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Mater Today Bio

Title:		Effect of film thickness in gelatin hybrid gels for artificial olfaction
Author(s):		Esteves C; Santos GMC; Alves C; Palma S; Porteira AR; Filho J; Costa HMA; Alves VD; Morais Faustino BM; Ferreira I; Gamboa H; Roque ACA;
Address:		"UCIBIO, Departamento de Quimica, Faculdade de Ciencias e Tecnologia, Universidade Nova de Lisboa, Caparica, Portugal. LIBPhys-UNL, Departamento de Fisica, Faculdade de Ciencias e Tecnologia, Universidade Nova de Lisboa, Caparica, Portugal. LEAF - Linking Landscape, Environment, Agriculture and Food, Instituto Superior de Agronomia, Universidade de Lisboa, Lisboa, Portugal. CENIMAT/I3N, Departamento de Ciencias dos Materiais, Faculdade de Ciencias e Tecnologia, Universidade Nova de Lisboa, Caparica, Portugal"
Journal Title:		Mater Today Bio
Year:		2019
Volume:		20190322
Issue:
Page Number:		100002 -
DOI:		10.1016/j.mtbio.2019.100002
ISSN/ISBN:		2590-0064 (Electronic) 2590-0064 (Linking)
Abstract:		"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 mum 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 mum 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"
Keywords:		Electronic nose Gas sensor Gelatin Ionic liquid Liquid crystal Machine learning;
Notes:		"PubMed-not-MEDLINEEsteves, Carina Santos, Goncalo M C Alves, Claudia Palma, Susana I C J Porteira, Ana R Filho, Joao Costa, Henrique M A Alves, Vitor D Morais Faustino, Bruno M Ferreira, Isabel Gamboa, Hugo Roque, Ana C A eng 639123/ERC_/European Research Council/International England 2020/03/12 Mater Today Bio. 2019 Mar 22; 1:100002. doi: 10.1016/j.mtbio.2019.100002. eCollection 2019 Jan"