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Evans, Lindsey

Publications and source records attributed to Evans, Lindsey.

18 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Automatic signal decoding and sensor stability of a 3-electrode mixed-potential sensor for NO x /NH 3 quantification

Sensors to detect mixtures of NO x /NH 3 are needed to monitor emissions of diesel automobiles where a selective catalytic reduction system uses an NH 3 mediated reaction to reduce NO x . We report on the application of a three electrode La 0.8 Sr 0.2 CrO 3 , Au 0.5 Pd 0.5 , Pt mixed potential sensor using yttria-stabilized-zirconia (YSZ) as a solid electrolyte to NO x /NH 3 sensing. Artificial neural networks were used to automatically decode the concentrations of NO x /NH 3 and errors of less than 15% are achieved. The optimal architecture for ANN decoding and the maximum density of training data points are also determined. The stability of the sensor was monitored by electrochemical impedance spectroscopy. The impedance associated with YSZ oxygen ion conduction and the electrochemical reactions at the three-phase interface are tracked for a period of over 100 days.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Additively manufactured mixed potential electrochemical sensors for NO x , C 3 H 8 , and NH 3 detection

Additive manufacturing of mixed potential electrochemical sensors opens the possibility to perform rapid prototyping of electrode and electrolyte materials. We report for the first time the use of this technique for the fabrication of solid-state electrochemical gas sensors of the mixed potential type and assessment of variability in the manufacturing process. La 0.87 Sr 0.13 CrO 3 (LSCO) and Pt electrodes bridged with a porous yttria-stabilized zirconia (YSZ) have been deposited on YSZ substrates by direct-write extrusion of pastes and inks. The sensors are evaluated for their sensitivity to 200 ppm of NO x , C 3 H 8 , and NH 3 . There is a need to understand how variations in intrinsic materials parameters during manufacturing such as differences in porosity affect the gas sensing of additively manufactured sensors to guide optimization of their performance and serve as quality control techniques. Further characterizations of these devices include electrochemical impedance spectroscopy and an aqueous electrochemical assessment of the electrode surface area and diffusion through the porous layer. In conclusion, we find a correlation of increased sensitivity with larger gas reaction impedance, higher Pt electrode surface area, and slower diffusion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Quantitative decoding of the response a ceramic mixed potential sensor array for engine emissions control and diagnostics

The development of on-board sensors for emissions monitoring is necessary for continuous monitoring of the performance of catalytic systems in automobiles. We have fabricated mixed potential electrochemical gas sensing devices with Pt, La 0.8 Sr 0.2 CrO 3 (LSCO), and Au/Pd alloy electrodes and a porous yttria-stabilized zirconia electrolyte. The three-electrode design takes advantage of the preferential selectivity of the Pt + Au/Pd and Pt + LSCO pairs towards different species of gases and has additional tunable selectivity achieved by applying a current bias to the latter pair. Voltages were recorded in single, binary, and ternary gas streams of NO, NO 2 , C 3 H 8 , and CO. We have also trained artificial neural networks to examine the voltage output from sensors in biased and unbiased modes to both identify which single test gas or binary mixture of two test gases is present in a gas stream as well as extract concentration values. We were then able to identify single and binary mixtures of these gases with accuracy of at least 98%. For determining concentration, the peak in the error distribution for binary mixtures was 5% and 80% of test data fell under <12% error. The sensor stability was also evaluated over the course of over 100 days and the ability to retrain ANNs with a small dataset was demonstrated.

33 ADVANCED PROPULSION SYSTEMS↗