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Palanisamy, Ponnusamy

Publications and source records attributed to Palanisamy, Ponnusamy.

5 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 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↗
DOE OSTI2014

Mixed-Potential NO x and NH 3 Sensors Fabricated by Commercial Manufacturing Methods [Mixed-Potential Sensors NO x and NH 3 Fabricated by Commercial Manufacturing Methods]

Meeting EPA Tier 3 emissions reduction requirements while simultaneously increasing fuel economy to meet new CAFE standards will require optimization of advanced combustion strategies and emissions control technologies. There is an immediate need for suitable exhaust gas sensor technologies to monitor internal combustion engine tailpipe emissions and to control and maintain efficient operation of the engine and exhaust after treatment systems. NH 3 , NO x , and HC sensors could enable onboard diagnostics and combustion control in lean-burn engines, analogous to the role of O 2 sensors in stoichiometric burn engines. Commercial manufacturing methods have been used to fabricate self-heated mixed-potential sensors in a planar automotive configuration. By altering materials composition and operating conditions, we are able to obtain sensitivity/selectivity to each NH 3 , NO x and HCs. In addition, these devices exhibit stable performance over months of testing as a result of the stable morphology of the electrode/electrolyte/gas three-phase interface.

36 MATERIALS SCIENCE↗