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Smart sensing / Data mining

In collaboration with Prof. Andreas Schütze at Saarland University in Saarbrücken, Germany, smart sensor operation of SiC-FETs and advanced data evaluation are developed. Cycling of the operation temperature and of the applied gate bias together with smart data evaluation largely improve the information from SiC-FET sensors. Interesting results have been obtained like simultaneous quantification of both NO and NO2 in a (varying) mixture of synthetic exhaust.

This research project has been run by two joint PhD students, Christian Bur (PhD defense on April 2015) and Manuel Bastuck, at both Saarland and Linköping Universities within the research school DocMASE.

Figure: Linear discriminant analysis (LDA) showing the discrimination of four different concentrations of CO, NO2 and NH3 in a mixture of all three in 5% oxygen in nitrogen using a Pt-gated SiC-FET sensor in temperature and bias cycled operation (C. Bur et al., Sens. Actuat. B-Chem., 193 (2014) 931-940)


Responsible for this page: Donatella Puglisi

Last updated: 03/10/17