Search Results (420)

Bioelectrical signal measurements play a crucial role in clinical diagnosis and continuous health monitoring. Conventional wet electrodes, however, present limitations as they are conductive gel for skin irritation and/or have inflexibility. Here, we developed a cost-effective and user-friendly stretchable dry electrode constructed with a flexible network of Ag/AgCl nanowires embedded in polydimethylsiloxane (PDMS). We compared the performance of the stretched Ag/AgCl nanowire electrode with commonly used commercial wet electrodes to measure electrocardiogram (ECG), electromyogram (EMG), and electroencephalogram (EEG) signals. All the signal-to-noise ratios (SNRs) of the as-fabricated or stretched (50% tensile strain) Ag/AgCl nanowire electrodes are higher than that measured by commercial wet electrodes as well as other dry electrodes. The evaluation of ECG signal quality through waveform segmentation, the signal quality index (SQI), and heart rate variability (HRV) reveal that both the as-fabricated and stretched Ag/AgCl nanowire electrode produce high-quality signals similar to those obtained from commercial wet electrodes. The stretchable electrode exhibits high sensitivity and dependability in measuring EMG and EEG data, successfully capturing EMG signals associated with muscle activity and clearly recording α-waves in EEG signals during eye closure. Our stretchable dry electrode shows enhanced comfort, high sensitivity, and convenience for curved surface biosignal monitoring in clinical contexts. Full article

Detecting stress is important for improving human health and potential, because moderate levels of stress may motivate people towards better performance at cognitive tasks, while chronic stress exposure causes impaired performance and health risks. We propose a Brain–Computer Interface (BCI) system to detect stress in the context of high-pressure work environments. The BCI system includes an electroencephalogram (EEG) headband with dry electrodes and an electrocardiogram (ECG) chest belt. We collected EEG and ECG data from 40 participants during two stressful cognitive tasks: the Cognitive Vigilance Task (CVT), and the Multi-Modal Integration Task (MMIT) we designed. We also recorded self-reported stress levels using the Dundee Stress State Questionnaire (DSSQ). The DSSQ results indicated that performing the MMIT led to significant increases in stress, while performing the CVT did not. Subsequently, we trained two different models to classify stress from non-stress states, one using EEG features, and the other using heart rate variability (HRV) features extracted from the ECG. Our EEG-based model achieved an overall accuracy of 81.0% for MMIT and 77.2% for CVT. However, our HRV-based model only achieved 62.1% accuracy for CVT and 56.0% for MMIT. We conclude that EEG is an effective predictor of stress in the context of stressful cognitive tasks. Our proposed BCI system shows promise in evaluating mental stress in high-pressure work environments, particularly when utilizing an EEG-based BCI. Full article

The construction industry is actively developing remote-controlled excavators to address labor shortages and improve work safety. However, visually induced motion sickness (VIMS) remains a concern in the remote operation of construction machinery. To predict the occurrence and severity of VIMS, we developed a prototype system that acquires multiple physiological signals with different mechanisms under a low burden and detects VIMS from the collected data. Signals during VIMS were recorded from nine healthy adult males operating excavator simulators equipped with multiple displays and a head-mounted display. Light gradient-boosting machine-based VIMS detection binary classification models were constructed using approximately 30,000 s of time-series data, comprising 23 features derived from the physiological signals. These models were validated using leave-one-out cross-validation on seven participants who experienced severe VIMS and evaluated through area under the curve (AUC) scores. The mean receiver operating characteristic curve AUC score was 0.84, and the mean precision–recall curve AUC score was 0.71. All features were incorporated into the models, with saccade frequency and skin conductance response identified as particularly important. These trends aligned with subjective assessments of VIMS severity. This study contributes to advancing the use of remote-controlled machinery by addressing a critical challenge to operator performance and safety. Full article

PEMFCs play a key role in the energy transition scenarios thanks to the zero emissions, versatility, and power density. PEMFC performances are improved optimizing water management to ensure proper ion transport: it is well known that a well-balanced water content avoids either electrodes flooding or membrane drying, causing gas starvation at the active sites or low proton conductivity, respectively. In this paper, an analytical formulation for water transport dynamics within the membrane, derived from membrane water balance, is proposed to overcome the limitations of PEM dynamics model largely adopted in the literature. The dynamics is simulated thanks to the introduction of a characteristic time with a closed analytical form, which is general and easily implementable for any application where both low computational time and high accuracy are required. Furthermore, the net water molar fluxes at the membrane boundaries can be easily computed as well for a cell’s simulation. The analytical formulation has a strong dependency on the operative conditions, as well as physical parameters of the membrane itself. From the proposed formulation, for a 200 µm membrane, the characteristic time can vary from 5 s up to 50 s; this example shows how control strategies must consider PEM dynamic behavior. Full article

Emotion is an intricate cognitive state that, when identified, can serve as a crucial component of the brain–computer interface. This study examines the identification of two categories of positive and negative emotions through the development and implementation of a dry electrode electroencephalogram (EEG). To achieve this objective, a dry EEG electrode is created using the silver-copper sintering technique, which is assessed through Scanning Electron Microscope (SEM) and Energy Dispersive X-ray Analysis (EDXA) evaluations. Subsequently, a database is generated utilizing the designated electrode, which is based on the musical stimulus. The collected data are fed into an improved deep network for automatic feature selection/extraction and classification. The deep network architecture is structured by combining type 2 fuzzy sets (FT2) and deep convolutional graph networks. The fabricated electrode demonstrated superior performance, efficiency, and affordability compared to other electrodes (both wet and dry) in this study. Furthermore, the dry EEG electrode was examined in noisy environments and demonstrated robust resistance across a diverse range of Signal-To-Noise ratios (SNRs). Furthermore, the proposed model achieved a classification accuracy of 99% for distinguishing between positive and negative emotions, an improvement of approximately 2% over previous studies. The manufactured dry EEG electrode is very economical and cost-effective in terms of manufacturing costs when compared to recent studies. The proposed deep network, combined with the fabricated dry EEG electrode, can be used in real-time applications for long-term recordings that do not require gel. Full article

Bioimpedance imaging aims to generate a 3D map of the resistivity and permittivity of biological tissue from multiple impedance channels measured with electrodes applied to the skin. When the electrodes are distributed around the body (for example, by delineating a cross section of the chest or a limb), bioimpedance imaging is called electrical impedance tomography (EIT) and results in functional 2D images. Conventional EIT systems rely on individually cabling each electrode to master electronics in a star configuration. This approach works well for rack-mounted equipment; however, the bulkiness of the cabling is unsuitable for a wearable system. Previously presented cooperative sensors solve this cabling problem using active (dry) electrodes connected via a two-wire parallel bus. The bus can be implemented with two unshielded wires or even two conductive textile layers, thus replacing the cumbersome wiring of the conventional star arrangement. Prior research demonstrated cooperative sensors for measuring bioimpedances, successfully realizing a measurement reference signal, sensor synchronization, and data transfer though still relying on individual batteries to power the sensors. Subsequent research using cooperative sensors for biopotential measurements proposed a method to remove batteries from the sensors and have the central unit supply power over the two-wire bus. Building from our previous research, this paper presents the application of this method to the measurement of bioimpedances. Two different approaches are discussed, one using discrete, commercially available components, and the other with an application-specific integrated circuit (ASIC). The initial experimental results reveal that both approaches are feasible, but the ASIC approach offers advantages for medical safety, as well as lower power consumption and a smaller size. Full article

Compared with the traditional gel electrode, the dry electrode is being taken more seriously in bioelectrical recording because of its easy preparation, long-lasting ability, and reusability. However, the commonly used dry AgCl electrodes and silver cloth electrodes are generally hard to record through hair due to their flat contact surface. Claw electrodes can contact skin through hair on the head and body, but the internal claw structure is relatively hard and causes discomfort after being worn for a few hours. Here, we report a conductive Velcro electrode (CVE) with an elastic hook hair structure, which can collect biopotential through body hair. The elastic hooks greatly reduce discomfort after long-time wearing and can even be worn all day. The CVE electrode is fabricated by one-step immersion in conductive silver paste based on the cost-effective commercial Velcro, forming a uniform and durable conductive coating on a cluster of hook microstructures. The electrode shows excellent properties, including low impedance (15.88 kΩ @ 10 Hz), high signal-to-noise ratio (16.0 dB), strong water resistance, and mechanical resistance. After washing in laundry detergent, the impedance of CVE is still 16% lower than the commercial AgCl electrodes. To verify the mechanical strength and recovery capability, we conducted cyclic compression experiments. The results show that the displacement change of the electrode hook hair after 50 compression cycles was still less than 1%. This electrode provides a universal acquisition scheme, including effective acquisition of different parts of the body with or without hair. Finally, the gesture recognition from electromyography (EMG) by the CVE electrode was applied with accuracy above 90%. The CVE proposed in this study has great potential and promise in various human–machine interface (HMI) applications that employ surface biopotential signals on the body or head with hair. Full article

The paper investigates the feasibility of plasma electrolytic treatment (PET) of 90CrSi tool steel to enhance hardness and wear resistance. The influence of electrophysical parameters of PET (polarity of the active electrode, chemical-thermal treatment, and polishing modes) on the composition, structure, morphology, and tribological properties of the surface was studied. Tribological tests were carried out under dry friction conditions according to the shaft-bushing scheme with fixation of the friction coefficient and temperature in the friction contact zone, measurements of surface microgeometry parameters, morphological analysis of friction tracks, and weight wear. The formation of a surface hardened to 1110–1120 HV due to the formation of quenched martensite is shown. Features of nitrogen diffusion during anodic PET and cathodic PET were revealed, and diffusion coefficients were calculated. The wear resistance of the surface of 90CrSi steel increased by 5–9 times after anodic PET followed by polishing, by 16 times after cathodic PET, and up to 32 times after subsequent polishing. It is shown that in all cases, the violation of frictional bonds occurs through the plastic displacement of the material, and the wear mechanism is fatigue wear during dry friction and plastic contact. Full article

The electrodes of industrial electrostatic precipitators degrade as a result of two phenomena: corrosion and erosion. The first is chemical degradation by highly reactive compounds formed during combustion, in particular, during the incineration of municipal or industrial wastes or high-sulfur coal. The degradation intensity of electrostatic precipitator electrodes depends on the chemical composition of the exhaust gasses. High concentrations of chlorides, fluorides, or sulfur in the exhaust gasses cause strong corrosion of the electrostatic precipitator elements. The second mechanism is the erosion caused by solid particles conveyed by the exhaust gas stream due to their collision with the electrodes. In this study, the analysis of the degradation of electrodes of an electrostatic precipitator downstream of an industrial waste incinerator was carried out. The industrial wastes of unknown sources were subjected to thermal degradation in a rotary kiln. The aim of this study was to provide fundamental knowledge about the mechanisms of electrode degradation located on the surface of discharge electrodes of electrostatic precipitators during the combustion of industrial wastes. Full article

The scalable fabrication of cost-efficient bifunctional catalysts with enhanced hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) performance plays a significant role in overall water splitting in hydrogen production fields. MoSe₂ is considered to be one of the most promising candidates because of its low cost and high catalytic activity. Herein, hierarchical nitrogen-doped carbon networks were constructed to enhance the catalytic activity of the MoSe₂-based materials by scalable free-drying combined with an in situ selenization strategy. The rationally designed carbonaceous network-encapsulated MoSe₂ composite (MoSe₂/NC) endows a continuous honeycomb-like structure. When utilized as a bifunctional electrocatalyst for both HER and OER, the MoSe₂/NC electrode exhibits excellent electrochemical performance. Significantly, the MoSe₂/NC‖MoSe₂/NC cells require a mere 1.5 V to reach a current density of 10 mA cm⁻² for overall water splitting in 1 M KOH. Ex situ characterizations and electrochemical kinetic analysis reveal that the superior catalytic performance of the MoSe₂/NC composite is mainly attributed to fast electron and ion transportation and good structural stability, which is derived from the abundant active sites and excellent structural flexibility of the honeycomb-like carbon network. This work offers a promising pathway to the scalable fabrication of advanced non-noble bifunctional electrodes for highly efficient hydrogen evolution. Full article

Sodium-ion batteries are a technology rapidly approaching widespread adoption, so studying the thermal stability and safety of their components is a pressing issue. In this work, we employed differential scanning calorimetry (DSC) and ex situ powder X-ray diffraction to study the thermal stability of several types of sodium-ion electrolytes (NaClO₄ and NaPF₆ solutions in PC, EC, DEC, and their mixtures) and various cathode and anode materials (Na₃V₂(PO₄)₃, Na₃(VO)₂(PO₄)₂F, β-NaVP₂O₇, and hard carbon) in combination with electrolytes. The obtained results indicate, first, the satisfactory thermal stability of liquid Na-ion electrolytes, which start to decompose only at 270~300 °C. Second, we observed that charged vanadium-based polyanionic cathodes, which appear to be very stable in the “dry” state, demonstrate an increase in decomposition enthalpy and a shift of the DSC peaks to lower temperatures when in contact with 1 M NaPF₆ in the EC:DEC solution. However, the greatest thermal effect from the “electrode–electrolyte” interaction is demonstrated by the anode material: the heat of decomposition of the soaked electrode in the charged state is almost 40% higher than the sum of the decomposition enthalpies of the electrolyte and dry electrode separately. Full article

Carbon nanotubes, as carbon allotropes distinguished by their intricate structures and exceptional physicochemical properties, have demonstrated substantial progress in recent years across diverse domains, including energy production, chemical synthesis, and environmental preservation. They exhibit notable attributes such as high thermal stability, superior adsorption capacity, and a substantial specific surface area, rendering them superb catalyst supports. Particularly in electrochemical energy storage, CNTs are extensively employed in supercapacitor electrodes owing to their elevated electrical conductivity, mechanical robustness, and electrocatalytic prowess, which facilitate significant energy storage capabilities. Their intricate pore architecture and reactive sites make functionalized carbon nanotubes well suited for synthesizing composite materials with diverse components, which are ideal for sequestering carbon dioxide from both atmospheric and indoor environments. This review presents a comprehensive examination of carbon nanotube synthesis methodologies, encompassing chemical vapor deposition, arc discharge, and laser ablation, and evaluates their impacts on the structural and functional properties of carbon nanotubes. Furthermore, this article underscores the applications of carbon nanotubes in fields such as fuel cells, photocatalysis, ammonia synthesis, dry methane reforming, Fischer–Tropsch synthesis, and supercapacitors. Despite the considerable potential of carbon nanotubes, their manufacturing processes remain intricate and costly, impeding large-scale industrial production. This review concludes by addressing the challenges in fabricating carbon nanotube composites and outlining future development prospects. Full article

Polybenzoxazine (PBz) aerogels hold immense potential, but their conventional production methods raise environmental and safety concerns. This research addresses this gap by proposing an eco-friendly approach for synthesizing high-performance carbon derived from polybenzoxazine. The key innovation lies in using eugenol, ethylene diamine, and formaldehyde to create a polybenzoxazine precursor. This eliminates hazardous solvents by employing the safer dimethyl sulfoxide. An acidic catalyst plays a crucial role, not only in influencing the microstructure but also in strengthening the material’s backbone by promoting inter-chain connections. Notably, this method allows for ambient pressure drying, further enhancing its sustainability. The polybenzoxazine acts as a precursor to produce two different carbon materials. The carbon material produced from the calcination of PBz is denoted as PBZC, and the carbon material produced from the gelation and calcination of PBz is denoted as PBZGC. The structural characterization of these carbon materials was analyzed through different techniques, such as XRD, Raman, XPS, and BET analyses. BET analysis showed increased surface of 843 m² g⁻¹ for the carbon derived from the gelation method (PBZGC). The electrochemical studies of PBZC and PBZGC imply that a well-defined morphology, along with suitable porosity, paves the way for increased conductivity of the materials when used as electrodes for supercapacitors. This research paves the way for utilizing heteroatom-doped, polybenzoxazine aerogel-derived carbon as a sustainable and high-performing alternative to traditional carbon materials in energy storage devices. Full article

This research explores the integration of the Dry Sensor Interface-24 (DSI-24) EEG headset with a ChatGPT-enabled Furhat robot to monitor cognitive stress in video gaming environments. The DSI-24, a cutting-edge, wireless EEG device, is adept at rapidly capturing brainwave activity, making it particularly suitable for dynamic settings such as gaming. Our study leverages this technology to detect cognitive stress indicators in players by analyzing EEG data. The collected data are then interfaced with a ChatGPT-powered Furhat robot, which performs dual roles: guiding players through the data collection process and prompting breaks when elevated stress levels are detected. The core of our methodology is the real-time processing of EEG signals to determine players’ focus levels, using a mental focusing feature extracted from the EEG data. The work presented here discusses how technology, data analysis methods and their combined effects can improve player satisfaction and enhance gaming experiences. It also explores the obstacles and future possibilities of using EEG for monitoring video gaming environments. Full article

The generation of ozone by dielectric barrier discharge (DBD) is widely used for water and wastewater treatment, the control of catalytic reactions, and surface treatment. Recently, a need for compact, effective, and economical ozone and reactive oxygen–nitrogen species (RONS) generators for medical, biological, and agricultural applications has been observed. In this study, a novel hybrid DBD (HDBD) reactor fulfilling such requirements is presented. Its structured high-voltage (HV) electrode allows for the ignition of both the surface and volume microdischarges contributing to plasma generation. A Peltier module cooling of the dielectric barrier, made of alumina, allows for the efficient control of plasma chemistry. The typical electrical power consumption of this device is below 30 W. The operation frequency of the DBD driver oscillating in the auto-resonance mode is from 20 to 40 kHz. The specific energy input (SEI) of the reactor was controlled by the DBD driver input voltage in the range from 10.5 to 18.0 V, the Peltier current from 0 to 4.5 A, the duty cycle of the pulse-width modulated (PWM) power varied from 0 to 100%, and the gas flow from 0.5 to 10 SLM. The operation with oxygen, synthetic air, and compressed dry air (CDA) was characterized. The ultraviolet light (UV) absorption technique was implemented for the measurement of the ozone concentration. The higher harmonics of the discharge current observed in the frequency range of 5 to 50 MHz were used for monitoring the discharge net power. Full article