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Optimization of a Low-Power Chemoresistive Gas Sensor: Predictive Thermal Modelling and Mechanical Failure Analysis
The substrate plays a key role in chemoresistive gas sensors. It acts as mechanical support for the sensing material, hosts the heating element and, also, aids the sensing material in signal transduction. In recent years, a significant improvement in the substrate production process has been achieve...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7865525/ https://www.ncbi.nlm.nih.gov/pubmed/33503884 http://dx.doi.org/10.3390/s21030783 |
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author | Gaiardo, Andrea Novel, David Scattolo, Elia Crivellari, Michele Picciotto, Antonino Ficorella, Francesco Iacob, Erica Bucciarelli, Alessio Petti, Luisa Lugli, Paolo Bagolini, Alvise |
author_facet | Gaiardo, Andrea Novel, David Scattolo, Elia Crivellari, Michele Picciotto, Antonino Ficorella, Francesco Iacob, Erica Bucciarelli, Alessio Petti, Luisa Lugli, Paolo Bagolini, Alvise |
author_sort | Gaiardo, Andrea |
collection | PubMed |
description | The substrate plays a key role in chemoresistive gas sensors. It acts as mechanical support for the sensing material, hosts the heating element and, also, aids the sensing material in signal transduction. In recent years, a significant improvement in the substrate production process has been achieved, thanks to the advances in micro- and nanofabrication for micro-electro-mechanical system (MEMS) technologies. In addition, the use of innovative materials and smaller low-power consumption silicon microheaters led to the development of high-performance gas sensors. Various heater layouts were investigated to optimize the temperature distribution on the membrane, and a suspended membrane configuration was exploited to avoid heat loss by conduction through the silicon bulk. However, there is a lack of comprehensive studies focused on predictive models for the optimization of the thermal and mechanical properties of a microheater. In this work, three microheater layouts in three membrane sizes were developed using the microfabrication process. The performance of these devices was evaluated to predict their thermal and mechanical behaviors by using both experimental and theoretical approaches. Finally, a statistical method was employed to cross-correlate the thermal predictive model and the mechanical failure analysis, aiming at microheater design optimization for gas-sensing applications. |
format | Online Article Text |
id | pubmed-7865525 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-78655252021-02-07 Optimization of a Low-Power Chemoresistive Gas Sensor: Predictive Thermal Modelling and Mechanical Failure Analysis Gaiardo, Andrea Novel, David Scattolo, Elia Crivellari, Michele Picciotto, Antonino Ficorella, Francesco Iacob, Erica Bucciarelli, Alessio Petti, Luisa Lugli, Paolo Bagolini, Alvise Sensors (Basel) Article The substrate plays a key role in chemoresistive gas sensors. It acts as mechanical support for the sensing material, hosts the heating element and, also, aids the sensing material in signal transduction. In recent years, a significant improvement in the substrate production process has been achieved, thanks to the advances in micro- and nanofabrication for micro-electro-mechanical system (MEMS) technologies. In addition, the use of innovative materials and smaller low-power consumption silicon microheaters led to the development of high-performance gas sensors. Various heater layouts were investigated to optimize the temperature distribution on the membrane, and a suspended membrane configuration was exploited to avoid heat loss by conduction through the silicon bulk. However, there is a lack of comprehensive studies focused on predictive models for the optimization of the thermal and mechanical properties of a microheater. In this work, three microheater layouts in three membrane sizes were developed using the microfabrication process. The performance of these devices was evaluated to predict their thermal and mechanical behaviors by using both experimental and theoretical approaches. Finally, a statistical method was employed to cross-correlate the thermal predictive model and the mechanical failure analysis, aiming at microheater design optimization for gas-sensing applications. MDPI 2021-01-25 /pmc/articles/PMC7865525/ /pubmed/33503884 http://dx.doi.org/10.3390/s21030783 Text en © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Gaiardo, Andrea Novel, David Scattolo, Elia Crivellari, Michele Picciotto, Antonino Ficorella, Francesco Iacob, Erica Bucciarelli, Alessio Petti, Luisa Lugli, Paolo Bagolini, Alvise Optimization of a Low-Power Chemoresistive Gas Sensor: Predictive Thermal Modelling and Mechanical Failure Analysis |
title | Optimization of a Low-Power Chemoresistive Gas Sensor: Predictive Thermal Modelling and Mechanical Failure Analysis |
title_full | Optimization of a Low-Power Chemoresistive Gas Sensor: Predictive Thermal Modelling and Mechanical Failure Analysis |
title_fullStr | Optimization of a Low-Power Chemoresistive Gas Sensor: Predictive Thermal Modelling and Mechanical Failure Analysis |
title_full_unstemmed | Optimization of a Low-Power Chemoresistive Gas Sensor: Predictive Thermal Modelling and Mechanical Failure Analysis |
title_short | Optimization of a Low-Power Chemoresistive Gas Sensor: Predictive Thermal Modelling and Mechanical Failure Analysis |
title_sort | optimization of a low-power chemoresistive gas sensor: predictive thermal modelling and mechanical failure analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7865525/ https://www.ncbi.nlm.nih.gov/pubmed/33503884 http://dx.doi.org/10.3390/s21030783 |
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