Abstract
Catalytic noble metal (s) or its alloy (s) has long been used as the electrode material to enhance the sensing performance of the semiconducting oxide based gas sensors. In the present paper, design of optimized ternary metal alloy electrode, while the database is in pure or binary alloy compositions, using a machine learning methodology is reported for detection of CH4 gas as a test case. Pure noble metals or their binary alloys as the electrode on the semiconducting ZnO sensing layer were investigated by the earlier researchers to enhance the sensitivity towards CH4. Based on those research findings, an artificial neural network (ANN) models were developed considering the three main features of the gas sensor devices, viz. response magnitude, response time and recovery time as a function of ZnO particle size and the composition of the catalytic alloy. A novel methodology was introduced by using ANN models considered for optimized ternary alloy with enriched presentation through the multi-objective genetic algorithm (GA) wherever the generated pareto front was used. The prescriptive data analytics methodology seems to offer more or less convinced evidences for future experimental studies.
Highlights
Noble metals like palladium, platinum, silver, gold etc. were investigated for a long time due to their contribution towards improving the performance of semiconductor gas sensor devices (Acharyya et al, 2016)
Often utilized in the form of electrode, act as the potential adsorption size for the target gas species, either through chemical sensitization or through electronic sensitization (Roy et al, 2012). They help in lowering down the activation energy requirement for gas dissociation
The target versus achieved output plots for the artificial neural network (ANN) models show that the performance of most of the ANN models are satisfactory
Summary
Platinum, silver, gold etc. were investigated for a long time due to their contribution towards improving the performance of semiconductor gas sensor devices (Acharyya et al, 2016). It was found that the catalytic activities of these metals can further be reinforced by judiciously alloying it with a secondary metal (Acharyya & Bhattacharyya, 2016; Roy et al, 2012) Such binary alloys, often utilized in the form of electrode, act as the potential adsorption size for the target gas species, either through chemical sensitization or through electronic sensitization (Roy et al, 2012). Most of the approaches are based on trial-and-error method which is time consuming, expensive, and even without any guarantee of success
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