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Projeto de investigação
An affinity-based approach towards highly specific odor sensing
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Effect of Polymer Hydrophobicity in the Performance of Hybrid Gel Gas Sensors for E-Noses
Publication . Oliveira, Ana Rita; Costa, Henrique M. A.; Ramou, Efthymia; Palma, Susana I. C. J.; Roque, Ana Cecília A.; UCIBIO - Applied Molecular Biosciences Unit; DQ - Departamento de Química; MDPI - Multidisciplinary Digital Publishing Institute
Relative humidity (RH) is a common interferent in chemical gas sensors, influencing their baselines and sensitivity, which can limit the performance of e-nose systems. Tuning the composition of the sensing materials is a possible strategy to control the impact of RH in gas sensors. Hybrid gel materials used as gas sensors contain self-assembled droplets of ionic liquid and liquid crystal molecules encapsulated in a polymeric matrix. In this work, we assessed the effect of the matrix hydrophobic properties in the performance of hybrid gel materials for VOC sensing in humid conditions (50% RH). We used two different polymers, the hydrophobic PDMS and the hydrophilic bovine gelatin, as polymeric matrices in hybrid gel materials containing imidazolium-based ionic liquids, [BMIM][Cl] and [BMIM][DCA], and the thermotropic liquid crystal 5CB. Better accuracy of VOC prediction is obtained for the hybrid gels composed of a PDMS matrix combined with the [BMIM][Cl] ionic liquid, and the use of this hydrophobic matrix reduces the effect of humidity on the sensing performance when compared to the gelatin counterpart. VOCs interact with all the moieties of the hybrid gel multicomponent system; thus, VOC correct classification depends not only on the polymeric matrix used, but also on the IL selected, which seems to be key to achieve VOCs discrimination at 50% RH. Thus, hybrid gels’ tunable formulation offers the potential for designing complementary sensors for e-nose systems operable under different RH conditions.
Incorporation of VOC-Selective Peptides in Gas Sensing Materials
Publication . Oliveira, Ana Rita; Ramou, Efthymia; Teixeira, Gonçalo Duarte Gomes; Palma, Susana I. C. J.; Roque, Ana C. A.; UCIBIO - Applied Molecular Biosciences Unit; DQ - Departamento de Química
Enhancing the selectivity of gas sensing materials towards specific volatile organic compounds (VOCs) is challenging due to the chemical simplicity of VOCs as well as the difficulty in interfacing VOC selective biological elements with electronic components used in the transduction process. We aimed to tune the selectivity of gas sensing materials through the incorporation of VOC-selective peptides into gel-like gas sensing materials. Specifically, a peptide (P1) known to discriminate single carbon deviations among benzene and derivatives, along with two modified versions (P2 and P3), were integrated with gel compositions containing gelatin, ionic liquid and without or with a liquid crystal component (ionogels and hybrid gels respectively). These formulations change their electrical or optical properties upon VOC exposure, and were tested as sensors in an in-house developed e-nose. Their ability to distinct and identify VOCs was evaluated via a supervised machine learning classifier. Enhanced discrimination of benzene and hexane was detected for the P1-based hybrid gel. Additionally, complementaritv of the electrical and optical sensors was observed considering that a combination of both their accuracy predictions yielded the best classification results for the tested VOCs. This indicates that a combinatorial array in a dual-mode e-nose could provide optimal performance and enhanced selectivity.
Enhancing VOCs Selectivity by Designing Novel Gas Sensitive Soft Materials
Publication . Oliveira, Ana Rita Martins Lourenço de; Roque, Ana
Artificial olfaction aims to mimic the biological sense of smell, using electronic-nose devices
that result from the combination of (bio)chemical sensors, electronics, and artificial intelligence
tools. These devices can detect and identify individual or mixtures of gas analytes, such as
Volatile Organic Compounds (VOCs).
This thesis explores the design of novel gas sensing materials based on ionogels and
hybrid gels materials, with the goal of increasing their selectivity and discrimination towards
different VOCs. Sensing materials based on the entrapment of ionic liquids within a biopolymeric
matrix (ionogel), or on liquid crystal-ionic liquid droplet systems within a biopolymeric
matrix (hybrid gels) were created and coupled with artificial intelligence algorithms to develop
a custom-made electronic nose, for gas sensing purposes. The ionic liquid and liquid
crystal components involved in this type of sensing materials provide complementary measurable
signals (electric and optical), that can help tune the sensor selectivity, and due to their
dynamic self-assembling nature allows the creation of dual responsive materials in the presence
of VOCs.
The tunability of ionogels and different hybrid gels towards VOCs discrimination capability
was first assessed by changing the materials composition. Changing components such
as the ionic liquid cation, and the hydrophobicity of the chosen polymeric matrix, influenced
morphological properties, VOC sensing capability, and sensors performance and storage-stability
under room ambient.
The addition of simple biological molecules to the gel’s formulation, such as peptides
and small affinity ligand molecules, was also explored. In one study, three peptides were incorporated
in the ionogels and hybrid gels composition. In a second approach, a library of
fourteen different small ligands were chemically immobilized onto the glass surface of hybrid
gel sensors. These materials were explored in a tailor-made electronic nose showing their potential
to discriminate between a set of distinct volatiles under environmental conditions.
Overall, this work demonstrates the versatility of sustainable and stimuli-responsive
novel gas sensing materials for use in electro-optical devices, capable of performing under
environmental conditions, exhibiting promising results in artificial olfaction and gas sensing
applications.
Impact of the Cationic Moiety of Ionic Liquids on Chemoselective Artificial Olfaction
Publication . Oliveira, Ana Rita; Ramou, Efthymia; Palma, Susana I. C. J.; Esteves, Carina; Barbosa, Arménio; Roque, Ana Cecília Afonso; UCIBIO - Applied Molecular Biosciences Unit; DQ - Departamento de Química; ACS - American Chemical Society
Ionogels and derived materials are assemblies of polymers and ionic liquids characterized by high stability and ionic conductivity, making them interesting choices as gas sensors. In this work, we assessed the effect of the ionic liquid moiety to generate ionogels and hybrid gels as electrical and optical gas sensors. Six ionic liquids consisting of a constant anion (chloride) and distinct cationic head groups were used to generate ionogels and hybrid gels and further tested as gas sensors in customized electronic nose devices. In general, ionogel-based sensors yielded higher classification accuracies of standard volatile organic compounds when compared to hybrid material-based sensors. In addition, the high chemical diversity of ionic liquids is further translated to a high functional diversity in analyte molecular recognition and sensing.
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Fundação para a Ciência e a Tecnologia
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SFRH/BD/128687/2017