Search Results (2,714)

The development of micro glucose sensors plays a vital role in the management and monitoring of diabetes, facilitating real-time tracking of blood glucose levels. In this paper, we developed a three-layer core-sheath microwire (NW@CuO@Co₃O₄) with nickel wire as the core and copper oxide and cobalt oxide nanowires as the sheath. The unique core-sheath structure of microwire enables it to have both good conductivity and excellent electrochemical catalytic activity when used as an electrode for glucose detecting. The non-enzymatic glucose sensor base on a NW@CuO@Co₃O₄ core-sheath wire exhibits a high sensitivity of 4053.1 μA mM⁻¹ cm⁻², a low detection limit 0.89 μM, and a short response time of less than 2 s. Full article

Point-of-care (POC) antigen detection plays a crucial role in curbing the spread of viruses. Paper-based fluorescence aptasensors are expected to offer a low-cost tool to meet the needs of decentralized POC diagnosis. Herein, we report on a fluorescent paper-based sensing system for detecting the SARS-CoV-2 spike protein. The sensing system was constructed by loading multi-layer Nb₂C MXene nano-quenchers and carbon-dot-labeled aptamer (G-CDs@Apt) probes onto a mixed cellulose ester (MCE) paper substrate. On the Nb₂C MXene/G-CDs@Apt sensing paper, abundant G-CDs@Apt probes were attached to the multilayer MXene nano-quenchers and kept in a fluorescence-off state, while recognition of the target detached the G-CDs@Apt probes formed the nano--quenchers, resulting in fluorescence recovery of the sensing paper. The developed paper-based sensor performed well in the one-step detection of the SARS-CoV-2 S1 protein with a detection limit of 0.067 ng/mL (0.335 pg/test). The assay exhibited good selectivity and anti-interference in the detection of the SARS-CoV-2 S1 protein in artificial saliva. Moreover, the paper-based aptasensor was successfully used to detect the SARS-CoV-2 S1 protein in actual environmental samples with recoveries of 90.87–100.55% and relative standard deviations of 1.52–3.41%. The proposed technology provides a cost-effective alternative to traditional antibody test strips for a wide range of POC diagnostic applications. Full article

This study investigates the structural and catalytic properties of pure and Sr-doped LaCoO₃ and LaFeO₃ thin films for potential use as resistive gas sensors. Thin films were deposited via pulsed laser deposition (PLD) and characterized using X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM), atomic force microscopy (AFM), nanoindentation, and scratch tests. XRD analysis confirmed the formation of the desired perovskite phases without secondary phases. XPS revealed the presence of La³⁺, Co³⁺/Co⁴⁺, Fe³⁺/Fe⁴⁺, and Sr²⁺ oxidation states. SEM and AFM imaging showed compact, nanostructured surfaces with varying morphologies (shape and size of surface irregularities) depending on the composition. Sr doping led to surface refinement and increased nanohardness and adhesion. Transmission electron microscopy (TEM) analysis confirmed the columnar growth of nanocrystalline films. Sr-doped LaCoO₃ demonstrated enhanced sensitivity and stability in the presence of NO₂ gas compared to pure LaCoO₃, as evidenced by electrical resistivity measurements within 230 ÷ 440 °C. At the same time, it was found that Sr doping stabilizes the catalytic activity of LaFeO₃ (in the range of 300 ÷ 350 °C), although its behavior in the presence of NO₂ differs from that of LaCo(Sr)O₃—especially in terms of response and recovery times. These findings highlight the potential of Sr-doped LaCoO₃ and LaFeO₃ thin films for NO₂ sensing applications. Full article

This study calibrates an affordable, solar-powered LoRaWAN air quality monitoring prototype using the research-grade Palas Fidas Frog sensor. Motivated by the need for sustainable air quality monitoring in smart city initiatives, this work integrates low-cost, self-sustaining sensors with research-grade instruments, creating a cost-effective hybrid network that enhances both spatial coverage and measurement accuracy. To improve calibration precision, the study leverages the Super Learner machine learning technique, which optimally combines multiple models to achieve robust PM (Particulate Matter) monitoring in low-resource settings. Data was collected by co-locating the Palas sensor and LoRaWAN devices under various climatic conditions to ensure reliability. The LoRaWAN monitor measures PM concentrations alongside meteorological parameters such as temperature, pressure, and humidity. The collected data were calibrated against precise PM concentrations and particle count densities from the Palas sensor. Various regression models were evaluated, with the stacking-based Super Learner model outperforming traditional approaches, achieving an average test R² value of 0.96 across all target variables, including 0.99 for PM_2.5 and 0.91 for PM_10.0. This study presents a novel approach by integrating Super Learner-based calibration with LoRaWAN technology, offering a scalable solution for low-cost, high-accuracy air quality monitoring. The findings demonstrate the feasibility of deploying these sensors in urban areas such as the Dallas-Fort Worth metroplex, providing a valuable tool for researchers and policymakers to address air pollution challenges effectively. Full article

Nanoarchitectonics influences the properties of objects at micro- and even macro-scales, aiming to develop better structures for protection of product. Although its applications were analyzed in different areas, nanoarchitectonics of food packaging—the focus of this review—has not been discussed, to the best of our knowledge. The (A) structural and (B) functional hierarchy of food packaging is discussed here for the enhancement of protection, extending shelf-life, and preserving the nutritional quality of diverse products including meat, fish, dairy, fruits, vegetables, gelled items, and beverages. Interestingly, the structure and design of packaging for these diverse products often possess similar principles and methods including active packaging, gas permeation control, sensor incorporation, UV/pulsed light processing, and thermal/plasma treatment. Here, nanoarchitechtonics serves as the unifying component, enabling protection against oxidation, light, microbial contamination, temperature, and mechanical actions. Finally, materials are an essential consideration in food packaging, particularly beyond commonly used polyethylene (PE), polypropylene (PP), polyethylene terephthalate (PET), polystyrene (PS), and polyvinyl chloride (PVC) plastics, with emphasis on biodegradable (polybutylene succinate (PBS), polyvinyl alcohol (PVA), polycaprolactone (PCL), and polybutylene adipate co-terephthalate (PBAT)) as well as green even edible (bio)-materials: polysaccharides (starch, cellulose, pectin, gum, zein, alginate, agar, galactan, ulvan, galactomannan, laccase, chitin, chitosan, hyaluronic acid, etc.). Nanoarchitechnotics design of these materials eventually determines the level of food protection as well as the sustainability of the processes. Marketing, safety, sustainability, and ethics are also discussed in the context of industrial viability and consumer satisfaction. Full article

The COVID-19 pandemic highlighted the global necessity to develop fast, affordable, and user-friendly diagnostic alternatives. Alongside recognized tests such as ELISA, nanotechnologies have since been explored for direct and indirect diagnosis of SARS-CoV-2, the etiological agent of COVID-19. Accordingly, in this work, we report a method to detect anti-SARS-CoV-2 antibodies based on graphene-based field-effect transistors (GFETs), using a nanostructured platform of graphene with added gold nanorods (GNRs) and a specific viral protein. To detect anti-N-protein IgG antibodies for COVID-19 in human sera, gold nanorods were functionalized with the nucleocapsid (N) protein of SARS-CoV-2, and subsequently deposited onto graphene devices. Our test results demonstrate that the sensor is highly sensitive and can detect antibody concentrations as low as 100 pg/mL. Using the sensor to test human sera that were previously diagnosed with ELISA showed a 90% accuracy rate compared to the ELISA results, with the test completed in under 15 min. Integrating graphene and nanorods eliminates the need for a blocker, simplifying sensor fabrication. This hybrid sensor holds robust potential to serve as a simple and efficient point-of-care platform. Full article

The secondary equipment of a substation is pivotal for maintaining the safe and reliable operation of the power grid. However, over time, insulation defects can inevitably arise in this equipment. Gas detection in substation secondary equipment has proven to be an effective method for assessing its insulation status. In this paper, we employed a density functional theory (DFT) approach to simulate the adsorption process of three types of fault gases from substation secondary equipment onto Cr-modified BN nanosheets. From the doped and adsorption models, two stable structures were chosen, and by calculating their band structures, density of states, and differential charge density, we uncovered the relevant adsorption and sensing mechanisms. Our findings reveal that Cr-modified BN nanosheets possess robust gas-sensing capabilities, particularly in capturing O₃, which is primarily attributable to the contribution of Cr’s 4d orbital electron layer. Specifically, the adsorption capacity of Cr-modified BN nanosheets for fault gases in substation secondary equipment follows the order: O₃ > NO₂ > CO. The adsorption of Cr-BN on the three target gases mainly tends to be chemisorption accompanied by chemical bond breaking. Notably, there are significant changes in the electronic properties of the adsorbent substrate before and after the adsorption of the target gas molecules, resulting in alterations in its overall conductivity. This research lays the theoretical groundwork for the experimental development of high-performance gas-sensitive sensors designed to detect fault gases in substation secondary equipment. Full article

This parameter study examines the impact of two distinct adhesion layers, chromium (Cr) and titanium (Ti), on the performance of CuO/Cu₂O-based chemoresistive gas sensors by varying the layer thickness. The sensing material utilised on a Si-SiO₂ sensor chip with Pt electrodes is an ultrathin CuO/Cu₂O film fabricated through thermal deposition of Cu and subsequent oxidation. The sensors were evaluated by measuring the change in electrical resistance against a range of target gases, including carbon monoxide (CO), carbon dioxide (CO₂) and a mixture of hydrocarbons (HC_Mix), in order to assess any potential cross-sensitivity issues. As the reactions occur at the surface, the surface was characterised by scanning electron microscopy (SEM) and the composition by grazing incidence X-Ray diffraction (GIXRD) measurement to gain further insight into the influence of the adhesion layer on the sensing performance. Full article

Background: Aging is characterized by shared cellular and molecular processes, and aging-related diseases might co-exist in a cluster of comorbidities, particularly in vulnerable individuals whose phenotype meets the criteria for frailty. Whilst the multidimensional definition of frailty is still controversial, there is an increasing understanding of the common pathways linking metabolic syndrome, cognitive decline, and sarcopenia, frequent conditions in frail elderly patients. Methods: We performed a systematic search in the electronic databases Cochrane Library and PubMed and included preclinical studies, cohort and observational studies, and trials. Discussion: Metabolic syndrome markers, such as insulin resistance and the triglyceride/HDL C ratio, correlate with early cognitive impairment. Insulin resistance is a cause of synaptic dysfunction and neurodegeneration. Conversely, fasting and fasting-mimicking agents promote neuronal resilience by enhancing mitochondrial efficiency, autophagy, and neurogenesis. Proteins acting as cellular metabolic sensors, such as SIRT1, play a pivotal role in aging, neuroprotection, and metabolic health. In AD, β-amyloid accumulation and hyperphosphorylated tau in neurofibrillary tangles can cause metabolic reprogramming in brain cells, shifting from oxidative phosphorylation to aerobic glycolysis, similar to the Warburg effect in cancer. The interrelation of metabolic syndrome, sarcopenia, and cognitive decline suggests that targeting these shared metabolic pathways could mitigate all the conditions. Pharmacological interventions, including GLP-1 receptor agonists, metformin, and SIRT 1 inducers, demonstrated neuroprotective effects in animals and some preliminary clinical models. Conclusions: These findings encourage further research on the prevention and treatment of neurodegenerative diseases as well as the drug-repurposing potential of molecules currently approved for diabetes, dyslipidemia, and metabolic syndrome. Full article

A dual-range mid-infrared carbon dioxide (CO₂) sensor is developed with temperature and humidity compensation functionalities. Using the same optical path, the sensor employs dual-channel signal processing circuits to achieve measurements across two detection ranges of 200–3000 parts-per-million (ppm) (low concentration range) and 8–25% (high concentration range), respectively. The developed sensor, with a compact size of 8.5 × 5.5 × 3.5 cm³, shows a good linear response, with fitting goodness R² = 0.99942 for the low range and R² = 0.9993 for the high range. Under environmental conditions of 20 °C temperature and 30% relative humidity and with an averaging time of 1 s, the limits of detection are 0.15 ppm for the low range and 32.4 ppm for the high range, respectively. A temperature and humidity compensation scheme based on multiple linear regression is proposed to mitigate the impact of environmental temperature and humidity changes. The experimental results demonstrate that the relative error after compensation is reduced from 21% to 0.87%. Indoor and outdoor CO₂ measurements are performed to validate the good characteristics of the sensor system. Full article

The emission of toxic gases such as NO₂, NO, SO₂, and CO from industrial activities, transportation, and energy production poses significant threats to the environment and public health. Traditional gas sensors often lack high sensitivity and selectivity. To address this, our study uses first-principles density functional theory (DFT) to investigate CuO-SnS monolayers for improved gas sensor performance. The results show that CuO modification significantly enhances the adsorption capacity and selectivity of SnS monolayers for NO₂ and NO, with adsorption energies of −2.301 eV and −2.142 eV, respectively. Furthermore, CuO modification is insensitive to CO₂ adsorption, demonstrating excellent selectivity. Structural and electronic analyses reveal that CuO modification reduces the band gap of SnS monolayers from 1.465 eV to 0.635 eV, improving the electrical conductivity and electron transfer, thereby enhancing the gas adsorption sensitivity. Further analyses highlight significant electronic interactions and charge transfer mechanisms between CuO-SnS monolayers and NO₂ and SO₂ molecules, indicating strong orbital hybridization. In conclusion, this study provides a theoretical basis for developing high-performance gas sensors, showing that CuO-SnS monolayers have great potential for detecting toxic gases. Full article

Background/Objectives: Home spirometry allows people with cystic fibrosis (CF) to monitor their lung function from home. However, there are concerns about its feasibility and validity compared to traditional clinic spirometry. The aim of this study was to evaluate the feasibility and validity of telehealth spirometry for patients with CF living in a regional setting. Methods: This retrospective study included forty-eight people with cystic fibrosis (pwCF) aged 6–33 years. Participants performed home spirometry using a portable flow sensor spirometer over a one-year period, without supervision. Spirometry readings from portable spirometers were compared with the nearest in-clinic spirometry using the intra-correlation coefficient (ICC) and Bland–Altman plots. Data were collected over a period of one year, with regular intervals of measurements. Results: In 427 of the 877 (48.6%) attempted sessions, successful spirometry at home was recorded. Although we showed good reliability between at-home and in-clinic measurements using the Bland–Altman plots and intraclass correlation co-efficient (ICC) (values ranged from 0.76 to 0.88), analysis of the 117 pairs of at-home and in-clinic spirometries showed that mean differences of forced expiratory volume in the 1st sec (FEV1) and forced vital capacity (FVC) obtained at home (both in liter and z-score) had, on average, lower values than the corresponding values at the clinic. Conclusions: Home-based telehealth spirometry is feasible among pwCF and provides advantages, especially for those from remote or secluded areas. However, lower values in FVC and FEV1 obtained through home spirometry should not be used interchangeably with clinic values. Full article

Zinc cobaltite (ZnCo₂O₄) is a ternary metal oxide found in spinel with promising properties for various applications. Optimizing its catalytic activity requires an understanding of its electrochemical behavior. The electrochemical properties of ZnCo₂O₄ have significantly improved due to recent developments in nanostructuring, doping, surface modification, hybridization, structural engineering, and electrochemical activation. These improvements have inspired and motivated researchers by presenting the latest developments in the field. The spinel structure, coupled with the redox properties of cobalt ions, semiconducting characteristics, and electrocatalytic potential, positions ZnCo₂O₄ as a versatile material for several electrochemical energy storage and conversion systems. This review explores these advancements; the notable properties of ZnCo₂O₄; and its applications in sensors, batteries, photovoltaics, and supercapacitors. Full article

Flexible pressure sensors play an extremely important role in the fields of intelligent medical treatment, humanoid robots, and so on. However, the low sensitivity and the small initial capacitance still limit its application and development. At present, the method of constructing the microstructure of the dielectric layer is commonly used to improve the sensitivity of the sensor, but there are some problems, such as the complex process and inaccurate control of the microstructure. In this work, an ion composite photosensitive resin based on polyurethane acrylate and ionic liquids (ILs) was prepared. The high compatibility of the photosensitive resin and ILs was achieved by adding a chitooligosaccharide (COS) chain extender. The microstructure of the dielectric layer was optimized by digital light processing (DLP) 3D-printing. Due to the introduction of ILs to construct an electric double layer (EDL), the flexible pressure sensor exhibits a high sensitivity of 32.62 kPa⁻¹, which is 12.2 times higher than that without ILs. It also has a wide range of 100 kPa and a fast response time of 51 ms. It has a good pressure response under different pressures and can realize the demonstration application of human health. Full article

The accurate measurement of human balance is required in numerous analysis and training applications. Force plates are frequently used but are too costly to be suitable for home-based systems such as balance training. A growing body of research and commercial products use Pressure-Sensitive Mats (PSMs) for balance measurement. Low-cost PSMs are constructed with a piezoresistive material and use copper tracks as conductors. However, these lack accuracy, as they often have a low resolution and suffer from noise, non-repeatable effects, and crosstalk. This paper proposes novel algorithms that enable the Centre of Pressure (CoP) to be computed using low-cost PSM designs with significantly higher accuracy than is currently achievable. A mathematical model of a general low-cost PSM was developed and used to select the design of the PSM (track width and placement) that maximises CoP accuracy. These yield new optimal PSM geometries that decrease the mean absolute CoP error from 17.37% to 5.47% for an 8 × 8 sensor layout. Then, knowledge of the footprint was used to further optimise accuracy, showing a decrease in absolute error from 17.37% to 3.93% for an 8 × 8 sensor layout. A third algorithm was derived using models of human movement to further reduce measurement error. Full article