules. Cross sensitivities and interference to humidity, however, are still significant drawbacks of these sensors. The functionalization of MOx-sensing films with catalytic nanoparticles (NP) is a highly promising technology for optimizing sensor performance. The huge variety of potential MOx–NP combinations requires efficient screening technologies to find proper hybrid material mixtures which enable the controlled adjustment of the sensor response to specific target gases. This is of high importance for the realization of a multi-gas sensor device capable of the clear discrimination of single gas components from a gas mixture. In this work we introduce our approach for the efficient screening of hybrid MOx–NP material combinations. We have developed a specific Si-platform chip along with a gas measurement setup which enables the simultaneous characterization of 16 chemical sensor structures in parallel. The Si-chips feature an array of Ti/Pt electrodes for contacting ultrathin MOx-sensing films, which are deposited by spray pyrolysis, and structured by photolithography to a size of 50 × 100 µm2. On these platform chips we tested three different MOx (SnO2, ZnO, and CuO) before and after functionalization with mono- and bimetallic NPs (such as Au, Pt, Pd, and NiPt) on several test gases (CO, HCmix, toluene, CO2). Measurements were performed in a background gas of synthetic air at different relative humidity levels (25–75%) and at different operating temperatures up to 350 °C. We present the sensing performance results of various MOx-NP combinations, exhibiting an optimized response to specific target gases.
Author Contributions
Conceptualization, L.E., F.S.-L. and A.K.; methodology: L.E., A.K., J.S.N. and M.T; Formal analysis, F.S.-L., L.R. and L.E.; Investigation, F.S.-L. and L.R.; Resources, H.S., J.S.N., S.B., Ö.T., M.T., A.B. and K.P.; Writing—original draft, L.E.; Writing—review & editing, L.E. and A.K. All authors have read and agreed to the published version of the manuscript.
Funding
This project has received funding from the ECSEL Joint Undertaking (JU) under grant agreement No 876362. The JU receives support from the European Union’s Horizon 2020 research and innovation programme and Austria, Belgium, Czech Republic, Finland, Germany, Italy, Latvia, Netherlands, Poland, Switzerland.
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Data Availability Statement
Not applicable.
Acknowledgments
The authors gratefully acknowledge the financial support under the scope of the COMET program within the K2 Center “Integrated Computational Material, Process and Product Engineering (IC-MPPE)” (Project No. 886385). This program is supported by the Austrian Federal Ministries for Climate Action, Environment, Energy, Mobility, Innovation and Technology (BMK) and for Digital and Economic Affairs (BMDW), represented by the Austrian Research Promotion Agency (FFG), and the federal states of Styria, Upper Austria and Tyrol.
Conflicts of Interest
The authors declare no conflict of interest.
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