Modelling electronic transport in monocrystalline metal oxide gas sensors: from the surface kinetics to the experimental response
| Autor: | Roberto Guarino, Fabrizio Mo, Yuri Ardesi, Andrea Gaiardo, Matteo Tonezzer, Sergio Guarino, Gianluca Piccinini |
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| Rok vydání: | 2022 |
| Předmět: |
History
Polymers and Plastics Metals and Alloys Gas sensors Metal oxides Sensor response Numerical simulations Multiscale modelling NO2 sensors Condensed Matter Physics Industrial and Manufacturing Engineering Surfaces Coatings and Films Electronic Optical and Magnetic Materials Settore AGR/15 - SCIENZE E TECNOLOGIE ALIMENTARI Materials Chemistry Business and International Management Electrical and Electronic Engineering Instrumentation |
| Zdroj: | Sensors and Actuators B: Chemical. 373:132646 |
| ISSN: | 0925-4005 |
| Popis: | Gas sensing systems and devices based on metal oxides are widely spreading due to their high performance in terms of sensor response and relatively low costs. Despite several experimental studies, as well as molecular simulations, are available in the literature, a tool that can quickly predict the macroscopic sensor response, and potentially be used for predictive purposes, is still missing. In this work, we present a modelling approach based on finite-element simulations, using material electrical properties available in the literature. In a first approach, we derive the surface electron trap concentration from fitting the global sensor response. Then, we improve the model by eliminating this fitting and considering the actual time-dependent experimental response. We consider sensors based on single SnO2 nanowires and show how our model predicts with a good agreement the experimental response vs. NO2, as a function of the working temperature and gas concentration, and also provides many other physical quantities of interest, such as the conduction band edge bending, the space charge and the width of the depletion layer. We further discuss ideas for improving the model and thus increasing its predictive potential. |
| Databáze: | OpenAIRE |
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