Direct or Indirect Sonication in Ecofriendly MoS2 Dispersion for NO2 and NH3 Gas-Sensing Applications.

Unlike the most used, this study explores the effects of direct and indirect sonication methods on the dispersion and gas sensing performance of MoS2 nanoflakes. The obtained dispersions are characterized using various techniques, such as field emission scanning electron microscopy, high resolution transmission electron microscopy, atomic force microscopy, dynamic light scattering, and Raman and X-ray diffraction, to evaluate their morphological and structural properties. Gas sensing measurements are conducted using exfoliated MoS2 on interdigitated electrode structures, and the response to multiple gases is recorded. The sensitivity and selectivity of the sensors are analyzed and compared between the direct and indirect sonication methods. The results demonstrate that both direct and indirect methods lead to the formation of well-dispersed MoS2 multilayer nanosheets, whereas the indirect approach exhibits a uniform and bigger flake size. Gas sensing experiments reveal that the MoS2 nanoflakes prepared via indirect sonication have enhanced sensitivity by 17 and 46% toward NO2 and NH3 gases, respectively, compared to the ones achieved by the direct sonication method. Both methods demonstrated its selectivity for NO2 and NH3 and the preferential temperature to detect NO2 and NH3 gas are 50 and 100 °C, respectively. This research contributes to the development of eco-friendly MoS2-based gas sensors by providing insights into the influence of direct (probe) and indirect (bath) sonication methods on dispersion quality and gas sensing performance. The findings highlight the potential of indirect sonication as a reliable technique for fabricating high-performance MoS2 gas sensors, opening venues for the design and optimization of eco-friendly sensing platforms for environmental monitoring and industrial applications.

Selective NO2 Gas Sensors Employing Nitrogen- and Boron-Doped and Codoped Reduced Graphene Oxide.

In this paper, we develop high-performance gas sensors based on heteroatom-doped and -codoped graphene oxide as a sensing material for the detection of NO2 at trace levels. Graphene oxide (GO) was doped with nitrogen and boron by a chemical method using urea and boric acid as precursors. The prepared samples were characterized by scanning electron microscopy (SEM), transmission electron microscopy (TEM), Raman spectroscopy, X-ray diffraction (XRD), and X-ray photoelectron spectroscopy (XPS). The obtained results proved the successful reduction of graphene oxide by doping effects, leading to the removal of some oxygen functional groups and restoration of an sp2 carbon structure. New bonds in honeycombs, such as pyridinic, pyrrolic, graphitic, B-C3, B-C2-O, and B-O, were created. Compared to the nondoped GO, the N/B-rGO materials exhibited enhanced responses toward low concentrations of NO2 (<1 ppm) at 100 °C. Particularly, the N-rGO-based device showed the highest sensitivity and lowest limit of detection.

ZnO Decorated Graphene-Based NFC Tag for Personal NO2 Exposure Monitoring during a Workday.

This paper presents the integration of a sensing layer over interdigitated electrodes and an electronic circuit on the same flexible printed circuit board. This integration provides an effective technique to use this design as a wearable gas measuring system in a target application, exhibiting high performance, low power consumption, and being lightweight for on-site monitoring. The wearable system proves the concept of using an NFC tag combined with a chemoresistive gas sensor as a cumulative gas sensor, having the possibility of holding the data for a working day, and completely capturing the exposure of a person to NO2 concentrations. Three different types of sensors were tested, depositing the sensing layers on gold electrodes over Kapton substrate: bare graphene, graphene decorated with 5 wt.% zinc oxide nanoflowers, or nanopillars. The deposited layers were characterized using FESEM, EDX, XRD, and Raman spectroscopy to determine their crystalline structure, morphological and chemical compositions. The gas sensing performance of the sensors was analyzed against NO2 (dry and humid conditions) and other interfering species (dry conditions) to check their sensitivity and selectivity. The resultant-built wearable NFC tag system accumulates the data in a non-volatile memory every minute and has an average low power consumption of 24.9 µW in dynamic operation. Also, it can be easily attached to a work vest.

Enhanced CO2 Sensing by Oxygen Plasma-Treated Perovskite-Graphene Nanocomposites.

Carbon dioxide (CO2) is a major greenhouse gas responsible for global warming and climate change. The development of sensitive CO2 sensors is crucial for environmental and industrial applications. This paper presents a novel CO2 sensor based on perovskite nanocrystals immobilized on graphene and functionalized with oxygen plasma treatment. The impact of this post-treatment method was thoroughly investigated using various characterization techniques, including Raman spectroscopy, X-ray diffraction, and X-ray photoelectron spectroscopy. The detection of CO2 at parts per million (ppm) levels demonstrated that the hybrids subjected to 5 min of oxygen plasma treatment exhibited a 3-fold improvement in sensing performance compared to untreated layers. Consequently, the CO2 sensing capability of the oxygen-treated samples showed a limit of detection and limit of quantification of 6.9 and 22.9 ppm, respectively. Furthermore, the influence of ambient moisture on the CO2 sensing performance was also evaluated, revealing a significant effect of oxygen plasma treatment.

Hydrogen Sensing Mechanism of WS2 Gas Sensors Analyzed with DFT and NAP-XPS.

Nanostructured tungsten disulfide (WS2) is one of the most promising candidates for being used as active nanomaterial in chemiresistive gas sensors, as it responds to hydrogen gas at room temperature. This study analyzes the hydrogen sensing mechanism of a nanostructured WS2 layer using near-ambient-pressure X-ray photoelectron spectroscopy (NAP-XPS) and density functional theory (DFT). The W 4f and S 2p NAP-XPS spectra suggest that hydrogen makes physisorption on the WS2 active surface at room temperature and chemisorption on tungsten atoms at temperatures above 150 °C. DFT calculations show that a hydrogen molecule physically adsorbs on the defect-free WS2 monolayer, while it splits and makes chemical bonds with the nearest tungsten atoms on the sulfur point defect. The hydrogen adsorption on the sulfur defect causes a large charge transfer from the WS2 monolayer to the adsorbed hydrogen. In addition, it decreases the intensity of the in-gap state, which is generated by the sulfur point defect. Furthermore, the calculations explain the increase in the resistance of the gas sensor when hydrogen interacts with the WS2 active layer.

ZnO-Loaded Graphene for NO2 Gas Sensing.

This paper investigates the effect of decorating graphene with zinc oxide (ZnO) nanoparticles (NPs) for the detection of NO2. In this regard, two graphene sensors with different ZnO loadings of 5 wt.% and 20 wt.% were prepared, and their responses towards NO2 at room temperature and different conditions were compared. The experimental results demonstrate that the graphene loaded with 5 wt.% ZnO NPs (G95/5) shows better performance at detecting low concentrations of the target gas than the one loaded with 20 wt.% ZnO NPs (G80/20). Moreover, measurements under dry and humid conditions of the G95/5 sensor revealed that the material is very sensitive to ambient moisture, showing an almost eight-fold increase in NO2 sensitivity when the background changes from dry to 70% relative humidity. Regarding sensor selectivity, it presents a significant selectivity towards NO2 compared to other gas compounds.

Enhancement of the CO2 Sensing/Capture through High Cationic Charge in M-ZrO2 (Li+, Mg2+, or Co3+): Experimental and Theoretical Studies.

The capture and storage of CO2 are of growing interest in atmospheric science since greenhouse gas emission has to be reduced considerably in the near future. The present paper deals with the doping of cations on ZrO2, i.e., M-ZrO2 (M = Li+, Mg2+, or Co3+), defecting the crystalline planes for the adsorption of carbon dioxide. The samples were prepared by the sol-gel method and characterized completely by different analytical methods. The deposition of metal ions on ZrO2 (whose crystalline phases: monoclinic and tetragonal are transformed into a single-phase such as tetragonal for LiZrO2 and cubic for MgZrO2 or CoZrO2) shows a complete disappearance of the XRD monoclinic signal, and it is consistent with HRTEM lattice fringes: 2.957 nm for ZrO2 (101, tetragonal/monoclinic), 3.018 nm for tetragonal LiZrO2, 2.940 nm for cubic MgZrO2, and 1.526 nm for cubic CoZrO2. The samples are thermally stable, resulting an average size of ∼5.0-15 nm. The surface of LiZrO2 creates the oxygen deficiency, while for Mg2+ (0.089 nm), since the size of the atom is relatively greater than that of Zr4+ (0.084 nm), the replacement of Zr4+ by Mg2+ in sublattice is difficult; thus, a decrease of the lattice constant was noticed. Since the high band gap energy (ΔE > 5.0 eV) is suitable for CO2 adsorption, the samples were employed for the selective detection/capture of CO2 by using electrochemical impedance spectroscopy (EIS) and direct current resistance (DCR), showing that CoZrO2 is capable of CO2 capture about 75%. If M+ ions are deposited within the ZrO2 matrix, then the charge imbalance allows CO2 to interact with the oxygen species to form CO32- which produces a high resistance (21.04 × 106 (Ω, Ohm)). The adsorption of CO2 with the samples was also theoretically studied showing that the interaction of CO2 with MgZrO2 and CoZrO2 is more feasible than with LiZrO2, subscribing to the experimental data. The temperature effect (273 to 573 K) for the interaction of CO2 with CoZrO2 was also studied by the docking method and observed the cubic structure is more stable at high temperatures as compared to the monoclinic geometry. Thus, CO2 would preferably interact with ZrO2c (ERS = -19.29 kJ/mol) than for ZrO2m (22.4 J/mmol (ZrO2c = cubic; ZrO2m = monoclinic).

The planar anodic Al2O3-ZrO2 nanocomposite capacitor dielectrics for advanced passive device integration.

The need for integrated passive devices (IPDs) emerges from the increasing consumer demand for electronic product miniaturization. Metal-insulator-metal (MIM) capacitors are vital components of IPD systems. Developing new materials and technologies is essential for advancing capacitor characteristics and co-integrating with other electronic passives. Here we present an innovative electrochemical technology joined with the sputter-deposition of Al and Zr layers to synthesize novel planar nanocomposite metal-oxide dielectrics consisting of ZrO2 nanorods self-embedded into the nanoporous Al2O3 matrix such that its pores are entirely filled with zirconium oxide. The technology is utilized in MIM capacitors characterized by modern surface and interface analysis techniques and electrical measurements. In the 95-480 nm thickness range, the best-achieved MIM device characteristics are the one-layer capacitance density of 112 nF·cm-2, the loss tangent of 4·10-3 at frequencies up to 1 MHz, the leakage current density of 40 pA·cm-2, the breakdown field strength of up to 10 MV·cm-1, the energy density of 100 J·cm-3, the quadratic voltage coefficient of capacitance of 4 ppm·V-2, and the temperature coefficient of capacitance of 480 ppm·K-1 at 293-423 K at 1 MHz. The outstanding performance, stability, and tunable capacitors' characteristics allow for their application in low-pass filters, coupling/decoupling/bypass circuits, RC oscillators, energy-storage devices, ultrafast charge/discharge units, or high-precision analog-to-digital converters. The capacitor technology based on the non-porous planar anodic-oxide dielectrics complements the electrochemical conception of IPDs that combined, until now, the anodized aluminum interconnection, microresistors, and microinductors, all co-related in one system for use in portable electronic devices.

Octahedral Molybdenum Iodide Clusters Supported on Graphene for Resistive and Optical Gas Sensing.

This paper reports for the first time a gas-sensitive nanohybrid based on octahedral molybdenum iodide clusters supported on graphene flakes (Mo6@Graphene). The possibility of integrating this material into two different transducing schemes for gas sensing is proposed since the nanomaterial changes both its electrical resistivity and optical properties when exposed to gases and at room temperature. Particularly, when implemented in a chemoresistive device, the Mo6@Graphene hybrid showed an outstanding sensing performance toward NO2, revealing a limit of quantification of about 10 ppb and excellent response repeatability (0.9% of relative error). While the Mo6@Graphene chemoresistor was almost insensitive to NH3, the use of an optical transduction scheme (changes in photoluminescence) provided an outstanding detection of NH3 even for a low loading of Mo6. Nevertheless, the photoluminescence was not affected by the presence of NO2. In addition, the hybrid material revealed high stability of its gas sensing properties over time and under ambient moisture. Computational chemistry calculations were performed to better understand these results, and plausible sensing mechanisms were presented accordingly. These results pave the way to develop a new generation of multi-parameter sensors in which electronic and optical interrogation techniques can be implemented simultaneously, advancing toward the realization of highly selective and orthogonal gas sensing.

Three-Dimensional Assemblies of Edge-Enriched WSe2 Nanoflowers for Selectively Detecting Ammonia or Nitrogen Dioxide.

Herein, we present, for the first time, a chemoresistive-type gas sensor composed of two-dimensional WSe2, fabricated by a simple selenization of tungsten trioxide (WO3) nanowires at atmospheric pressure. The morphological, structural, and chemical composition investigation shows the growth of vertically oriented three-dimensional (3D) assemblies of edge-enriched WSe2 nanoplatelets arrayed in a nanoflower shape. The gas sensing properties of flowered nanoplatelets (2H-WSe2) are investigated thoroughly toward specific gases (NH3 and NO2) at different operating temperatures. The integration of 3D WSe2 with unique structural arrangements resulted in exceptional gas sensing characteristics with dual selectivity toward NH3 and NO2 gases. Selectivity can be tuned by selecting its operating temperature (150 °C for NH3 and 100 °C for NO2). For instance, the sensor has shown stable and reproducible responses (24.5%) toward 40 ppm NH3 vapor detection with an experimental LoD < 2 ppm at moderate temperatures. The gas detecting capabilities for CO, H2, C6H6, and NO2 were also investigated to better comprehend the selectivity of the nanoflower sensor. Sensors showed repeatable responses with high sensitivity to NO2 molecules at a substantially lower operating temperature (100 °C) (even at room temperature) and LoD < 0.1 ppm. However, the gas sensing properties reveal high selectivity toward NH3 gas at moderate operating temperatures. Moreover, the sensor demonstrated high resilience against ambient humidity (Rh = 50%), demonstrating its remarkable stability toward NH3 gas detection. Considering the detection of NO2 in a humid ambient atmosphere, there was a modest increase in the sensor response (5.5%). Furthermore, four-month long-term stability assessments were also taken toward NH3 gas detection, and sensors showed excellent response stability. Therefore, this study highlights the practical application of the 2H variant of WSe2 nanoflower gas sensors for NH3 vapor detection.

Unraveling the Gas-Sensing Mechanisms of Lead-Free Perovskites Supported on Graphene.

Lead halide perovskites have been attracting great attention due to their outstanding properties and have been utilized for a wide variety of applications. However, the high toxicity of lead promotes an urgent and necessary search for alternative nanomaterials. In this perspective, the emerging lead-free perovskites are an environmentally friendly and harmless option. The present work reports for the first time gas sensors based on lead-free perovskite nanocrystals supported on graphene, which acts as a transducing element owing to its high and efficient carrier transport properties. The use of nanocrystals enables achieving excellent sensitivity toward gas compounds and presents better properties than those of bulky perovskite thin films, owing to their quantum confinement effect and exciton binding energy. Specifically, an industrially scalable, facile, and inexpensive synthesis is proposed to support two different perovskites (Cs3CuBr5 and Cs2AgBiBr6) on graphene for effectively detecting a variety of harmful pollutants below the threshold limit values. H2 and H2S gases were detected for the first time by utilizing lead-free perovskites, and ultrasensitive detection of NO2 was also achieved at room temperature. In addition, the band-gap type, defect tolerance, and electronic surface traps at the nanocrystals were studied in detail for understanding the differences in the sensing performance observed. Finally, a comprehensive sensing mechanism is proposed.

A machine learning COVID-19 mass screening based on symptoms and a simple olfactory test.

The early detection of symptoms and rapid testing are the basis of an efficient screening strategy to control COVID-19 transmission. The olfactory dysfunction is one of the most prevalent symptom and in many cases is the first symptom. This study aims to develop a machine learning COVID-19 predictive tool based on symptoms and a simple olfactory test, which consists of identifying the smell of an aromatized hydroalcoholic gel. A multi-centre population-based prospective study was carried out in the city of Reus (Catalonia, Spain). The study included consecutive patients undergoing a reverse transcriptase polymerase chain reaction test for presenting symptoms suggestive of COVID-19 or for being close contacts of a confirmed COVID-19 case. A total of 519 patients were included, 386 (74.4%) had at least one symptom and 133 (25.6%) were asymptomatic. A classification tree model including sex, age, relevant symptoms and the olfactory test results obtained a sensitivity of 0.97 (95% CI 0.91-0.99), a specificity of 0.39 (95% CI 0.34-0.44) and an AUC of 0.87 (95% CI 0.83-0.92). This shows that this machine learning predictive model is a promising mass screening for COVID-19.

Dysprosium Doped Zinc Oxide for NO2 Gas Sensing.

Pure and dysprosium-loaded ZnO films were grown by radio-frequency magnetron sputtering. The films were characterized using a wide variety of morphological, compositional, optical, and electrical techniques. The crystalline structure, surface homogeneity, and bandgap energies were studied in detail for the developed nanocomposites. The properties of pure and dysprosium-doped ZnO thin films were investigated to detect nitrogen dioxide (NO2) at the ppb range. In particular, ZnO sensors doped with rare-earth materials have been demonstrated as a feasible strategy to improve the sensitivity in comparison to their pure ZnO counterparts. In addition, the sensing performance was studied and discussed under dry and humid environments, revealing noteworthy stability and reliability under different experimental conditions. In this perspective, additional gaseous compounds such as ammonia and ethanol were measured, resulting in extremely low sensing responses. Therefore, the gas-sensing mechanisms were discussed in detail to better understand the NO2 selectivity given by the Dy-doped ZnO layer.

Phthalocyanines and Porphyrins/Polyaniline Composites (PANI/CuPctBu and PANI/TPPH2) as Sensing Materials for Ammonia Detection.

We combined a conducting polymer, polyaniline (PANI), with an organic semiconducting macrocyclic (MCs) material. The macrocycles are the phthalocyanines and porphyrins used to tune the electrical properties of the PANI, which benefits from their ability to enhance sensor response. For this, we proceeded by a simple ultrasonically assisted reaction involving the two components, i.e., the PANI matrix and the MCs, to achieve the synthesis of the composite nanostructure PANI/MCs. The composite nanostructure has been characterized and deposited on interdigitated electrodes (IDEs) to construct resistive sensor devices. The isolated nanostructured composites present good electrical properties dominated by PANI electronic conductivity, and the characterization reveals that both components are present in the nanostructure. The experimental results obtained under gas exposures show that the composite nanostructures can be used as a sensing material with enhanced sensing properties. The sensing performance under different conditions, such as ambient humidity, and the sensor's operating temperature are also investigated. Sensing behavior in deficient humidity levels and their response at different temperatures revealed unusual behaviors that help to understand the sensing mechanism. Gas sensors based on PANI/MCs demonstrate significant stability over time, but this stability is highly reduced after experiments in lower humidity conditions and at high temperatures.

Metal loaded nano-carbon gas sensor array for pollutant detection.

Many research works report a sensitive detection of a wide variety of gas species. However, their in-lab detection is usually performed by using single gases and, therefore, selectivity often remains an unsolved issue. This paper reports a four-sensor array employing different nano-carbon sensitive layers (bare graphene, SnO2@Graphene, WO3@Graphene, and Au@CNTs). The different gas-sensitive films were characterised via several techniques such as FESEM, TEM, and Raman. First, an extensive study was performed to detect isolated NO2, CO2, and NH3molecules, unravelling the sensing mechanism at the operating temperatures applied. Besides, the effect of the ambient moisture was also evaluated. Afterwards, a model for target gas identification and concentration prediction was developed. Indeed, the sensor array was used in mixtures of NO2and CO2for studying the cross-sensitivity and developing a calibration model. As a result, the NO2detection with different background levels of CO2was achieved with anR2of 0.987 and an RMSE of about 22 ppb.

Comparative analysis of volatile organic compounds of breath and urine for distinguishing patients with liver cirrhosis from healthy controls by using electronic nose and voltammetric electronic tongue.

Advanced stage detection of liver cirrhosis (LCi) would lead to high mortality rates in patients. Therefore, accurate and non-invasive tools for its early detection are highly needed using human emanations that may reflect this disease. Human breath, along with urine and blood, has long been one of the three main biological media for assessing human health and environmental exposure. The primary objective of this study was to explore the potential of using volatile organic compounds (VOCs) assay of exhaled breath and urine samples for the diagnosis of patients with LCi and healthy controls (HC). For this purpose, we used a hybrid electronic nose (E-nose) combining two sensor families, consisting of an array of five commercial chemical gas sensors and six interdigitated chemical gas sensors based on pristine or metal-doped WO3 nanowires for sensing volatile gases in exhaled breath. A voltammetric electronic tongue (VE-tongue), composed of five working electrodes, was dedicated to the analysis of urinary VOCs using cyclic voltammetry as a measurement technique. 54 patients were recruited for this study, comprising 22 patients with LCi, and 32 HC. The two-sensing systems coupled with pattern recognition methods, namely Principal Component Analysis (PCA) and Discriminant Function Analysis (DFA), were trained to classify data clusters associated with the health status of the two groups. The diagnostic performances of the E-nose and VE-tongue systems were studied by using the receiver operating characteristic (ROC) method. The use of the E-nose or the VE-tongue separately, trained with these appropriate classifiers, showed a slight overlap indicating no clear discrimination between LCi patients and HC. To improve the performance of both electronic sensing devices, an emerging strategy, namely a multi-sensor data fusion technique, was proposed as a second aim to overcome this shortcoming. The data fusion approach of the two systems, at a medium level of abstraction, has demonstrated the ability to assess human health and disease status using non-invasive screening tools based on exhaled breath and urinary VOC analysis. This suggests that exhaled breath as well as urinary VOCs are specific to a disease state and could potentially be used as diagnostic methods.

Graphene Loading with Polypyrrole Nanoparticles for Trace-Level Detection of Ammonia at Room Temperature.

The outstanding versatility of graphene for surface functionalization has been exploited by its decoration with synthesized polypyrrole (PPy) nanoparticles (NPs). A green, facile, and easily scalable for mass production nanocomposite development was proposed, and the resulting PPy@Graphene was implemented in chemoresistive gas sensors able to detect trace levels of ammonia (NH3) under room-temperature conditions. Gas exposure for 5 min revealed that the presence of nanoparticles decorating graphene entail greater sensitivity (13-fold) in comparison to the bare graphene performance. Noteworthy, excellent repeatability (0.7% of relative error) and a low limit of detection of 491 ppb were obtained, together with excellent long-term stability. Besides, an extensive material characterization was conducted, and vibration bands obtained via Raman spectroscopy confirmed the formation of PPy NPs, while X-ray spectroscopy (XPS) revealed the relative abundance of the different species, as polarons and bipolarons. Additionally, XPS analyses were conducted before and after NH3 exposure to assess the PPy aging and the changes induced in their physicochemical and electronic properties. Specifically, the gas sensor was tested during a 5-month period, demonstrating significant stability over time, since just a slight decrease (11%) in the responses was registered. In summary, the present work reports for the first time the use of PPy NPs decorating graphene for gas-sensing purposes, revealing promising properties for the development of unattended gas-sensing networks for monitoring air quality.

On the Use of Pulsed UV or Visible Light Activated Gas Sensing of Reducing and Oxidising Species with WO3 and WS2 Nanomaterials.

This paper presents a methodology to quantify oxidizing and reducing gases using n-type and p-type chemiresistive sensors, respectively. Low temperature sensor heating with pulsed UV or visible light modulation is used together with the application of the fast Fourier transform (FFT) to extract sensor response features. These features are further processed via principal component analysis (PCA) and principal component regression (PCR) for achieving gas discrimination and building concentration prediction models with R2 values up to 98% and RMSE values as low as 5% for the total gas concentration range studied. UV and visible light were used to study the influence of the light wavelength in the prediction model performance. We demonstrate that n-type and p-type sensors need to be used together for achieving good quantification of oxidizing and reducing species, respectively, since the semiconductor type defines the prediction model's effectiveness towards an oxidizing or reducing gas. The presented method reduces considerably the total time needed to quantify the gas concentration compared with the results obtained in a previous work. The use of visible light LEDs for performing pulsed light modulation enhances system performance and considerably reduces cost in comparison to previously reported UV light-based approaches.

Synthesis of p-n Heterojunctions via Aerosol Assisted Chemical Vapor Deposition to Enhance the Gas Sensing Properties of Tungsten Trioxide Nanowires: A Mini-Review.

Here we discuss the aerosol-assisted synthesis of p-n heterojunction metal oxides and we report their gas sensing properties via a short review of the latest results achieved. In particular, we show that the decoration of one-dimensional tungsten oxide (n-type) with nanoparticles of different p-type oxides from transition metals such as Ni, Co or Ir enables achieving a chemical and electronic sensitization of the resulting hybrid metal oxide materials. This leads to remarkable differences in responsiveness to gases, showing that, to some extent, a selective detection of some major pollutant gases (NO2, H2S or NH3) would be possible. Results are critically reviewed, shortcomings are identified and future research directions are given.

Characterization and Analysis of Okoume and Aiele Essential Oils from Gabon by GC-MS, Electronic Nose, and Their Antibacterial Activity Assessment.

Essential oil resins of Aucoumea klaineana (Okoume) and Canarium schweinfurthii (Aiele) species, of the Burseraceae family, were studied to investigate their bioactive constituents and their antibacterial activities. Aiele resin had a higher yield (6.86%) of essential oil than Okoume (3.62%). Twenty-one compounds for Okoume and eighteen for Aiele essential oil were identified using a gas chromatography-mass spectrometry (Gp-C-MS) technique. The main compounds identified in Okoume essential oil were benzenemethanol, α, α,4-trimethyl (28.85%), (+)-3-carene (3,7,7-trimethyl bicyclo[4.1.0]hept-3-ene) (17.93%), D-Limonene ((4R)-1-methyl-4-prop-1-en-2-ylcyclohexene) (19.36%). With regard to the Aiele essential oil, we identified (1R,4S)-1-methyl-4-propan-2-ylcyclohex-2-en-1-ol (26.64%), and 1-methyl-4-propan-2-ylcyclohex-2-en-1-ol (26.83%). Two strains of bacteria, Escherichia coli and Staphylococcus aureus, were used in antibacterial tests. S. aureus was found to be more sensitive to Okoume and Aiele essential oils, with a high inhibition zone ranging from 20 to 16 mm. In comparison, the inhibition zone ranged from 6 to 12 mm for E. coli. An electronic nose (e-nose) combined with pattern analysis methods such as principal component analysis (PCA), discriminant function analysis (DFA), and hierarchical cluster analysis (HCA) were used to discriminate the essential oil samples. In summary, the e-nose and GC-MS allowed the identification of bioactive compounds in the essential oil samples, which have a strong antimicrobial activity, with satisfactory results.