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Since 1970, human activities have permitted the spread of Dengue virus (DENV) and the primary mosquito vectors Aedes spp. to virtually every continent. Infection rates have increased more than 30-fold and it has become the most prevalent arboviral disease in the world. Every year, 3.6 billion people are at risk of infection and there are 390 million new infections, mostly among children. With no vaccine or specific treatment, early detection plays a significant role in decreasing fatality rates. Dengue infection has no pathognomonic clinical features, thus diagnostic tools are essential for diagnosis.In addition to a human transmission cycle, a variety of forest-dwelling non-human primates are hosts for DENV in a sylvatic cycle. Unfortunately, sylvatic cross-over events occur regularly and have resulted in disease outbreaks within humans. Vector surveillance plays a critical role in dengue detection and outbreak prevention. Current laboratory methods for detection and diagnosis of DENV require highly trained personnel and costly equipment that are impractical for regular surveillance and diagnostic use. Thus, new technologies to facilitate and enhance diagnostic and surveillance capabilities within each transmission cycle are urgently needed. This research describes the development of two novel biosensors using single-walled carbon nanotube transducers functionalized for the detection of whole DENV or DENV Non-Structural Protein 1 (NS1). Heparin, an analog of the heparan sulfate proteoglycans that are receptors for DENV, was used as a bioreceptor for detection of whole DENV virions within viral culture. This permits detection of DENV virions from a variety of viral culture-compatible samples; such as fluid or tissue samples from monkeys, vector mosquitos, and humans. Anti-dengue NS1 monoclonal antibodies were used to detect DENV NS1, a clinically accepted biomarker for DENV infection. This biosensor will allow early detection and diagnosis of the disease in Aedes mosquitos and human saliva. Both biosensors were selective and sensitive for their target analyte in a 10-μL sample over the clinically relevant concentration range with detection occurring in only 10-20 min. Each was constructed to be a portable, rapid, and inexpensive diagnostic tool suitable for use by minimally-trained personnel in the field, laboratory, or point-of-care location.

High-performance chemiresistor gas sensor made of sulfide porous GaN decorated with Pt nanoparticles, which shows tunable sensor response and enhanced sensitivity. The fabricated gas sensors show detection of H2 down to 30 ppm at 23 °C after sulfide treatment and Pt decorated porous GaN. The response time and recovery time were equal to 47 s and 113 s, respectively. Density functional theory simulations were used to support the detection mechanism based on sulfide treatment. Adsorption energy calculations showed that H adsorption energy is lowered by the simultaneous presence of S and Pt on the GaN (0001) surface. The density of states (DOS) calculations revealed possibility of bond strengthening when Pt and S is adsorbed on GaN surface along with H, arising from the hybridization of d and p orbitals of Pt and S with that of H 1s orbitals.

MXenes are a promising class of two-dimensional materials with several potential applications, including energy storage, catalysis, electromagnetic interference shielding, transparent electronics, and sensors. Here, we report a novel Mo2CTx MXene sensor for the successful detection of volatile organic compounds (VOCs). The proposed sensor is a chemiresistive device fabricated on a Si/SiO2 substrate using photolithography. The impact of various MXene process conditions on the performance of the sensor is evaluated. The VOCs, such as toluene, benzene, ethanol, methanol, and acetone, are studied at room temperature with varying concentrations. Under optimized conditions, the sensor demonstrates a detection limit of 220 ppb and a sensitivity of 0.0366 Ω/ppm at a toluene concentration of 140 ppm. It exhibits an excellent selectivity toward toluene against the other VOCs. Ab initio simulations demonstrate selectivity toward toluene in line with the experimental results.

In this work, we report the detection and discrimination of five commercially available NESTT K-9 explosive compounds, including 2,4,6-trinitrotoluene (TNT), cyclotrimethylenetrinitramine (RDX), pentaerythritol tetranitrate (PETN), potassium nitrate, and potassium chlorate. An array of 48 chemiresistors were fabricated and assembled with four types of gold nanoparticle sensing materials. The functional groups include tetradecylamine (TDA), octadecylamine (ODA), 3-mercaptopropionic acid (MPA), and 4-aminothiophenol (ATP). Machine learning methods were applied to analyze sensor data. The discrimination accuracy of the sensor array was studied over time at various vapor concentrations ( ${p}/{p}_{0}$ ), using several classifiers, including linear discriminant analysis (LDA), support vector machine (SVM), k-nearest neighbors (KNN), and bagged trees (BT), with five-fold cross-validation. More than 90% accuracy was achieved using datasets with more than 2500 sensor measurements. Sensor arrays and classification algorithms exhibit good stability over a range of vapor concentrations. The results demonstrate the utility of machine learning for detection and classification of volatiles, including explosive and related compounds.

Identifying the components and their relative proportions in the binary mixtures of the structurally similar Volatile Organic Compounds (VOCs) are required for many applications. In this work, the binary vapor mixtures of VOCs with isomeric components at variable combined concentrations ranging from 200 to 2500 ppm are discriminated using a single generic tin oxide gas sensor. Sharp fluctuations in the pellet temperature bring in more valuable analyte nature-related information into the sensor’s response patterns, which can be extracted and used for discriminating among complex mixtures. The classic staircase voltage waveform fails to produce the abrupt variations in the pellet temperature facilitated via the thermal shock induction method applied for the virtual array formation out of a single tin oxide chemiresistor. Linear discriminant analysis is applied after preprocessing and feature selection of the sensor response patterns. Two simple classifiers operating based on the Euclidean distance in the feature space are utilized for analyte classification. The recognitions of binary vapor mixtures of 1-propanol, 2-propanol, 1-butanol, and 2-butanol are demonstrated as examples. A total of 546 individual experiments are carried out to confirm the accuracy of the performance; all the binary test mixtures are identified correctly; with 2.3% of error in compositions determination. The experiments are satisfactorily repeated in the form of independent work sessions within a 1-month time interval to represent the repeatability of the response patterns. The thermal shock induction appears as a replacement for the sensor arrays which suffer from the multi-dimensional drift of the array components.

Applications of molybdenum disulfide (MoS2) in energy storage devices, solar cells, electrocatalysts, and sensors require good electrical conductivity. However, neither of the current ways to prepa...

Due to their tunneling-based charge transport mechanism, gold nanoparticle (GNP) composites attract significant interest for applications as resistive sensors for strain and volatile organic compounds. Here, we present a facile method for patterning and re-functionalization of alkanedithiol cross-linked GNP thin films based on deep ultraviolet photolithography. A lift-off process using a sacrificial layer of polymethyl methacrylate (PMMA) was used in combination with a rapid, spin-coating-based GNP film deposition procedure to fabricate patterned GNP films. Furthermore, PMMA mask layers were utilized for selective molecular doping of individual GNP film chemiresistors in a chemiresistor array with different ligand molecules, leading to altered chemical selectivities. The methods presented in this work are suitable for patterning organically cross-linked GNP films for various sensing applications as well as the fabrication of electronic noses based on GNP film chemiresistor arrays. Due to the photolithographic approach, the deposition and re-functionalization methods outlined in this paper are easily scalable, in contrast to serial techniques such as ink-jet printing or microdispensing.

On the perspective to develop CuO–TiO2 MOS, multilayered Cu and Ti thin layers were alternatively deposited on silicon wafers using 25 keV Ar + ion beam sputtering and, subsequently, oxidized by thermal annealing in air at 400 °C for 24 h. The deposited films have variable ratios of the Cu and Ti % at. One of the main goal is to obtain such multilayers avoiding the presence of Cu–Ti–O compounds. The samples were characterized in terms of composition (by RBS and SIMS analyses) and morphology (by AFM and SEM investigations). In particular, SIMS maps allows to observe the spatial distribution and thickness of each phase of the Cu/Ti multilayers, and further to observe Cu diffusion and mixing with Ti, as well as phase separation of CuO and TiO2 in the samples. The reasons of this effect represent an open issue that has to investigated, in order to improve the MOS fabrication.

Single-walled carbon nanotubes (SWNTs) are incorporated in different device configurations such as chemiresistors and field-effect transistors (FETs) as a sensing element for the fabrication of highly sensitive and specific biochemical sensors. For this purpose, sorting and aligning of semiconducting SWNTs between the electrodes is advantageous. In this work, a silicon shadow mask fabricated using conventional semiconductor processes and silicon bulk micromachining was used to make metal contacts over SWNTs with a minimum feature of 1 μm gap between the electrodes. The developed silicon shadow mask-based metal contact patterning process is cost-effective and free from photoresist (PR) chemical coatings and thermal processing. After a detailed investigation, sodium dodecyl sulfate (SDS), an anionic surfactant, along with ultrasonication process, was found to be effective for the removal of unclamped and metallic SWNTs, resulting in aligned and clamped semiconducting SWNTs between the electrodes. The presence of aligned semiconducting SWNTs was confirmed using atomic force microscopy (AFM), field emission scanning electron microscopy (FESEM), and Raman spectroscopy techniques. The fabricated devices were tested for nitrogen dioxide (NO2) gas sensing as a test case. The sensitivity enhancement of ∼21 to 76% in the 20-80 ppm NO2 concentration range has been observed in the case of aligned semiconducting SWNT devices compared to the random network SWNT-based sensors.

In this work, a ɤ-MnO2 flower-like nanostructure was synthesized. The structural and morphological characterization of ɤ-MnO2 flower-like nanostructure was performed by X-ray powder diffraction (XRD), N2–sorption studies (Brunauer–Emmett–Teller surface area measurements) (BET), particle size distribution (PSA), energy dispersive X-ray spectroscopy (EDS), and scanning electron microscopy (SEM). The ammonia gas sensor was fabricated based on the high surface area of ɤ-MnO2 flower-like nanostructure. According to the results, tetragonal tunnels were advantageous for trapping and adsorption-desorption of NH3 gas molecules. The results indicated that the gas sensor based on ɤ-MnO2 flower-like nanostructure had high sensitivity (40% response to 100 mg L−1 NH3 gas), selectivity, detectability up to 2 mg L−1 NH3 gas, long-term stability, and repeatability for two months at room temperature. Of the study also examined the effect of compounds such as ethanol, acetone, hydrazine, n-heptane, monomethylamine (MMA), triethylamine (TEA) and trimethylamine (TMA) on the detection of ammonia gas.

Semiconducting metal oxides are widely used for gas sensors. The resulting chemiresistor devices, however, suffer from non-linear responses, signal fluctuations and gas cross-sensitivities, which limits their use in demanding applications of air-quality monitoring. Here, we show that conventional semiconducting metal oxide materials can provide high-performance sensors using an impedance measurement technique. Our approach is based on dielectric excitation measurements and yields sensors with a linear gas response (R2 > 0.99), broad dynamic range of gas detection (six decades of concentrations) and high baseline stability, as well as reduced humidity and ambient-temperature effects. We validated the technique using a range of commercial sensing elements and a range of gases in both laboratory and field conditions. Our approach can be applied to both n- and p-type semiconducting metal oxide materials, and we show that it can be used in wireless sensor networks, and drone-based and wearable environmental and industrial gas monitoring. Semiconducting metal oxide gas sensors with a linear response, broad dynamic range and high baseline stability can be created with the help of a dielectric excitation technique.

In this paper, an impedance-transduced sensor is developed based on a nanostructured graphene (GN) and poly (methyl methacrylate) (PMMA) sensing film for the detection of individual volatile organic compounds (VOCs) in aqueous media. Benefiting from a porous and high surface area, the nanostructured nanofiber is characterized by scanning electron microscopy (SEM) and optimized by the electrochemical impedance spectroscopy (EIS) technique. The recorded EIS data indicate the selective recognition of four VOCs of interest at a constant pH while there is no redox probe. The non-faradaic responses to each analyte at different concentrations are correlated with a three-element equivalent circuit (resistances of the solution and the film, and a pseudo-capacitance). To analyze the ability of the sensing film in distinguishing between VOCs with similar average boiling points, the values of the individual equivalent circuit elements are used as features and clustered in three-dimensional (3D) plots. Among the features, the two representing the maximum differences between the VOCs are represented in a two-dimensional (2D) plot to show the selectivity of the sensor. The feature extraction analysis demonstrates that the constant phase element (CPE) of the equivalent circuit is a more accurate predictor of VOCs than the interfacial capacitance. These results show high selectivity of the sensorial platform due to the synergistic pairing of nanostructured GN and PMMA.

Ethylene is a dynamic plant hormone, and its temporal monitoring can be used to glean insight into plant health and status. However, the real-time distributed detection of ethylene at trace levels under ambient conditions remains a challenge. We report a single-walled carbon nanotube-based chemiresistor catalyst combination that can detect ppb levels of ethylene in air. Cycling between Pd(II) and Pd(0) via Wacker oxidation with a nitrite cocatalyst imparts response discrimination driven by the chemoselectivity of the chemical transformation. Sensitivity is controlled by a combination of the chemical reaction efficiency and the n-doping strength of the Pd(0) species generated in situ. The covalent functionalization of the carbon nanotube sidewall with pyridyl ligands drastically improves the device sensitivity via enhanced n-doping. The utility of this ethylene sensor is demonstrated in the monitoring of senescence in red carnations and purple lisianthus flowers., Okay, bloomer: Wacker oxidation is used as a signal transduction mechanism for the selective and sensitive detection of ethylene in air via chemiresistive sensing. Using this system, the senescence of lisianthus flowers and carnations is monitored.

Ethanol is widely used in preparing alcoholic beverages, thermometers, perfumes, flavorings, colorings, and medicines. Ethanol sensors are mainly used in biofuel plants and breweries to quantify ethanol concentrations through infrared spectral studies as well as in forensics and direct alcohol fuel cells. This overview discusses the various materials and methods used in the determination of ethanol concentrations in sensing applications using resistance-based measurements. A comprehensive view of the different nanomaterials that have been studied is provided, with an outlook on the shortcomings as well as merits of the material architectures. Statistical methods of interpreting sensing performance are analyzed as well, through which possibilities for improving the adaptability of materials towards their end use is projected.

A paper based chemiresistor has been fabricated to selectively sense ethanol in human breath. The chemiresistor was composed of a sensing mixture of multiwall-carbon-nano-tubes (MWCNTs), poly (diallyl-dimethyl-ammonium chloride) (PDDA), alcohol dehydrogenase (ADH), and coenzyme (NADH). The aluminum electrode was deposited on the paper surface, followed by drop-casting of the aforementioned sensing mixture. The resistance of the sensors was measured by exposing the same in gas-vapor mixture as well as the sample solution. The surface-modified MWCNTs specifically broke down ethanol present in the gas-vapor mixture or in a solution to generate a quantitative electronic response proportional to the ethanol concentration. Subsequently, the interference of other volatile organic materials was also tested to prove the selectivity and sensitivity of the sensor towards ethanol in the presence of different volatile organic compounds (VOCs). The variation of the resistance during the interaction between sensor and ethanol was also characterized by measuring the surface potential of the channel material under ethanol exposure using Kelvin probe force microscopy (KPFM). The sensor was integrated with a voltage divider circuit, a display, and a microcontroller unit to make a proof-of-concept prototype for the point-of-care (POC) detection of ethanol in human breath.

Lanthanum oxide nanoparticles were synthesized by a simple reverse micelle method and characterized by X-ray powder diffraction (XRD), Brunauer–Emmett–Teller (BET) surface area measurements, particle size distribution (PSA), energy-dispersive X-ray spectroscopy (EDS), scanning electron microscopy (SEM), and transmission electron microscopy (TEM) techniques. The lanthanum oxide nanoparticles were coated on an interdigitated microelectrode (IDE) surface by the drop-coating method. The sensor response was investigated by measuring the electrical resistance of the sensor when dimethylamine gas was inserted into the test chamber. Within the 3–3300 mg L−1 concentration range, the sensor response and recovery times were 27–184 s and 3–10 s, respectively. The results indicated that the La2O3 sensor exhibited an amazing performance in the detection of dimethylamine gas at room temperature and provided a significant response (Rg/Ra = 7.4) for 100 mg L−1 of dimethylamine gas.

The detection of nitric dioxide (NO2) at the parts-per-trillion (ppt) level is critical for both environmental monitoring and human health. However, none of the chemiresistors reported to date can detect NO2 at the parts-per-trillion (ppt) level due to the low sensitivity of the sensory materials. In this work, an ion-in-conjugation polymer para-polyphenylsquaraine (p-PPS) was designed and fabricated into an NO2 chemiresistor. The sensor had the highest sensitivity of 1450 ppm−1 (at 100 ppb) and the lowest detection limit of 40 ppt among all reported chemiresistors. In addition, p-PPS showed ultrahigh selectivity, where other interfering gases had less than 1/1887th of the signal of NO2 under the same concentration (10 ppm). Calculations, in situ infrared spectroscopy and sum frequency generation spectroscopy (SFG) revealed that the ion-in-conjugation-inspired H-bonding between p-PPS and NO2 led to such high sensitivity. Our results highlight the potential of the concept of ion-in-conjugation in the design of highly sensitive gas sensory materials.

The agriculture industry in its current form is under considerable threat due to rapidly changing climate conditions and severe weather brought upon by global warming. This global food production crisis has prompted a growing affluence towards greenhouse farming which is reported to increase the per acre yield by up to 15 times when compared to traditional open-air farming. The increase in crop production capacity is attributed in part to the controlled environmental conditions which is made possible through the implementation of gas sensing technologies. All gas sensing technologies implement a sensing material which acts as the chemical interface between the surrounding environment and the sensor. However, a single sensing material will often interact with multiple target parameters therefore requiring arrays of gas sensors coated with different sensing materials to monitor the concentration of a single target gas. These arrays of gas sensors coupled with the required driving and readout circuitries are often referred to as electronic Nose (eNose) systems, where selectivity is dependent on the number of sensors in the array. In this work, impedance-based gas sensors are designed and developed as a promising candidate technology in reducing the number of sensors required in an eNose system employed in complex environments. Fringing field utilization is identified as a critical design parameter and two unique sensor designs are proposed which utilize a greater volume of fringing fields when compared to the three most commonly used sensor designs. The performance of these proposed designs is compared against the conventional sensor designs through simulation and controlled environmental experimentation. The proposed designs exhibit a capacitive response more than 100 times greater and an impedance sensitivity 20 times greater than the highest performing conventional benchmark.

The remarkable potential of breath analysis in medical care and diagnosis, and the consequent development of electronic noses, is currently attracting the interest of the research community. This is mainly due to the possibility of applying the technique for early diagnosis, screening campaigns, or tracking the effectiveness of treatment. Carbon nanotubes (CNTs) are known to be good candidates for gas sensing, and they have been recently considered for the development of electronic noses. The present work has the aim of reviewing the available literature on the development of CNTs-based electronic noses for breath analysis applications, detailing the functionalization procedure used to prepare the sensors, the breath sampling techniques, the statistical analysis methods, the diseases under investigation, and the population studied. The review is divided in two main sections: one focusing on the e-noses completely based on CNTs and one reporting on the e-noses that feature sensors based on CNTs, along with sensors based on other materials. Finally, a classification is presented among studies that report on the e-nose capability to discriminate biomarkers, simulated breath, and animal or human breath.

In recent times, an increasing number of applications in different fields need gas sensors that are miniaturized but also capable of distinguishing different gases and volatiles. Thermal electronic noses are new devices that meet this need, but their performance is still under study. In this work, we compare the performance of two thermal electronic noses based on SnO2 and ZnO nanowires. Using five different target gases (acetone, ammonia, ethanol, hydrogen and nitrogen dioxide), we investigated the ability of the systems to distinguish individual gases and estimate their concentration. SnO2 nanowires proved to be more suitable for this purpose with a detection limit of 32 parts per billion, an always correct classification (100%) and a mean absolute error of 7 parts per million.

In this study, we developed fast and highly sensitive, label-free Ca-doped cupric oxide (CuO) based che-miresistive biosensors to detect C-reactive protein (CRP). The Successive Ionic Layer Adsorption and Reaction (SILAR) method was used to deposit pure and Ca-doped CuO thin films on interdigitated gold electrodes. Film surfaces were functionalized with monoclonal anti-C-reactive protein antibody (anti-CRP) by random physisorption method. Sensor fabrication steps were monitored using the linear sweep vol-tammetry method. Scanning electron microscopy was used to investigate the surface morphology. Energy-dispersive X-ray spectroscopy was used to determine the elemental composition. The structure of the films was investigated by the powder X-ray diffractometry method. Sensor parameters were determined by the change in sensor resistance over time. The sensors showed a good response to CRP with a linear detection range of 0.1-5.0 pg/ml, which was within the clinically significant range. Detection limits of 49.61 and 48.81 ng/ml were estimated using the standard deviation of the y-intercept and the standard deviation of the regression line, respectively. Dynamic response times of all fabricated sensors were found to be less than 30 s (c) 2022 Elsevier B.V. All rights reserved.

Toxic and nontoxic volatile organic compound (VOC) gases are emitted into the atmosphere from certain solids and liquids as a consequence of wastage and some common daily activities. Inhalation of toxic VOCs has an adverse effect on human health, so it is necessary to monitor their concentration in the atmosphere. In this work, we report on the fabrication of inorganic nanotube (INT)-tungsten disulfide, paper-based graphene–PEDOT:PSS sheet and WS2 nanotube-modified conductive paper-based chemiresistors for VOC gas sensing. The WS2 nanotubes were fabricated by a two-step reaction, that is oxide reduction and sulfurization, carried out at 900 °C. The synthesized nanotubes were characterized by FE-SEM, EDS, XRD, Raman spectroscopy, and TEM. The synthesized nanotubes were 206–267 nm in diameter. The FE-SEM results show the length of the nanotubes to be 4.5–8 µm. The graphene–PEDOT:PSS hybrid conductive paper sheet was fabricated by a continuous coating process. Then, WS2 nanotubes were drop-cast onto conductive paper for fabrication of the chemiresistors. The feasibility and sensitivity of the WS2 nanotube-modified paper-based chemiresistor were tested in four VOC gases at different concentrations at room temperature (RT). Experimental results show the proposed sensor to be more sensitive to butanol gas when the concentration ranges from 50 to 1000 ppm. The limit of detection (LOD) of this chemiresistor for butanol gas was 44.92 ppm. The WS2 nanotube-modified paper-based chemiresistor exhibits good potential as a VOC sensor with the advantages of flexibility, easy fabrication, and low fabrication cost.