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New process developments linked to Power to X (energy storage or energy conversion to another form of energy) require tools to perform process monitoring. The main gases involved in these types of processes are H2, CO, CH4, and CO2. Because of the non-selectivity of the sensors, a multi-sensor matrix has been built in this work based on commercial sensors having very different transduction principles, and, therefore, providing richer information. To treat the data provided by the sensor array and extract gas mixture composition (nature and concentration), linear (Multi Linear Regression—Ordinary Least Square “MLR-OLS” and Multi Linear Regression—Partial Least Square “MLR-PLS”) and non-linear (Artificial Neural Network “ANN”) models have been built. The MLR-OLS model was disqualified during the training phase since it did not show good results even in the training phase, which could not lead to effective predictions during the validation phase. Then, the performances of MLR-PLS and ANN were evaluated with validation data. Good concentration predictions were obtained in both cases for all the involved analytes. However, in the case of methane, better prediction performances were obtained with ANN, which is consistent with the fact that the MOX sensor’s response to CH4 is logarithmic, whereas only linear sensor responses were obtained for the other analytes. Finally, prediction tests performed on one-year aged sensor platforms revealed that PLS model predictions on aged platforms mainly suffered from concentration offsets and that ANN predictions mainly suffered from a drop of sensitivity.

Electrochemical sensors have been used for many decades. However, the modeling of such sensors used in electrolysis mode is poorly documented, especially in the case of multiple gases’ parallel actions. These are of great interest since they constitute the first brick to bring information on the natures and concentrations of gaseous mixture compositions, thanks to gray box modeling of sensor arrays, for example. Based on Butler–Volmer’s equations, a model assuming parallel reactions at gold cathode has been introduced in this article and confronted with experimental results. The establishment of the model is based on the extraction of three variables: the charge transfer coefficient “α”, the reaction order γ, and the reaction constant rate k0. Tests performed without pollutants and with different concentrations of oxygen could be nicely fitted using the model. The influence of the polarization current on the three variables of the model has been evaluated, showing a clear influence on the constant rate and the reaction order. Moreover, increasing the polarization current enabled us to obtain selectivity for oxidant gases. Similarly, the effect of the oxygen concentration was evaluated. Results showed that, in this case, the charge transfer coefficients “α” obtained for oxidant gases are quite different from the ones obtained in the polarization current varying conditions. Therefore, the model will be interesting in situations where polarization current and oxygen content are not varied together. Variation of polarization current can be quite interesting to obtain increased information for multivariate analysis purposes in constant oxygen content situations. Additionally, other parameters have to be considered for applications in which the oxygen content is bound to change, such as exhaust gases or combustion.

Electrochemical NOx sensors based on yttria-stabilized zirconia (YSZ) provide a reliable onboard way to control NOx emissions from glass-melting furnaces. The main limitation is the poisoning of this sensor by sulfur oxides (SOx) contained in the stream. To overcome this drawback, an “SO2 trap” with high SOx storage capacity and low affinity to NOx is required. Two CuO/BaO/SBA-15 traps with the same CuO loading (6.5 wt.%) and different BaO loadings (5 and 24.5 wt.%, respectively) were synthetized, thoroughly characterized and evaluated as SO2 traps. The results show that the 6.5%CuO/5%BaO/SBA-15 trap displays the highest SO2 adsorption capacity and can fully adsorb SO2 for a specific period of time, while additionally displaying a very low NO adsorption capacity. A suitable quantity of this material located upstream of the sensor could provide total protection of the NOx sensor against sulfur poisoning in glass-furnace exhausts.

Ammonia detection at ambient with low-cost sensors is a challenge for various applications like breath analysis and agriculture. Such a challenge can be reached with functionalized SnO2 based gas sensors using silanization by 3-aminopropyltriethoxysilane (APTES) as an intermediate step before grafting with functional end group providing selectivity for the target gas. Moreover, operation at room temperature gives the opportunity to develop a sensor on a plastic substrate entirely manufactured by inkjet technology, by developing suitable inks, in particular to obtain SnO2 sensing element.

Mixed potential ammonia gas sensors were fabricated by using two sensing materials of Ni3V2O8 and Au-V2O5 as working electrodes, YSZ as electrolyte and platinum as reference electrode. The results have shown that the Ni3V2O8 sensors show cross-sensitivity toward NO gas. However, Au-V2O5 working electrodes displayed a high sensitivity to NH3 as well as fast response and recovery times at high temperatures. Furthermore, the results indicate that the selectivity of Au-V2O5 sensors increases by increasing temperature.

In this work, a flexible tin oxide (SnO2) gas sensor was successfully fabricated by inkjet printing technology. This thin film deposition technique requires the formulation of stable suspensions with specific fluidic properties. Aqueous Sol-gel method was applied to synthesize a stable sol based on tin oxide, then transformed into ink with the appropriate viscosity and surface tension to be printed using a drop-on-demand piezoelectric inkjet printer. Thermal analyses of synthetized sol show that a crystallized structure of SnO2 could be obtained at 350 °C, which is lower than crystallization temperatures of SnO2 previously reported in the literature, and entirely consistent with our plastic substrate. The printed thin-film was then sintered at 350 °C on polyimide foil (Upilex-50S) and characterized as sensor.

The development of selective and cheap metal oxide gas sensor at ambient temperature is still a challenging idea. In this study, SnO2 surface functionalization was performed in order to obtain sensitive and selective gas sensor operated at ambient temperature. 3-aminopropyltriethoxysilane (APTES) was used as an intermediate step, followed by functionalization with molecules having acyl chloride with different end functional groups molecules such as alkyl, acid and ester groups. Acid and ester modified sensors are sensitive to ammonia between 0.2 and 10 ppm at room temperature. However, ester modified SnO2 is more selective than acid modified sensor regarding ethanol and carbon monoxide gases.

Among all NOx reduction approaches, selective catalyst reduction (SCR) system is one the most reliable ways to control NOx emissions from diesel engine vehicles and trucks. In order to optimize the conversion rates of NOx and to prevent inducing excessive NH3 to the air, an NH3 and NOx sensor is required. In this study, three different types of YSZ ink have been examined to identify the most effective electrolyte for NOx and NH3 sensing. The results have shown that a home-made ink with YSZ powder shows the best sensitivity towards ammonia without polarization and the highest NO2/NO signal ratio with polarization current of 25 nA.

Sol based SnO2 precursor was synthetized by aqueous sol-gel route, then transformed into a stable ink with appropriate viscosity and surface tension to be inkjet printed and sintered at relatively moderate temperature. Plastic foil with thickness of 50 μm was selected as substrate for its high thermal resistance and stability (Upilex-50S). Prepared sol and formulated ink were both characterized by analytical techniques; electrical measurements were performed on the printed sensing film to characterize the response to CO gas in different concentrations, at working temperature of 300 °C.