Search Results (25)

Creatinine serves as a crucial diagnostic biomarker for assessing kidney disease. This work developed portable non-enzymatic and multienzyme-modified electrochemical biosensors for the detection of creatinine based on commercial screen-printed carbon electrodes (SPCEs). The non-enzymatic creatinine sensor was constructed by the electrochemical deposition of AuNPs onto the surface of a pre-activated SPCE by electrochemical activation, followed by the surface modification of a Nafion membrane. The developed AuNPs/SCPE exhibited excellent reproducibility, and the proposed Nafion/AuNPs/SPCE sensor showed excellent detection sensitivity and selectivity toward creatinine. In comparison, the enzymatic creatinine biosensor was gradually established by the electrodeposition of a Prussian blue (PB) membrane on the optimal AuNPs/SCPE surface, followed by multi-enzyme cascade modification (which consisted of creatinine amidohydrolase (CA), creatine oxidase (CI) and sarcosine oxidase (SOx)) and drop-casting the Nafion membrane to stabilize the interface. The introduction of a PB interlayer acted as the redox layer to monitor the generation of hydrogen peroxide (H₂O₂) produced by the enzymatic reaction, while the Nafion membrane enhanced the detection selectivity toward creatine, and the multi-enzyme cascade modification further increased the detection specificity. Both non-enzymatic and enzymatic creatinine sensors could detect the lowest concentrations of less than or equal to 10 μM. In addition, the efficiency and reproducibility of the proposed composite biosensor were also confirmed by repetitive electrochemical measurements in human serum, which showed a positive linear calibration relation of peak currents versus the logarithm of the concentration between 10 μM and 1000 μM, namely, i_p (μA) = −7.06 lgC (μM) −5.30, R² = 0.996. This work offers a simple and feasible approach to the development of enzymatic and non-enzymatic creatinine biosensors. Full article

This study integrates hyperspectral remote sensing with chemical and pedological data to estimate Zn, Pb, and Cd concentrations in the upper soil layers. Conducted in agricultural fields east and northeast of Celje, Slovenia, an area impacted by past industrial activities such as zinc ore smelting, the research integrates remote sensing and soil sampling to rapidly identify and map soil pollution over large surfaces. A multi-sensor approach was employed, combining two hyperspectral cameras (VNIR and SWIR, aerial), laboratory spectrometry, soil parameters, and content of chemical covariates measured with portable XRF and ICP-OES with a direct comparison of both techniques for this specific purpose. Accurate atmospheric and signal transformations were performed to improve modeling. The importance of covariates was thoroughly evaluated using conditional permutations to assess their contribution to the prediction of metal concentrations. The proposed framework utilizes spectral data and privileged information during training, improving prediction accuracy through a multi-stage model architecture. Here, a base model trained on spectral data is corrected using privileged information. During inference, the model functions without relying on privileged data providing a scalable and cost-effective solution for large-scale environmental monitoring. Our model achieved a reduction of predicted RMSE for Zn and Cd maps in comparison to the baseline models, translating to more precise identification of possibly polluted zones. However, for Pb, no improvements were observed, potentially due to variability in the data, including spectral issues or imbalances in the training and test datasets. Full article

Heavy and transition metal (HTM) ions have significant harmful effects on the physical environment and play crucial roles in biological systems; hence, it is crucial to accurately identify and quantify any trace pollution. Molecular sensors which are based on organic molecules employed as optical probes play a crucial role in sensing and detecting toxic metal ions in water, food, air, and biological environments. When appropriate combinations of conduction and selective recognition are combined, fluorescent and colorimetric chemosensors are appealing instruments that enable the selective, sensitive, affordable, portable, and real-time investigation of the possible presence of heavy and transition metal ions. This feature article aims to provide readers with a more thorough understanding of the different methods of synthesis and how they work. As noted in the literature, we will highlight colorimetric and fluorometric sensors based on their receptors into multiple categories for heavy metal ion detection, such as Hg²⁺, Ag²⁺, Cd^2+, Pb²⁺, and In³⁺, and simultaneous multiple-ion detection. Full article

This study investigated the morphological dependence of ZnO nanostructures, specifically nanotube- and nanorod-based electrodes, on their electrochemical performance for the detection of lead ions (Pb²⁺) in aqueous solutions. The results demonstrate that ZnO nanotubes exhibit significantly enhanced sensitivity compared to nanorods during CV measurements. During SWV measurements, the sensitivity (116.79 mA·mM⁻¹) and a lower limit of detection of 0.0437 μM were determined. The hollow, high-aspect-ratio structure of nanotubes provides a larger active surface area and facilitates better ion accessibility, resulting in superior electron transfer efficiency and catalytic activity. These results underscore the critical role of morphology in optimizing ZnO-based sensors. Analysis of real water samples from various natural reservoirs revealed no detectable lead, while lead was identified exclusively in artificially prepared samples containing water exposed to lead hunting shot. Over a 30-day period, the sensor retained over 95% of its initial performance when stored under vacuum conditions, demonstrating minimal signal degradation. Under ambient conditions, stability loss was attributed to moisture adsorption on the porous nanostructure. The sensor also displayed outstanding reproducibility, with current response variations across multiple probes remaining within 4%. The cost-effective and simple fabrication process of ZnO nanostructures further highlights their potential for scalable production, environmental monitoring, and integration into portable sensing devices. Full article

Both the mineralogy and geochemistry of coal mine waste presents environmental and social challenges while simultaneously offering the potential source for recovery of metals, including critical raw materials (CRMs). Assessing these challenges and opportunities requires effective waste management strategies and comprehensive material characterization. This study deals with the integration of analytical data obtained from various portable sensor technologies. Infrared reflection spectroscopy (covering a wide wavelength range of 0.4 to 15 µm), and geochemical x-ray fluorescence (XRF) were utilized to differentiate between samples belonging to various geological lithologies and quantify elements of interest. Therefore, we developed a methodological framework that encompasses data integration and machine learning techniques. The model developed using the infrared data predicts the Sr concentration with a model accuracy of R² = 0.77 for the testing dataset; however, the model performances decreased for predicting other elements such as Pb, Zn, Y, and Th. Despite these limitations, the approach demonstrates better performance in discriminating materials based on both mineralogical and geochemical compositions. Overall, the developed methodology, enables rapid and in-situ determination of coal mine waste composition, providing insights into waste composition that are directly linked to potential environmental impact, and the possible recovery of economically valuable metals. Full article

Screen-printed electrodes (SPEs) are reliable, portable, affordable, and versatile electrochemical platforms for the real-time analytical monitoring of emerging analytes in the environmental, clinical, and agricultural fields. The aim of this study was to evaluate the electrochemical behavior of gold screen-printed electrodes (SPGEs) modified with molecules containing amino (Tr-N) or α-aminophosphonate (Tr-P) groups for the selective and sensitive detection of the toxic metal ions Pb²⁺ and Hg²⁺ in aqueous samples. After optimizing the analytical parameters (conditioning potential and time, deposition potential and time, pH and concentration of the supporting electrolyte), anodic square wave stripping voltammetry (SWASV) was used to evaluate and compare the electrochemical performance of bare or modified electrodes for the detection of Hg²⁺ and Pb²⁺, either alone or in their mixtures in the concentration range between 1 nM and 10 nM. A significative improvement in the detection ability of Pb²⁺ ions was recorded for the amino-functionalized gold sensor SPGE-N, while the presence of a phosphonate moiety in SPGE-P led to greater sensitivity towards Hg²⁺ ions. The developed sensors allow the detection of Pb²⁺ and Hg²⁺ with a limit of detection (LOD) of 0.41 nM and 35 pM, respectively, below the legal limits for these heavy metal ions in drinking water or food, while the sensitivity was 5.84 µA nM⁻¹cm⁻² and 10 µA nM⁻¹cm⁻², respectively, for Pb²⁺ and Hg²⁺. The reported results are promising for the development of advanced devices for the in situ and cost-effective monitoring of heavy metals, even in trace amounts, in water resources. Full article

The assessment of fine motor competence plays a pivotal role in neuropsychological examinations for the identification of developmental deficits. Several tests have been proposed for the characterization of fine motor competence, with evaluation metrics primarily based on qualitative observation, limiting quantitative assessment to measures such as test durations. The Placing Bricks (PB) test evaluates fine motor competence across the lifespan, relying on the measurement of time to completion. The present study aims at instrumenting the PB test using wearable inertial sensors to complement PB standard assessment with reliable and objective process-oriented measures of performance. Fifty-four primary school children (27 6-year-olds and 27 7-year-olds) performed the PB according to standard protocol with their dominant and non-dominant hands, while wearing two tri-axial inertial sensors, one per wrist. An ad hoc algorithm based on the analysis of forearm angular velocity data was developed to automatically identify task events, and to quantify phases and their variability. The algorithm performance was tested against video recordings in data from five children. Cycle and Placing durations showed a strong agreement between IMU- and Video-derived measurements, with a mean difference <0.1 s, 95% confidence intervals <50% median phase duration, and very high positive correlation (ρ > 0.9). Analyzing the whole population, significant differences were found for age, as follows: six-year-olds exhibited longer cycle durations and higher variability, indicating a stage of development and potential differences in hand dominance; seven-year-olds demonstrated quicker and less variable performance, aligning with the expected maturation and the refined motor control associated with dominant hand training during the first year of school. The proposed sensor-based approach allowed the quantitative assessment of fine motor competence in children, providing a portable and rapid tool for monitoring developmental progress. Full article

The development of effective methods for dopamine detection is critical. In this study, a homogeneous colorimetric strategy for the detection of dopamine based on a copper sulfide and Prussian blue/platinum (CuS@PB/Pt) composite was developed. A rose-like CuS@PB/Pt composite was synthesized for the first time, and it was discovered that when hydrogen peroxide was present, the 3,3′,5,5′-tetramethylbenzidine (TMB) changed from colorless into blue-oxidized TMB. The CuS@PB/Pt composite was characterized with a scanning electron microscope (SEM), an energy dispersive spectrometer (EDS), and an X-ray photoelectron spectrometer (XPS). Moreover, the catalytic activity of the CuS@PB/Pt composite was inhibited by the binding of dopamine to the composite. The color change of TMB can be evaluated by the UV spectrum and a portable smartphone detection device. The developed colorimetric sensor can be used to quantitatively analyze dopamine between 1 and 60 µM with a detection limit of 0.28 μM. Furthermore, the sensor showed good long-term stability and good performance in human serum samples. Compared with other reported methods, this strategy can be performed rapidly (16 min) and has the advantage of smartphone visual detection. The portable smartphone detection device is portable and user-friendly, providing convenient colorimetric analysis for serum. This colorimetric strategy also has considerable potential for the development of in vitro diagnosis methods in combination with other test strips. Full article

In this work, we report a low-cost and highly sensitive electrochemical sensor for detecting As(III) in water. The sensor uses a 3D microporous graphene electrode with nanoflowers, which enriches the reactive surface area and thus enhances its sensitivity. The detection range achieved was 1–50 ppb, meeting the US-EPA cutoff criteria of 10 ppb. The sensor works by trapping As(III) ions using the interlayer dipole between Ni and graphene, reducing As(III), and transferring electrons to the nanoflowers. The nanoflowers then exchange charges with the graphene layer, producing a measurable current. Interference by other ions, such as Pb(II) and Cd(II), was found to be negligible. The proposed method has potential for use as a portable field sensor for monitoring water quality to control hazardous As(III) in human life. Full article

To exploit high-performance and stable sensing materials with a room working temperature is pivotal for portable and mobile sensor devices. However, the common sensors based on metal oxide semiconductors usually need a higher working temperature (usually above 300 °C) to achieve a good response toward gas detection. Currently, metal halide perovskites have begun to rise as a promising candidate for gas monitoring at room temperature but suffer phase instability. Herein, we construct 1D/3D PyPbI₃/FA_0.83Cs_0.17PbI₃ (denoted by PyPbI₃/FACs) bilayer perovskite by post-processing spin-coating Pyrrolidinium hydroiodide (PyI) salt on top of 3D FACs film. Benefitting from the 1D PyPbI₃ coating layer, the phase stability of 1D/3D PyPbI₃/FACs significantly improves. Simultaneously, the gas sensor based on the 1D/3D PyPbI₃/FACs bilayer perovskite presents a superior selectivity and sensitivity toward NO₂ detection at room temperature, with a low detection limit of 220 ppb. Exposed to a 50 ± 3% relative humidity (RH) level environment for a consecutive six days, the 1D/3D PyPbI₃/FACs perovskite-based sensor toward 10 ppm NO₂ can still maintain a rapid response with a slight attenuation. Gas sensors based on hybrid 1D/3D-structured perovskite in this work may provide a new pathway for highly sensitive and stable gas sensors in room working temperature, accelerating its practical application and portable device. Full article

Creatinine is the final metabolic product of creatine in muscles and a widely accepted biomarker for chronic kidney disease. In this work, we present a non-enzymatic sensor based on an electrochemical pretreated screen-printed carbon electrode (PTSPCE) with electrodeposited Cu nanoparticles (CuNPs). To function in a PoC format, the prepared PTSPCE/CuNPs non-enzymatic sensors were used as disposable elements in a portable potentiostat. The pretreatment using mild anodic and cathodic potentials in PBS resulted in an increased electroactive surface area and improved conductivity, confirmed by cyclic voltammetry and electrochemical impedance. Moreover, the detection through the CuNPs–creatinine interaction showed an enhanced performance in the PTSPCE surface compared to the bare electrode. The optimized PTSPCE/CuNPs sensor showed a linear working range from 10 to 160 μM (R² = 0.995), a sensitivity of 0.2582 μA·μM⁻¹ and an LOD of 0.1 μM. The sensor analytical parameters covered the requirements of creatinine detection in biofluids such as blood and saliva, with a low interference of common biomarkers such as urea, glucose, and uric acid. When evaluated in Fusayama/Meyer artificial saliva, the PTSPCE/CuNPs showed an average recovery rate of 116%. According to the observed results, the non-enzymatic PTSPCE/CuNPs sensor can potentially operate as a creatinine early screening system in PoC format. Full article

The use of economic methods to design and fabricate flexible copper sensors decorated with bismuth micro/nanodentrites for the detection of lead and cadmium in sweat is demonstrated. The flexible copper sensors were constructed with simple and cost-effective materials; namely, flexible and adhesive conductive copper tape, adhesive label containing the design of a three-electrode electrochemical system, and nail polish or spray as a protective layer. The flexible copper device consisted of a working electrode decorated with bismuth micro/nanodentrites using an electrodeposition technique, a copper pseudo-reference and copper counter electrodes. Under optimal experimental conditions, the flexible sensing platform showed excellent performance toward the detection of lead and cadmium using differential pulse anodic stripping voltammetry (DPAdSV) in a wide linear range from 2.0 μM to 50 μM with acceptable reproducibility and repeatability, and limits of detection and quantification of 5.36 and 17.9 μM for Cd²⁺ ions and 0.76 μM and 2.5 for Pb²⁺ ions. Studies of addition and recovery in spiked artificial sweat sample were performed, with a recovery of 104.6%. The flexible copper device provides a great opportunity for application in wearable perspiration-based healthcare systems or portable sensors to detect toxic metals in biological samples. Full article

While potentiometric, plasticized membrane sensors are known as convenient, portable and inexpensive analytical instruments, their development is time- and resource-consuming, with a poorly predictable outcome. In this study, we investigated the applicability of the QSPR (quantitative structure–property relationship) method for predicting the potentiometric sensitivity of plasticized polymeric membrane sensors, using the ionophore chemical structure as model input. The QSPR model was based on the literature data on sensitivity, from previously studied, structurally similar ionophores, and it has shown reasonably good metrics in relating ionophore structures to their sensitivities towards Cu²⁺, Cd²⁺ and Pb²⁺. The model predictions for four newly synthesized diphenylphosphoryl acetamide ionophores were compared with real potentiometric experimental data for these ionophores, and satisfactory agreement was observed, implying the validity of the proposed approach. Full article

Efficient battery technology is imperative for the adoption of clean energy automotive solutions. In addition, efficient battery technology extends the useful life of the battery as well as provides improved performance to fossil fuel technology. Model predictive control (MPC) is an effective way to operate battery management systems (BMS) at their maximum capability, while maintaining the safety requirements. Using the physics-based model (PBM) of the battery allows the control system to operate on the chemical and physical process of the battery. Since these processes are internal to the battery and are physically unobservable, the extended Kalman filter (EKF) serves as a virtual observer that can monitor the physical and chemical properties that are otherwise unobservable. These three methods (i.e., PBM, EKF, and MPC) together can prolong the useful life of the battery, especially for Li-ion batteries. This capability is not limited to the automotive industry: any real-world smart application can benefit from a portable/mobile efficient BMS, compelling these systems to be executed on resource-constrained embedded devices. Furthermore, the intrinsic adaptive control process of the PBM is uniquely suited for smart systems and smart technology. However, the sheer computational complexity of PBM for MPC and EKF prevents it from being realized on highly constrained embedded devices. In this research work, we introduce a novel, unique, and efficient embedded software architecture for a PB-EKF-MPC smart sensor for BMS, specifically on embedded devices, by addressing the computational complexity of PBM. Our proposed embedded software architecture is created in such a way to be executed on a 32-bit embedded microprocessor running at 100 MHz with a limited memory of 128 KB, and still obtains an average execution time of 4.8 ms. Full article

Here, the voltammetric electrochemical approach was applied to detect uric acid (UA) in a conductive sensing medium (phosphate buffer solution-PBS) by using PbO-doped NiO nanocomposites (NCs)-decorated glassy carbon electrode (GCE) performing as working electrode. The wet-chemically prepared PbO-doped NiO NCs were subjected to characterization by the implementation of XRD, FESEM, XPS, and EDS analysis. The modified GCE was used to detect uric acid (UA) in an enzyme-free conductive buffer (PBS) of pH = 7.0. As the outcomes of this study reveal, it exhibited good sensitivity of 0.2315 µAµM⁻¹cm⁻² and 0.2233 µAµM⁻¹cm⁻², corresponding to cyclic (CV) and differential pulse (DPV) voltammetric analysis of UA, respectively. Furthermore, the proposed UA sensor showed a wider detection (0.15~1.35 mM) range in both electrochemical analysis methods (CV & DPV). In addition, the investigated UA sensor displayed appreciable limit of detection (LOD) of 41.0 ± 2.05 µM by CV and 43.0 ± 2.14 µM by DPV. Good reproducibility performance, faster response time and long-time stability in detection of UA were perceived in both electrochemical analysis methods. Finally, successful analysis of the bio-samples was performed using the recovery method, and the results were found to be quite acceptable in terms of accuracy. Thus, the findings indicate a reliable approach for the development of 5th generation biosensors using metal-oxides as sensing substrate to fulfill the requirements of portable use for in situ detection. Full article