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Effect of film thickness in gelatin hybrid gels for artificial olfaction
Artificial olfaction is a fast-growing field aiming to mimic natural olfactory systems. Olfactory systems rely on a first step of molecular recognition in which volatile organic compounds (VOCs) bind to an array of specialized olfactory proteins. This results in electrical signals transduced to the...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7061580/ https://www.ncbi.nlm.nih.gov/pubmed/32159137 http://dx.doi.org/10.1016/j.mtbio.2019.100002 |
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author | Esteves, Carina Santos, Gonçalo M.C. Alves, Cláudia Palma, Susana I.C.J. Porteira, Ana R. Filho, João Costa, Henrique M.A. Alves, Vitor D. Morais Faustino, Bruno M. Ferreira, Isabel Gamboa, Hugo Roque, Ana C.A. |
author_facet | Esteves, Carina Santos, Gonçalo M.C. Alves, Cláudia Palma, Susana I.C.J. Porteira, Ana R. Filho, João Costa, Henrique M.A. Alves, Vitor D. Morais Faustino, Bruno M. Ferreira, Isabel Gamboa, Hugo Roque, Ana C.A. |
author_sort | Esteves, Carina |
collection | PubMed |
description | Artificial olfaction is a fast-growing field aiming to mimic natural olfactory systems. Olfactory systems rely on a first step of molecular recognition in which volatile organic compounds (VOCs) bind to an array of specialized olfactory proteins. This results in electrical signals transduced to the brain where pattern recognition is performed. An efficient approach in artificial olfaction combines gas-sensitive materials with dedicated signal processing and classification tools. In this work, films of gelatin hybrid gels with a single composition that change their optical properties upon binding to VOCs were studied as gas-sensing materials in a custom-built electronic nose. The effect of films thickness was studied by acquiring signals from gelatin hybrid gel films with thicknesses between 15 and 90 μm when exposed to 11 distinct VOCs. Several features were extracted from the signals obtained and then used to implement a dedicated automatic classifier based on support vector machines for data processing. As an optical signature could be associated to each VOC, the developed algorithms classified 11 distinct VOCs with high accuracy and precision (higher than 98%), in particular when using optical signals from a single film composition with 30 μm thickness. This shows an unprecedented example of soft matter in artificial olfaction, in which a single gelatin hybrid gel, and not an array of sensing materials, can provide enough information to accurately classify VOCs with small structural and functional differences. |
format | Online Article Text |
id | pubmed-7061580 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-70615802020-03-10 Effect of film thickness in gelatin hybrid gels for artificial olfaction Esteves, Carina Santos, Gonçalo M.C. Alves, Cláudia Palma, Susana I.C.J. Porteira, Ana R. Filho, João Costa, Henrique M.A. Alves, Vitor D. Morais Faustino, Bruno M. Ferreira, Isabel Gamboa, Hugo Roque, Ana C.A. Mater Today Bio Full-Length Article Artificial olfaction is a fast-growing field aiming to mimic natural olfactory systems. Olfactory systems rely on a first step of molecular recognition in which volatile organic compounds (VOCs) bind to an array of specialized olfactory proteins. This results in electrical signals transduced to the brain where pattern recognition is performed. An efficient approach in artificial olfaction combines gas-sensitive materials with dedicated signal processing and classification tools. In this work, films of gelatin hybrid gels with a single composition that change their optical properties upon binding to VOCs were studied as gas-sensing materials in a custom-built electronic nose. The effect of films thickness was studied by acquiring signals from gelatin hybrid gel films with thicknesses between 15 and 90 μm when exposed to 11 distinct VOCs. Several features were extracted from the signals obtained and then used to implement a dedicated automatic classifier based on support vector machines for data processing. As an optical signature could be associated to each VOC, the developed algorithms classified 11 distinct VOCs with high accuracy and precision (higher than 98%), in particular when using optical signals from a single film composition with 30 μm thickness. This shows an unprecedented example of soft matter in artificial olfaction, in which a single gelatin hybrid gel, and not an array of sensing materials, can provide enough information to accurately classify VOCs with small structural and functional differences. Elsevier 2019-03-22 /pmc/articles/PMC7061580/ /pubmed/32159137 http://dx.doi.org/10.1016/j.mtbio.2019.100002 Text en © 2019 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Full-Length Article Esteves, Carina Santos, Gonçalo M.C. Alves, Cláudia Palma, Susana I.C.J. Porteira, Ana R. Filho, João Costa, Henrique M.A. Alves, Vitor D. Morais Faustino, Bruno M. Ferreira, Isabel Gamboa, Hugo Roque, Ana C.A. Effect of film thickness in gelatin hybrid gels for artificial olfaction |
title | Effect of film thickness in gelatin hybrid gels for artificial olfaction |
title_full | Effect of film thickness in gelatin hybrid gels for artificial olfaction |
title_fullStr | Effect of film thickness in gelatin hybrid gels for artificial olfaction |
title_full_unstemmed | Effect of film thickness in gelatin hybrid gels for artificial olfaction |
title_short | Effect of film thickness in gelatin hybrid gels for artificial olfaction |
title_sort | effect of film thickness in gelatin hybrid gels for artificial olfaction |
topic | Full-Length Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7061580/ https://www.ncbi.nlm.nih.gov/pubmed/32159137 http://dx.doi.org/10.1016/j.mtbio.2019.100002 |
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