Search Results (4,650)

By using density functional theory (DFT), the adsorption behavior of gas molecules on defective graphene doped with manganese and nitrogen were investigated. The geometric structure, electronic structure, and magnetic properties of two substrates were calculated and the sensing mechanism was also analyzed. The results indicate that the MnSV-GP and MnN₃-GP have stronger structural stability, in which Mn atoms and their coordination atoms will become the adsorption point for five gas molecules (CH₂O, CO, N₂O, SO₂, and NH₃), respectively. Moreover, at room temperature (298 K), the recovery time of the MnSV-GP sensor for N₂O gas molecules is approximately 1.1 s. Therefore, it can be concluded that the MnSV-GP matrix as a magnetic gas sensor has a promising potential for detecting N₂O. These results also provide a new pathway for the potential application of Mn-doped graphene in the field of gas sensors. Full article

To improve our understanding of Bacillus subtilis growth and biofilm formation under different environmental conditions, two versions of a microfluidic reactor with two channels separated by a polydimethylsiloxane (PDMS) membrane were developed. The gas phase was introduced into the channel above the membrane, and oxygen transfer from the gas phase through the membrane was assessed by measuring the dissolved oxygen concentration in the liquid phase using a miniaturized optical sensor and oxygen-sensitive nanoparticles. B. subtilis biofilm formation was monitored in the growth channels of the microbioreactors, which were designed in two shapes: one with circular extensions and one without. The volumes of these microbioreactors were (17 ± 4) μL for the reactors without extensions and (28 ± 4) μL for those with extensions. The effect of microbioreactor geometry and aeration on B. subtilis biofilm growth was evaluated by digital image analysis. In both microbioreactor geometries, stable B. subtilis biofilm formation was achieved after 72 h of incubation at a growth medium flow rate of 1 μL/min. The amount of oxygen significantly influenced biofilm formation. When the culture was cultivated with a continuous air supply, biofilm surface coverage and biomass concentration were higher than in cultivations without aeration or with a 100% oxygen supply. The channel geometry with circular extensions did not lead to a higher total biomass in the microbioreactor compared to the geometry without extensions. Full article

A pipeline network is the most efficient and rapid way to transmit natural gas from source to destination. The smooth operation of natural gas pipeline control stations depends on electrical equipment such as data loggers, control systems, surveillance, and communication devices. Besides having a reliable and consistent power source, such control stations must also have cost-effective and intelligent monitoring and control systems. Distributed processes are monitored and controlled using supervisory control and data acquisition (SCADA) technology. This paper presents an Internet of Things (IoT)-based, open-source SCADA architecture designed to monitor a Hybrid Power System (HPS) at a remote natural gas pipeline control station, addressing the limitations of existing proprietary and non-configurable SCADA architectures. The proposed system comprises voltage and current sensors acting as Field Instrumentation Devices for required data collection, an ESP32-WROOM-32E microcontroller that functions as the Remote Terminal Unit (RTU) for processing sensor data, a Blynk IoT-based cloud server functioning as the Master Terminal Unit (MTU) for historical data storage and human–machine interactions (HMI), and a GSM SIM800L module and a local WiFi router for data communication between the RTU and MTU. Considering the remote locations of such control stations and the potential lack of 3G, 4G, or Wi-Fi networks, two configurations that use the GSM SIM800L and a local Wi-Fi router are proposed for hardware integration. The proposed system exhibited a low power consumption of 3.9 W and incurred an overall cost of 40.1 CAD, making it an extremely cost-effective solution for remote natural gas pipeline control stations. Full article

Accurately detecting atmospheric carbon dioxide is a vital part of responding to the global greenhouse effect. Conventional off-axis integral cavity detection systems are computationally intensive and susceptible to environmental factors. This study deploys an Extreme Learning Machine model incorporating a cascaded integrator comb (CIC) filter into the off-axis integrating cavity. It is shown that appropriate parameters can effectively improve the performance of the instrument in terms of lower detection limit, accuracy, and root mean square deviation. The proposed method is incorporated successfully into a monitoring station situated near an industrial area for detecting atmospheric carbon dioxide (CO₂) concentration daily. Full article

Battery power is crucial for wearable devices as it ensures continuous operation, which is critical for real-time health monitoring and emergency alerts. One solution for long-lasting monitoring is energy harvesting systems. Ensuring a consistent energy supply from variable sources for reliable device performance is a major challenge. Additionally, integrating energy harvesting components without compromising the wearability, comfort, and esthetic design of healthcare devices presents a significant bottleneck. Here, we show that with a meticulous design using small and highly efficient photovoltaic (PV) panels, compact thermoelectric (TEG) modules, and two ultra-low-power BQ25504 DC-DC boost converters, the battery life can increase from 9.31 h to over 18 h. The parallel connection of boost converters at two points of the output allows both energy sources to individually achieve maximum power point tracking (MPPT) during battery charging. We found that under specific conditions such as facing the sun for more than two hours, the device became self-powered. Our results demonstrate the long-term and stable performance of the sensor node with an efficiency of 96%. Given the high-power density of solar cells outdoors, a combination of PV and TEG energy can harvest energy quickly and sufficiently from sunlight and body heat. The small form factor of the harvesting system and the environmental conditions of particular occupations such as the oil and gas industry make it suitable for health monitoring wearables worn on the head, face, or wrist region, targeting outdoor workers. Full article

In this work, we describe the design, manufacturing development, and refinement of a chemical detection platform designed to identify specific odorants in the natural gas industry. As the demand for reliable and sensitive volatile organic compound (VOC) detection systems is growing, our project aimed to construct multiple prototypes to enhance our detection capabilities and provide portable detection platforms. Throughout the development process across nominally identical and duplicated instruments, various failure modes were encountered, which provided insight into the design and manufacturing challenges present when designing such platforms. We conducted a post hoc root cause analysis for each failure mode, leading to a series of design modifications and solutions. This paper details these design and manufacturing challenges, the analytical methods used to diagnose and address them, and the resulting improvements in system performance. In the end, a debugging flow chart is presented to aid future researchers in solving the possible issues that could be encountered. Our findings show the complexities of bespoke chemical sensor design for unique applications and highlight the critical importance of iterative testing and problem-solving in the development of industrial detection technologies. Achieving consistency across devices is essential for optimizing device-to-device efficiency. The work presented is the first step towards ensuring uniform performance across a production run of chemically sensitive devices. In the future, a universal device calibration model will be implemented, eliminating the need to collect data from each individual device. Full article

The effects of Au addition on the acetone response of Cu₂O-added porous SnO₂ (pr-Cu₂O-SnO₂) powders, which were synthesized by ultrasonic spray pyrolysis employing polymethyl methacrylate microspheres as a template, were investigated in this study. The 3.0 wt% Au-added pr-Cu₂O-SnO₂ sensor showed the largest acetone response among all sensors. In addition, the magnitude of the acetone response was much larger than those of the ethanol and toluene responses. The catalytic activities of these gases over Au-added pr-Cu₂O-SnO₂ powders were also examined to clarify the key factors affecting their acetone-sensing properties. The Au addition increased the complete oxidation activity of all gases, and the complete oxidation activity of acetone was much higher than those of ethanol and toluene. These results indicate that the oxidation behavior during the gas-diffusion process in the sensitive Au-added pr-Cu₂O-SnO₂ layer of the sensors is quite important in enhancing the acetone-sensing properties. Full article

Flexible materials with both in-plane and out-of-plane piezoelectric coefficients are needed in the development of advanced nanoelectromechanical systems. However, the challenge is to find flexible materials with the coexistence of in-plane and -out-of-plane piezoelectric responses, which hinders the progress of high-performance piezoelectric sensor development. In this paper, we propose the flexible XMAY₂ (X = I; M = Ti, Zr; A = Al, Ga; Y = S, Se) monolayers, which belong to the group III-VI XMAY₂ family, which showcase notable in-plane and out-of-plane piezoelectric coefficients. The in-plane (d₁₁) and out-of-plane (d₃₁) piezoelectric coefficients of the XMAY₂ monolayers vary from 5.20 to 7.04 pm/V and from −0.23 to 0.48 pm/V, respectively. The large in-plane and out-plane piezoelectric responses coexist (d₁₁ = 7.04 pm/V; d₃₁ = 0.48 pm/V) in the IZrGaS₂ monolayer, which is larger than other materials in the XMAY₂ family, such as SMoSiN₂ (d₁₁ = 2.51; d₃₁ = 0.28 pm/V). In addition, the mechanical and transport properties of XMAY₂ demonstrate its impressive flexibility characteristics as well as its efficient electrical conductivity. Due to inversion symmetry breaking in both atomic structure and charge distribution of XMAY₂ monolayers, the group III-VI XMAY₂ family exhibits a potentially rich scope of applications in the field of piezoelectricity. Full article

The diagnosis of inflammatory bowel disease (IBD) in children and the need to distinguish between subtypes (Crohn’s disease (CD) and ulcerative colitis (UC)) requires lengthy investigative and invasive procedures. Non-invasive, rapid, and cost-effective tests to support these diagnoses are needed. Faecal volatile organic compounds (VOCs) are distinctive in IBD. VOC profiles can be rapidly determined using a gas chromatography–sensor device (OdoReader©). In an inception-cohort of children presenting with suspected IBD, we directly compared the diagnostic fidelity of faecal calprotectin (FCP, a non-specific protein marker of intestinal inflammation) with OdoReader© VOC profiles of children subsequently diagnosed with IBD with matched controls diagnosed with other gastrointestinal conditions. The OdoReader© was 82% (95% confidence interval 75–89%) sensitive and 71% (61–80%) specific but did not outperform FCP (sensitivity 93% (77–99%) and specificity 86% (67–96%); 250 µg/g FCP cut off) in the diagnosis of IBD from other gastrointestinal conditions when validated in a separate sample from the same cohort. However, unlike FCP and better than other similar technologies, the OdoReader© could distinguish paediatric CD from UC (up to 88% (82–93%) sensitivity and 80% (71–89%) specificity in the validation set) and justifies further validation in larger studies. A non-invasive test based on VOCs could help streamline and limit invasive investigations in children. Full article

Illicit drug production in clandestine laboratories involves the use of large quantities of different chemicals that can be obtained for legitimate purposes. The identification of these chemicals, including reagents, catalyzers and solvents, is crucial for forensic investigations. From a legal point of view, a drug precursor is a material that is specific and critical to the production of a finished chemical and that constitutes a significant portion of the final molecular structure of the drug. In this study, a gas chromatography quartz-enhanced photoacoustic spectroscopy (GC-QEPAS) sensor—in conjunction with a deep learning model—was evaluated for its effectiveness in the detection and identification of interesting compounds for the production of amphetamine, methamphetamine, 3,4-methylenedioxymethamphetamine (MDMA), phenylcyclohexyl piperidine (PCP), and cocaine. The GC-QEPAS sensor includes a gas sampler, a fast GC for separation, and a QEPAS detector, which excites molecules exiting the GC column using a quantum cascade laser to provide the infra-red (IR) spectrum. The on-site capability of the GC-QEPAS system offers significant advantages over the current instruments employed in this field, including rapid analysis, which is crucial in field operations. This allows law enforcement to quickly identify specimens of interest on site. The system’s performance was validated by taking into account the limit of detection, repeatability, and within-laboratory reproducibility. The results showed excellent repeatability and reproducibility for both the GC and QEPAS modules. The deep learning model, a multilayer perceptron neural network, was trained using IR spectra and retention times, achieving very high classification accuracy in the testing conditions. This study demonstrated the efficacy of the GC-QEPAS sensor combined with a deep learning model for the reliable identification of drug precursors, providing a robust tool for law enforcement during criminal investigations in clandestine laboratories. Full article

Humidity is a well-known interference factor in metal oxide (MOX) gas sensors, significantly impacting their performance in various applications such as environmental monitoring and medical diagnostics. This study investigates the effects of adsorbed water on MOX conductivity using two different materials: pure tin oxide (SnO₂) and a tin–titanium–niobium oxide mixture (SnTiNb)_xO₂ (STN). The results reveal that (SnTiNb)_xO₂ sensors exhibit reduced sensitivity to humidity compared to pure tin oxide, rendering them more suitable for applications where humidity presence is critical. We aimed to shed light on a still controversial debate over the mechanisms involved in the water surface interactions for the aforementioned materials also by exploring theoretical studies in the literature. Experimental analysis involves varying temperatures (100 to 800 °C) to understand the kinetics of surface reactions. Additionally, a brief high-temperature heating method is demonstrated to effectively remove adsorbed humidity from sensor surfaces. The study employs Arrhenius-like plots for graphical interpretation, providing insights into various water adsorption/desorption phenomena. Overall, this research contributes to a deeper understanding of the role of humidity in MOX gas sensor mechanisms and offers practical insights for sensor design and optimization. Full article

Fast, accurate, real-time measurement of gas concentration is an important task for preventing coal mining disasters. In order to develop an accurate monitoring method for methane gas concentration at different locations in a mine environment, a non-source optical fiber sensor for multi-point methane detection has been developed in this paper. A 16-channel fiber splitter and a multi-channel time-sharing acquisition module are employed within the sensor, enabling simultaneous detection of methane gas at 16 points by a host. Furthermore, the methane sensors are connected to the monitoring host via an all-optical method, achieving non-source and long-range detection of methane. To assess the performance of the methane gas sensor, experiments were conducted to evaluate its detection range, response time, and stability. The results indicated that the average detection error was approximately 1.84% across the full range, and the response time did not exceed 10 s. The minimum detection limit of the sensor, as determined by the 1σ criteria, was obtained as 58.42 ppm. Additionally, the concentrations of methane gas measured at varying distances (1 km, 2 km, 5 km) were found to be essentially consistent over an extended period. These results suggest that the development of this non-source optical fiber sensor holds significant potential for providing a method for mine environment, multi-point online methane gas detection. Full article

Polymer modification has been established as a cost-effective, simple, in situ method for overcoming some of the inherent disadvantages of boron-doped diamond (BDD) electrodes, and its application has been extended to reliable, low-cost environmental monitoring solutions. The present review focuses on modifying BDD electrodes with semi-conductive polymers acting as redox mediators. This article reports on the development of a 3-methyl thiophene-modified boron-doped diamond (BDD/P3MT) sensor for the electrochemical determination of total phenolic compounds (TPCs) in tea samples, using gallic acid (GA) as a marker. GA is a significant polyphenol with various biological activities, making its quantification crucial. Thus, a simple, fast, and sensitive GA sensor was fabricated using the electroanalytical square wave voltammetry (SWV) technique. The sensor utilizes a semi-conductive polymer, 3-methyl thiophene, as a redox mediator to enhance BDD’s sensitivity and selectivity. Electrochemical synthesis was used for polymer deposition, allowing for greater purity and avoiding solubility problems. The BDD/P3MT sensor exhibits good electrochemical properties, including rapid charge transfer and a large electrochemical area, enabling GA detection with a limit of detection of 11 mg/L. The sensor’s response was correlated with TPCs measured by the Folin–Ciocalteu method. Square wave voltammetry (SWV) showed a good linear relationship between peak currents and GA concentrations in a wide linear range of 3–71 mg/L under optimal conditions. The BDD/P3MT sensor accurately measured TPCs in green tea, rooibos tea, and black tea samples, with green tea exhibiting the highest TPC levels. The results demonstrate the potential of the modified BDD electrode for the rapid and accurate detection of phenolic compounds in tea, with implications for quality control and antioxidant activity assessments. The prolific publications of the past decade have established BDD electrodes as robust BDD sensors for quantifying polyphenols. Fruits, vegetables, nuts, plant-derived beverages such as tea and wine, traditional Eastern remedies and various herbal nutritional supplements contain phenolic chemicals. The safety concerns of contaminated food intake are significant health concerns worldwide, as there exists a critical nexus between food safety, nutrition, and food security. It has been well established that green tea polyphenol consumption promotes positive health effects. Despite their potential benefits, consuming high amounts of these polyphenols has sparked debate due to concerns over potential negative consequences. Full article

Personal protective equipment (PPE) has been universally recognized for its role in protecting workers from injuries and illnesses. Smart PPE integrates Internet of Things (IoT) technologies to enable continuous monitoring of workers and their surrounding environment, preventing undesirable events, facilitating rapid emergency response, and informing rescuers of potential hazards. This work presents a smart PPE system with a sensor node architecture designed to monitor workers and their surroundings. The sensor node is equipped with various sensors and communication capabilities, enabling the monitoring of specific gases (VOC, CO₂, CO, O₂), particulate matter (PM), temperature, humidity, positional information, audio signals, and body gestures. The system utilizes artificial intelligence algorithms to recognize patterns in worker activity that could lead to risky situations. Gas tests were conducted in a special chamber, positioning capabilities were tested indoors and outdoors, and the remaining sensors were tested in a simulated laboratory environment. This paper presents the sensor node architecture and the results of tests on target risky scenarios. The sensor node performed well in all situations, correctly signaling all cases that could lead to risky situations. Full article