Alves, R, Rodrigues J, Ramou E, Palma S, Roque A, Gamboa H.
2022.
Classification of Volatile Compounds with Morphological Analysis of e-nose Response, Feb. Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies - BIOSIGNALS. :31–39.: Scitepress
AbstractElectronic noses (e-noses) mimic human olfaction, by identifying Volatile Organic Compounds (VOCs). This
work presents a novel approach that successfully classifies 11 known VOCs using the signals generated by
sensing gels in an in-house developed e-nose. The proposed signals’ analysis methodology is based on the
generated signals’ morphology for each VOC since different sensing gels produce signals with different shapes
when exposed to the same VOC. For this study, two different gel formulations were considered, and an average
f1-score of 84% and 71% was obtained, respectively. Moreover, a standard method in time series classification
was used to compare the performances. Even though this comparison reveals that the morphological approach
is not as good as the 1-nearest neighbour with euclidean distance, it shows the possibility of using descriptive
sentences with text mining techniques to perform VOC classification.
Palma, SICJ, Esteves C, Pádua AC, Alves CM, Santos GMC, Costa HMA, Dionisio M, Gamboa H, Gruber J, Roque ACA.
2019.
Enhanced gas sensing with soft functional materials, May 2019. ISOEN 2019 - 18th International Symposium on Olfaction and Electronic Nose, Proceedings. , Fukuoka, Japan: Institute of Electrical and Electronics Engineers Inc.
AbstractThe materials described in this work result from the selfassembly of liquid crystals and ionic liquids into droplets,
stabilized within a biopolymeric matrix. These systems are
extremely versatile gels, in terms of composition, and offer
potential for fine tuning of both structure and function, as
each individual component can be varied. Here, the
characterization and application of these gels as sensing thin
films in gas sensor devices is presented. The unique
supramolecular structure of the gels is explored for molecular
recognition of volatile organic compounds (VOCs) by
employing gels with distinct formulations to yield
combinatorial optical and electrical responses used in the
distinction and identification of VOCs.
Moreira, IP, Sato L, Alves C, Palma S, Roque AC.
2021.
Fish gelatin-based films for gas sensing. BIODEVICES 2021 - 14th International Conference on Biomedical Electronics and Devices; Part of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2021. :32–39.: SciTePress
AbstractElectronic noses (e-noses) mimic the complex biological olfactory system, usually including an array of gas sensors to act as the olfactory receptors and a trained computer with signal-processing and pattern recognition tools as the brain. In this work, a new stimuli-responsive material is shown, consisting of self-assembled droplets of liquid crystal and ionic liquid stabilised within a fish gelatin matrix. These materials change their opto/electrical properties upon contact with volatile organic compounds (VOCs). By using an in-house developed e-nose, these new gas-sensing films yield characteristic optical signals for VOCs from different chemical classes. A support vector machine classifier was implemented based on 12 features of the signals. The results show that the films are excellent identifying hydrocarbon VOCs (toluene, heptane and hexane) (95% accuracy) but lower performance was found to other VOCs, resulting in an overall 60.4% accuracy. Even though they are not reusable, these sustainable gas-sensing films are stable throughout time and reproducible, opening several opportunities for future optoelectronic devices and artificial olfaction systems.