Quantifying nitrogen oxides and ammonia via frequency modulation in gas sensors

The use of Silicon Carbide Field Effect Transistor (SiC-FET) sensors in cyclic operation is a proven way to quantify different gases. The standard workflow involves extracting shape-defining features such as averages and slopes of the sensor signal. This work’s main goal is to verify if frequency modulation can be used to simultaneously quantify Nitric Oxide (NO), Nitrogen Dioxide (NO2) and Ammonia (NH3). Linear models were chosen, namely: Ordinary Least Squares (OLS), Principal Components Regression (PCR), Partial Least Squares Regression (PLSR) and Ridge regression. Results indicate that these models fail to predict concentrations completely for every gas. Analysis indicates that the features are not linear in terms of concentrations. This work is concluded by recommending a few other alternatives before discarding frequency cycling completely: non-parametric models of regression and different frequency regime, namely the use of triangular waves in future experiments.