(Invited) Quantitative Decoding of Complex Gas Mixtures for Environmental Monitoring Using Mixed-Potential Sensors

Vehicle manufactures are pursuing selective catalyst reduction (SCR) and exhaust gas recirculation (EGR) systems to meet EPA emissions regulations for lean-burn engines. Exhaust gas sensors are needed to monitor emissions and control and maintain efficient operation of these systems. Oxygen λ-sensors are in integral part of OBD of today’s spark-ignition vehicle emission systems, but a suitable analog is not available for NO_x, NH₃ and NMHC detection and discrimination in lean-burn engines. Mixed-potential sensors fabricated via well-established commercial manufacturing methods present a promising avenue to enable the widespread utilization of NO_x, NH₃ and NMHC sensing technology. These electrochemical devices develop a non-Nernstian potential due to differences in the redox kinetics of various gas species at each electrode/electrolyte/gas interface. The electrode potential is not fixed by equilibrium thermodynamics as it is in the O₂ l-sensor, but rather by the rates of different electrochemical reactions occurring simultaneously at each electrode/ electrolyte interface. Therefore, device-to-device reproducibility of the triple phase interface, as well as long term morphological stability are required. The patented LANL sensor design incorporates dense electrodes and a porous electrolyte (1). The use of dense electrodes minimizes deleterious heterogeneous catalysis, and the increased morphological stability of dense electrodes yields a robust electrochemical interface, increasing lifetime durability (2). The Materials Synthesis and Integrated Devices group at LANL has worked in collaboration with Electro-Science Laboratories (ESL, King of Prussia, PA) to fabricate planar mixed-potential sensors via the readily scalable, cost-effective high temperature co-fired ceramic (HTCC) technology already employed in the manufacturing of planar O₂ λ-sensors.

We have developed two distinct sensing platforms for NO_x and NH₃ detection. The NO_x sensor consists of La_1-xSr_xCrO₃ and Pt electrodes. Under open circuit conditions, this sensor responds to many of the constituents of concern in emissions monitoring, however, the selectivity may be tuned by operating conditions (3). By operating at a small positive current bias, this sensor becomes preferentially selective to NO_x species.  Selectivity towards non-methane hydrocarbons (NMHC) is improved by operation at elevated temperatures, however sensitivity is reduced. The NH₃ sensor consists of Au/Pd and Pt electrodes and is minimally sensitive to NO_xspecies with varying sensitivity to NMHCs depending on operating temperature. While these devices exhibit preferential selectivity to target analytes, a single device with absolute selectivity remains elusive.  The work herein presents an alternative strategy to absolute selectivity in which the cross-sensitivity of varying sensor elements at varying operating conditions is exploited through the use of Bayesian inference predictive algorithms based on physical models of sensor-analyte interactions.   

We have previously shown that the individual concentration of individual analyte species can be uniquely determined from a mixtures of two gases based on the sensor voltage response of a single sensor operating at four different current bias points by employing a Bayesian interference model(4).  In this work, we seek to expand our proof-of-concept demonstration to uniquely identifying the concentration of NO, NO₂, NH₃, and C₃H₆ in complex mixtures relevant to diesel exhaust. In this study we are employing two different sensors, the aforementioned LSCr|YSZ|Pt and Au|YSZ|Pt planar sensor devices, operating at multiple temperatures.  Sensor voltage response data collected on a wide range of mixing ratios are used to train the Bayesian model. Complex mixtures not used in the training set will be used to test the accuracy of the model. This research represents the first stages of developing miniaturized mixed-potential electrochemical sensor (MPES) arrays as an all-in-one NO_x/NH₃/NMHC sensor package that will provide quantitative emissions monitoring and onboard diagnostics (OBD) for all lean-burn engine applications. The MPES arrays have potential to be used in Environmental monitoring of complex gas mixtures. The characteristics of micro-systems that are required to realize the potential of MPES arrays will be discussed and preliminary results to realize these concepts will be presented.

Acknowledgements

The research was funded by the Los Alamos National Laboratory Directed Research Development Exploratory Research program.

References

1.         R. Mukundan, E. L. Brosha, F. H. Garzon, US 7,575,709 (2009).

2.         R. Mukundan, E. L. Brosha, F. H. Garzon, Journal of The Electrochemical Society 150, H279 (2003).

3.         C. R. Kreller, P. K. Sekhar, W. Li, P. Palanisamy, E. L. Brosha, R. Mukundan, F. H. Garzon, ECS Transactions 50, 307-314 (2012).

4.         J. Tsitron, C. R. Kreller, P. K. Sekhar, R. Mukundan, F. H. Garzon, E. L. Brosha, A. V. Morozov, Sensors and Actuators B: Chemical 192, 283-293 (2014).