An Optimized E-nose for Efﬁcient Volatile Sensing and Discrimination

Santos, Guilherme; Alves, Cláudia; Pádua, Ana Carolina; Palma, Susana; Gamboa, Hugo; Roque, Ana C. A.

doi:10.5220/0007390700360046

Cited by 10 publications

(27 citation statements)

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“…After that, the outliers were removed. Twelve features relevant to the morphology of the signal curves were extracted per cycle 37 and used as input to train an automatic classifier based on SVM. The classification results for all the gel compositions tested (both hybrid and control gels) were presented in normalized confusion matrices and accuracy plots.…”

Section: Methodsmentioning

confidence: 99%

“…The SVM classification model used in this work was implemented and optimized by our research group, as described in a previous publication, 37 using a data pool of signals generated by 5CB hybrid gels upon exposure to the same set of 12 VOCs used in this work. Briefly, the classification model is trained with features extracted from the cycles’ curves.…”

Section: Methodsmentioning

confidence: 99%

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Nanoscale Events on Cyanobiphenyl-Based Self-Assembled Droplets Triggered by Gas Analytes

Ramou

Palma

Roque

2022

ACS Appl. Mater. Interfaces

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Liquid crystals (LCs) are prime examples of dynamic supramolecular soft materials. Their autonomous self-assembly at the nanoscale level and the further nanoscale events that give rise to unique stimuli-responsive properties have been exploited for sensing purposes. One of the key features to employ LCs as sensing materials derives from the fine-tuning between stability and dynamics. This challenging task was addressed in this work by studying the effect of the alkyl chain length of cyanobiphenyl LCs on the molecular self-assembled compartments organized in the presence of ionic liquid molecules and gelatin. The resulting multicompartment nematic and smectic gels were further used as volatile organic compound chemical sensors. The LC structures undergo a dynamic sequence of phase transitions, depending on the nature of the LC component, yielding a variety of optical signals, which serve as optical fingerprints. In particular, the materials incorporating smectic compartments resulted in unexpected and rich optical textures that have not been reported previously. Their sensing capability was tested in an in-house-assembled electronic nose and further assessed via signal collection and machine-learning algorithms based on support vector machines, which classified 12 different gas analytes with high accuracy scores. Our work expands the knowledge on controlling LC self-assembly to yield fast and autonomous accurate chemical-sensing systems based on the combination of complex nanoscale sensing events with artificial intelligence tools.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Nanoscale Events on Cyanobiphenyl-Based Self-Assembled Droplets Triggered by Gas Analytes

Ramou

Palma

Roque

2022

ACS Appl. Mater. Interfaces

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show abstract

“…To assess the ability of each sensing material to identify VOCs based on the shape of the signals, the cycles were first normalised using the percentile method. Then, shape-related features were extracted from each normalised cycle and used as input variables to build an automatic classifier algorithm based on Support Vector Machine (SVM), as reported previously [ 19 , 20 ]. For each sensing material, the classifier was used to make predictions of the VOC identification.…”

Section: Methodsmentioning

confidence: 99%

Synergy between silk fibroin and ionic liquids for active gas-sensing materials

Moreira¹,

Esteves²,

Palma³

et al. 2022

Materials Today Bio

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“…The e-nose device [ 21 ] includes a detection chamber, a sample chamber, and an exposure and a recovery pump ( Fig. 1 d).…”

Section: Methodsmentioning

confidence: 99%

“…For each type of suberin film, the cycles dataset was divided in training dataset (the 50 cycles per VOC from the first experiment) and validation dataset (the 50 cycles per VOC from the second experiment). Twelve features regarding the morphology of the waveform were extracted per cycle, as explained elsewhere [ 8 , 21 ], and used as input to implement automatic VOC classifiers based on the support vector machines (SVM) algorithm. The SVM was tuned with the radial basis kernel and hyperparameters C = 100 and γ = 0.1.…”

Section: Methodsmentioning

confidence: 99%

Sustainable plant polyesters as substrates for optical gas sensors

Rodrigues

Palma

Correia

et al. 2020

Materials Today Bio

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The fast and non-invasive detection of odors and volatile organic compounds (VOCs) by gas sensors and electronic noses is a growing field of interest, mostly due to a large scope of potential applications. Additional drivers for the expansion of the field include the development of alternative and sustainable sensing materials. The discovery that isolated cross-linked polymeric structures of suberin spontaneously self-assemble as a film inspired us to develop new sensing composite materials consisting of suberin and a liquid crystal (LC). Due to their stimuli-responsive and optically active nature, liquid crystals are interesting probes in gas sensing. Herein, we report the isolation and the chemical characterization of two suberin types (from cork and from potato peels) resorting to analyses of gas chromatography–mass spectrometry (GC-MS), solution nuclear magnetic resonance (NMR), and X-ray photoelectron spectroscopy (XPS). The collected data highlighted their compositional and structural differences. Cork suberin showed a higher proportion of longer aliphatic constituents and is more esterified than potato suberin. Accordingly, when casted it formed films with larger surface irregularities and a higher C/O ratio. When either type of suberin was combined with the liquid crystal 5CB, the ensuing hybrid materials showed distinctive morphological and sensing properties towards a set of 12 VOCs (comprising heptane, hexane, chloroform, toluene, dichlormethane, diethylether, ethyl acetate, acetonitrile, acetone, ethanol, methanol, and acetic acid). The optical responses generated by the materials are reversible and reproducible, showing stability for 3 weeks. The individual VOC-sensing responses of the two hybrid materials are discussed taking as basis the chemistry of each suberin type. A support vector machines (SVM) algorithm based on the features of the optical responses was implemented to assess the VOC identification ability of the materials, revealing that the two distinct suberin-based sensors complement each other, since they selectively identify distinct VOCs or VOC groups. It is expected that such new environmentally-friendly gas sensing materials derived from natural diversity can be combined in arrays to enlarge selectivity and sensing capacity.

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An Optimized E-nose for Efﬁcient Volatile Sensing and Discrimination

Cited by 10 publications

References 0 publications

Nanoscale Events on Cyanobiphenyl-Based Self-Assembled Droplets Triggered by Gas Analytes

Nanoscale Events on Cyanobiphenyl-Based Self-Assembled Droplets Triggered by Gas Analytes

Synergy between silk fibroin and ionic liquids for active gas-sensing materials

Sustainable plant polyesters as substrates for optical gas sensors

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