The influence of SO2 and the thickness of the sensitive layer on the performance of the Integrating NOx Sensor

Titelangaben

Groß, Andrea ; Hanft, Dominik ; Richter, Miriam ; Beulertz, Gregor ; Kubinski, David J. ; Visser, Jacobus H. ; Moos, Ralf:
The influence of SO2 and the thickness of the sensitive layer on the performance of the Integrating NOx Sensor.
2012
Veranstaltung: 14th International Meeting on Chemical Sensors - IMCS 2012 , 20.-23.05.2012 , Nürnberg, Germany.
(Veranstaltungsbeitrag: Kongress/Konferenz/Symposium/Tagung , Sonstige Präsentationstyp)
DOI: https://doi.org/10.5162/IMCS2012/5.2.2

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Abstract

Due to its chemical accumulation abilities, the integrating NOx sensor is potentially well suited for low ppm-level sensing of NO and NO2. The sensitive layer consists of a potassium-based automotive lean NOx trap (LNT) catalyst storing NOx chemically by forming nitrates. The accumulative sensing principle and the NOx concentration detection properties have been published recently.

Now, two factors influencing the sensing performance are addressed: Sulfur poisoning and the thickness of the sensitive layer. The measurement results reveal that the competition between SO2 and NO2 for the available storage sites, known from LNT catalysts, affects the sensor signal in two ways: First, the resistance of the sensitive layer (even without NOx) decreases in the presence of SO2 (sulfate formation), allowing for integrative SO2 detection. Secondly, the linear NOx measurement range decreases due to a diminished NOx storage capacity upon SO2 blocking the storage sites. A high reversibility of sulfur poisoning was obtained by desulfation at 650 °C in H2 containing gas. The resistance in the unloaded state was found to correlate with the inverse thickness of the LNT layer. More relevant, the thickness was found to highly influence the sensitivity and the linear measurement range of the integrating NOx sensor. Therefore, variations in the thickness are an effective tool to adapt the sensor performance (sensitivity and linear measurement range) to the application requirements without loosing the benefits of the integrating sensing principle.