Search Results (3,949)

Plants must constantly adapt to biotic and abiotic stressors, which the global climate change crisis has intensified. To monitor plant health and predict their ability to face these challenges, various target molecules, such as hormones, glucose, and reactive oxygen species, are used as proxies for their physiological status. This review provides a systematic assessment of the current state of biosensor technology, an innovative analytical approach designed for in situ, minimally invasive, and real-time monitoring. Using the PICO (Problem, Intervention, Comparison, and Outcome) strategy, relevant research papers were identified. The review highlights how biosensors can detect physiological responses to stress before visual symptoms manifest, offering a significant advantage over traditional, often destructive, laboratory techniques, like gas chromatography–mass spectrometer (GC-MS) or high-performance liquid chromatography (HPLC). These advancements aim to improve precision agriculture and forestry management by providing sustainable methods to assess resilience in changing environments. Finally, the challenges of translating research from model organisms to complex woody species and choosing the correct target are discussed, and future perspectives, including the integration of biosensors with Artificial Intelligence-driven predictive models for large-scale environmental monitoring, are outlined. Full article

The present Special Issue, entitled “Electrochemical (Bio)Sensors as Promising Analytical Tools in the Analysis of Soils, Plants and Environmental Monitoring”, aims to provide an up-to-date overview of recent advances in electroanalytical techniques and electrochemical (bio)sensors, with particular emphasis on their applications in environmental systems, agriculture, and biological matrices [...] Full article

Printed biosensors have attracted increasing attention as platforms for rapid, low-cost, and portable diagnostics because they can be fabricated on flexible or rigid substrates using scalable printing techniques. Their performance is strongly influenced by both the printing process and the materials employed, since factors such as ink rheology, particle dispersion, interfacial behavior, and post-processing conditions directly affect device architecture, sensing performance, and manufacturing reliability. This review summarizes recent advances in printed biosensors from the combined perspectives of printing technologies and functional materials. Commonly employed printing techniques, including inkjet, screen, aerosol jet, and roll-to-roll gravure printing, are discussed with emphasis on their processing characteristics and material requirements. The review also examines key material platforms used in printed biosensors, including carbon-based nanomaterials, metal oxides, metal nanoparticles, conductive polymers, dielectric materials, and hybrid composites, highlighting their roles in electrical conductivity, catalytic activity, biomolecule immobilization, mechanical flexibility, and overall analytical performance. Finally, current challenges and emerging research directions are outlined with respect to ink stability, post-processing strategies, sensor reliability, manufacturability, and practical translation. Overall, this review emphasizes that the development of high-performance printed biosensors depends on the synergistic integration of rational material design with optimized printing strategies. Full article

Operando mechanical behavior of lithium-ion batteries under aggressive conditions remains insufficiently quantified, especially under combined high-rate and deep-discharge operation. This study investigated strain evolution in a commercial 18650 NMC lithium-ion cell using surface-mounted fiber Bragg grating sensors across 20 sequential conditions combining five discharge rates (1–4.5 C) and four cutoff voltages (2.5–1.0 V). All tests were performed on a single cell using identical 0.5 C constant-current constant-voltage charging, followed by a 2 h rest period and controlled discharge, to systematically evaluate mechanochemical evolution with increasing electrochemical severity. Maximum tensile strain during charging ranged from 45 to 59 µε and showed limited sensitivity to discharge severity. In contrast, discharge behavior exhibited clear rate- and cutoff-dependent transitions from tensile to compressive deformation; the most severe condition (4.5 C, 1.0 V cutoff) produced a peak compressive strain of about −27 µε and the most negative residual strain after relaxation. Although temperature increased monotonically with C-rate, strain evolution was nonlinear and non-monotonic, indicating that electrochemically induced stress dominated over thermal expansion alone. These findings reveal progressive amplification of irreversible deformation under severe discharge and demonstrate the value of fiber Bragg grating sensing for operando assessment of electrochemical–mechanical coupling in cylindrical lithium-ion cells. Full article

Cobalt–copper bimetallic oxides (CoCuO_x) show great potential for constructing high-performance micro-supercapacitors (MSCs) for micro-electronic applications. However, their poor conductivity and complex preparation procedures significantly hinder their broad applications. To address these challenges, oxygen-vacancy-modified CoCuO_x-based binder-free electrodes were fabricated using a one-step computer numerical control wire electrical discharge machining (CNCWEDM) strategy. This approach enabled the fabrication of CoCuO_x-based maze-like MSCs (CoCuMMSCs) with designable electrochemical performance, which could be simply controlled by their geometric shape and machining voltage. Subsequently, theoretical simulations were conducted for studying the effect of MSCs geometric shape on their capacitive behavior. Remarkably, the CoCuMMSCs fabricated by a machining voltage of 100 V achieved the maximum capacitance of 32.8 mF cm⁻² at 0.15 mA cm⁻². Furthermore, the CoCuMMSCs demonstrated outstanding performance at ultrahigh scan rates of up to 50,000 mV s⁻¹, exceeding by more than two orders of magnitude the values previously reported in the literature. The obtained results proved that the development of the CNCWEDM technique facilitated manufacturing CoCuMMSCs devices with excellent performance by the comprehensive utilization of oxygen-vacancy incorporation, synergistic effect of cobalt and copper oxides, binder-free electrode design, proper device construction and controllable machining voltage. The advanced CNCWEDM strategy creates a new pathway for the high-efficiency fabrication of high-performance bimetallic-oxide-based micro-electronic devices, such as MSCs, intelligent micro-sensors and micro-batteries. Full article

The increasing use of antibiotics around the globe has contributed to an increase in antimicrobial resistance and become a major risk to both public health and sustainable development. Reliable and fast detection of antibiotic residues in clinical, agricultural, and environmental matrices is required to monitor antimicrobial resistance effectively. The conventional analytical techniques are sensitive, but they are also expensive, complex and lacking in portability. Voltammetry is a recently emerging electrochemical detection technique that is low-cost and rapid. To the best of our knowledge, for the first time, a meta-analysis was conducted on graphene-based electrochemical sensors and biosensors for antibiotic detection over the last decade. This systematic review critically examines the analytical properties of sensors and biosensors, the physicochemical properties of antibiotics, adsorption characteristics, and the use of nanoparticles to improve the selectivity and sensitivity of devices. This review critically examines the cost-effectiveness, scalability, and practicality of point-of-use devices using graphene-based sensors and biosensors. This systematic review also discusses the potential risks to human health from antibiotic contamination and the role of monitoring in contributing to achieving the UN’s Sustainable Development Goals. This systematic review identifies a gap between developing sensors in laboratories versus their deployment as field-deployable devices; it highlights challenges associated with stability, matrix effects and the complexity of manufacturing devices. Finally, it provides recommendations for future research that may help to address this gap to promote the transition of innovative devices from academic to practical applications. Full article

Accurate color classification plays a critical role across diverse fields, from textile manufacturing and environmental monitoring to biomedical diagnostics. This study introduces a machine-learning-driven approach to spectral color sensing using SENSIPATCH, a compact, wearable sensor system; while SENSIPATCH integrates multiple sensing modalities, including bioimpedance, electrochemical, thermal, humidity, and vibrational sensors, this work specifically utilizes its spectrometer module, which comprises multi-wavelength LEDs and photodiodes. Targeting the classification of 100 standardized PANTONE colors, the proposed framework is evaluated under controlled lighting conditions to ensure repeatable spectral acquisition. The experimental design includes both firm and loose contact scenarios to emulate variability in wearable placement. A structured data-preprocessing pipeline involving baseline correction, bootstrapping, and Z-score normalization was employed to enhance signal quality and improve model generalization. Five machine learning models were evaluated: Random Forest, SVM, MLP, CNN, and LSTM. The MLP demonstrated the strongest classification performance. Notably, the MLP achieved consistent accuracy across both contact conditions, indicating robustness against sensor placement variations. These results highlight the feasibility of compact LED-based wearable spectroscopy for reliable color classification under controlled measurement conditions, providing a baseline for future extensions to more diverse lighting conditions. Full article

Application of porous coordination polymers (PCPs), which include metal–organic frameworks (MOFs) and covalent organic frameworks (COFs) in sensors for detection of toxicant pollutants in water is discussed. Particular attention is given to electrochemical and photoluminescent sensors because PCPs/MOFs demonstrate good selectivity towards adsorption of molecules in combination with outstanding luminescent properties and electroconductivity in composite materials. The use of PCPs/MOFs as pre-concentrators of the compounds to be analyzed is also outlined. The review covers the results described in the literature over the past 5 years in such diverse fields as the determination of metal ions and anions, drugs, mycotoxins, pesticides, explosives, bacteria, etc. Thus, the review demonstrates the proliferation of MOF applications and the universal nature of sensors based on them. Full article

A nanostructured sensing platform based on electrospun functionalized multi-walled carbon nanotubes/poly(3-aminobenzylamine) (FMWCNTs/P3ABA) was developed for the electrochemical detection of dopamine (DA) on fluorine-doped tin oxide (FTO) glass substrate. The electrochemical characteristics of the electrodes were investigated by chronocoulometry (CC) and cyclic voltammetry (CV) in phosphate-buffered saline solution containing K₃[Fe(CN)₆] as a redox mediator. The zeta potential analysis confirmed the presence of a stable surface charge that favors electrostatic interaction with DA molecules. The DA detection was performed in human urine by differential pulse voltammetry (DPV) over a potential of −0.2 to 0.8 V and at scan rate of 5 mV s⁻¹, where the FMWCNTs/P3ABA nanofiber electrode exhibited a high sensitivity of 1.502 µA cm⁻² nM⁻¹, a linear detection range of 10–500 nM (R² = 0.992), and a limit of detection of 1.753 nM. The sensor exhibited stable and reproducible responses, and the fibrous composite effectively discriminated DA from common electroactive interferents, including ascorbic acid, uric acid, creatinine, and glucose. Furthermore, reliable dopamine quantification in human urine samples demonstrates the strong potential of the electrospun FMWCNTs/P3ABA composite nanofiber platform for practical bioanalytical and non-invasive sensing applications in the future. Full article

Dopamine is a key neurotransmitter and neuromodulator that regulates many critical brain functions. Accurate monitoring of its level is essential for neuroscience as well as the diagnosis and treatment of many brain diseases. In this work, we developed a new electrochemical sensor, comprising phosphorus-doped graphitic carbon nitride (P-g-C₃N₄) and zeolitic imidazolate framework 67 (ZIF-67), for dopamine detection. In this composite electrode material, ZIF-67 provides numerous adsorption and sensing sites, while P-g-C₃N₄ enhances overall electrical conductivity and stability. Cyclic voltammetry tests reveal the redox behavior of dopamine at the surface of the composite electrode across various pH values and scan rates. Using differential pulse voltammetry, the sensitivity and selectivity of this dopamine sensor were assessed, identifying a limit of detection of 0.39 nM. Further successful quantification of dopamine in urine samples suggests the potential practical use of this new composite electrochemical sensor for detecting dopamine and/or other neurotransmitters. Full article

Pesticide residues in food and agricultural products continue to constitute a significant concern for food safety, particularly when rapid decision-making is required across production and supply chains. Although chromatographic methods such as GC-MS and LC-MS/MS remain essential for confirmatory analysis, their dependence on central laboratories limits their applicability for field screening. Consequently, portable biosensor-based detection platforms have attracted increasing attention as rapid screening tools. This review synthesizes 26 peer-reviewed studies published between 2010 and 2025 on portable biosensor-based screening tools for pesticide detection in food and agricultural matrices, including electrochemical sensors, immunoassays, aptamer-based systems, paper-based lateral flow devices, and smartphone-assisted platforms. Given the heterogeneity of analytes, sensing mechanisms, and study designs, a narrative synthesis approach was applied. Overall, the evidence suggests a shift from laboratory-centered detection toward field-deployable technologies that may support preliminary screening within food safety monitoring frameworks. Paper-based lateral flow assays are widely reported as deployable formats, while electrochemical and affinity-based platforms are often positioned as intermediate solutions for mobile or semi-controlled testing environments. However, most platforms remain at the proof-of-concept or early validation stage, and challenges related to matrix interference, long-term stability, reproducibility, standardization, and large-scale implementation persist. This review highlights the potential role of portable biosensor technologies as complementary tools within tiered food safety monitoring systems and outlines key priorities for further development before wider regulatory integration can be considered. Full article

Two-dimensional Ti₃C₂O₂ MXene has emerged as a promising electrode material for non-enzymatic glucose sensing due to its metallic conductivity and biocompatibility. However, the atomic-scale sensing mechanism remains unclear. This DFT study uses the PBE functional with the D3(BJ) dispersion correction to elucidate glucose–MXene interactions under idealized vacuum conditions. Pristine Ti₃C₂O₂ shows metallic behavior with a density of states of about 8.2 states per electron volt at the Fermi level, dominated by Ti 3d states. β-d-glucose adsorbs onto the surface through hydrogen bonding, with an adsorption energy of −0.82 eV at a separation distance of 2.8 angstroms. Bader analysis indicates a transfer of about 0.15 electrons from MXene to glucose, resulting in a Fermi level shift of about −0.15 eV and an 18% reduction in the density of states at the Fermi level. These changes correspond to an estimated sensitivity of approximately 0.6 μA mM⁻¹ cm⁻² and a detection limit of about 17 µM, consistent with reported experimental performance of MXene-based sensors. Comparative adsorption calculations for common sweat interferents yield −0.45 eV for lactate and −0.25 eV for urea, indicating weaker interfacial affinity than glucose; these values reflect thermodynamic binding strength and possible surface occupation rather than definitive electrochemical selectivity, which additionally depends on redox potential, electron-transfer kinetics, and operating bias. We acknowledge three main limitations: first, the model considers only pure oxygen termination rather than mixed oxygen, hydroxyl, and fluorine terminations; second, the calculations are performed under vacuum rather than in aqueous conditions; third, the study is based on static zero kelvin structures rather than finite temperature dynamics. Despite these idealizations, the results provide baseline mechanistic insights to support rational design of MXene-based glucose sensors. Full article

Agriculture, as a basis of sustainable development, faces increasing pressure to meet rising global food demands while confronting the increasing impacts of climate change. Precision agriculture offers a data-driven approach to address these challenges by optimizing input use, improving productivity, and reducing environmental impacts. Sensor technologies play a critical role in smart and precision agriculture, offering high-resolution spatial and temporal insights into soil conditions, plant development and environmental conditions. This review highlights the current state and future potential of various sensor and imaging systems, particularly their role in monitoring soil properties, crop nutrition, plant health and detecting biotic and abiotic stressors. Special attention is given to accessible paper-based and printed electrochemical devices for on-site soil and plant analysis, as well as active handheld multispectral sensors designed for real-time canopy assessment. The integration of sensor-derived data with predictive models, IoT networks and decision-support tools enables more precise, site-specific management, improves input efficiency and supports climate-resilient agricultural practices. By examining the capabilities, limitations and future potential of these sensing platforms, this review highlights their growing importance in advancing sustainable intensification and strengthening crop production. Full article

The development of high-performance electrochemical sensors requires precise integration of electrode active materials that provide both superior electrocatalytic activity and long-term structural stability. Herein, we report a systematically optimized, one-pot electrochemical deposition approach for the fabrication of nanographenide-based nanoarchitectures, incorporating either a conducting polymer (PEDOT-NG) or Prussian blue (PB-NG). Derived from optimization-driven structural refinement—including applied potential, electrodeposition time, and precursor concentration—the robust nanoarchitecture exhibits a hierarchical morphology that provides an expanded electroactive surface area, accelerating charge transfer and enhancing electrochemical catalytic activity. The optimized PEDOT-NG exhibits exceptional sensitivity for the simultaneous determination of ascorbic acid (AA), dopamine (DA), and uric acid (UA), achieving wide linear ranges with low detection limits of 4.1, 0.12, and 0.18 μM, respectively. The PB-NG achieves a limit of detection of 4.39 μM, driven by highly reversible and stable redox kinetics. This performance is underpinned by narrowed peak-to-peak separations (ΔE) and reduced redox potentials. These results underscore the pivotal role of precise parametric control in developing high-performance electrochemical sensors. Furthermore, this work establishes a comprehensive strategy for designing resilient electrode active materials, thereby paving the way for next-generation electrochemical platforms tailored for diverse and robust sensing environments. Full article

We report the fabrication and electrochemical characterization of TiO₂-based impedimetric sensors for the analysis of artificial sweat compositions. Two-electrode topologies were patterned on indium tin oxide (ITO) substrates: an interdigitated electrode (IDE) configuration and a Hilbert fractal electrode (HFE) geometry. TiO₂ thin films with thickness up to 350 nm were deposited by dip-coating and evaluated as photoactive sensing layers. The impedimetric response of the sensors was investigated by electrochemical impedance spectroscopy in artificial sweat with composition varied in terms of ionic content (0–100 mM Na⁺) and organic content (2.5–30 mM lactic acid and 5–50 mM urea). Regardless of TiO₂ thickness, the high-frequency response is predominantly governed by electrode topology, with the HFE design exhibiting up to 2.5-fold higher modulation compared to the IDE configuration. Under UV illumination, a low-frequency, photo-assisted response emerges, influenced by the TiO₂ layer thickness and primarily sensitive to the organic components of the solution, particularly lactic acid. These results suggest that frequency-resolved impedance measurements in TiO₂|ITO structures may enable partial differentiation between ionic conductivity and organic contributions in sweat, providing a promising basis for multi-parameter sweat analysis. Full article