Search Results (280)

Molecularly imprinted polymers (MIPs) offer robust, cost-effective, and highly selective alternatives to fragile biological receptors. Specifically, electropolymerization has emerged as a versatile strategy that enables the precise, in situ formation of uniform MIP films directly on electrode surfaces. This review provides a comprehensive overview of electropolymerized MIPs (eMIPs) supported on advanced carbon-based materials for electrochemical (bio)sensing. We emphasize how the synergistic integration of eMIPs with carbonaceous architectures significantly enhances electron transfer, active surface area, and overall analytical sensitivity. Key fabrication aspects are systematically discussed, including monomer selection, electropolymerization parameters, and efficient template removal. A central aspect of this work is the critical categorization of sensing mechanisms into direct and indirect detection strategies. This distinction elucidates how eMIPs can quantify a broad spectrum of electroactive and non-electroactive targets in complex matrices, while strategically avoiding excessively high applied potentials. Finally, alongside outlining the transition of these systems into portable technologies, we address a critical shortcoming in the current literature: the urgent need for analytical standardization through the rigorous reporting of Imprinting and Selectivity Factors using Non-Imprinted Polymer (NIP) controls. Full article

High-entropy alloys (HEAs), composed of five or more principal elements in near-equimolar ratios, have emerged as a groundbreaking class of materials for next-generation flexible electronics. This review systematically examines the unique potential of HEAs as sensing materials, moving beyond their traditional role as structural components. We first elucidate the fundamental mechanisms—core effects including lattice distortion, sluggish diffusion, and the cocktail effect—that endow HEAs with an exceptional synergy of high strength, good ductility, tunable electrical resistivity, and superior electrocatalytic activity. Subsequently, we critically analyze the state-of-the-art strategies for processing HEA-based micro/nano structures, including mechanical alloying, wet-chemical synthesis, and non-equilibrium deposition techniques, with an emphasis on their compatibility with flexible substrates. The core of the review categorizes and discusses the latest advances in HEA-based flexible sensors for strain/stress, gas, and electrochemical (e.g., glucose, biomarkers, heavy metals) detection, highlighting the structure–property–performance relationships. Representative studies have demonstrated that HEA flexible strain sensors achieve a temperature coefficient of resistance as low as 45.59 ppm/K with no signal drift over 6000 stretching cycles; room-temperature hydrogen sensors reach a detection limit down to 31 ppb with a response time of 19 s; and non-enzymatic glucose sensors deliver a sensitivity up to 3043 μA·mM⁻¹·cm⁻². Finally, we summarize the key challenges—such as manufacturing scalability, long-term stability under dynamic deformation, and cost-effectiveness—and provide a forward-looking perspective on promising research directions, including high-throughput compositional screening, multi-functional sensor arrays, and the integration of machine learning for rational material design. Full article

Smart contact lens sensors integrate biochemical sensing elements, flexible electronics, power modules, and wireless readout components onto optically transparent contact lens platforms, enabling non-invasive and potentially continuous analysis of tear-derived biomarkers and ocular physiological signals. This review focuses on the translation pathway from contact lens materials and fabrication methods to sensing mechanisms, tear biomarker interpretation, and clinical deployment. We synthesize recent progress in substrate engineering, manufacturing processes, power delivery, and representative sensing strategies for intraocular pressure, glucose, electrolytes, pH, cortisol, cholesterol, and inflammatory cytokines. Instead of treating these systems as isolated examples, we compare optical/colorimetric, electrochemical, field-effect transistor, microfluidic, and wireless resonant approaches in terms of sensitivity, response time, power/readout requirements, and clinical relevance. Finally, we discuss persistent barriers, including biocompatibility, interface stability, tear-sample variability, calibration, sterilization, regulatory validation, data privacy, and compatibility with commercial contact lens manufacturing. Full article

Chronic diseases such as cardiovascular disorders, diabetes, neurological conditions, and kidney disease continue to rise worldwide. These conditions create a growing demand for continuous, non-invasive, and personalized health monitoring technologies. Wearable biosensors meet this need by enabling real-time physiological and biochemical measurements outside traditional clinical settings. Among wearable biosensors, those based on biofluids like sweat, tears, and saliva provide a painless alternative to blood sampling. These fluids also grant access to metabolites, electrolytes, hormones, proteins, and disease related biomarkers that reflect systemic health status. Advanced sensing technology allow us to continuously track health status by analyzing key biomarkers in these accessible biofluids. This review summarizes recent advances in non-invasive wearable biosensors and focuses on their sensing principles which includes biorecognition elements, signal transduction mechanisms, and data acquisition strategies. We also discussed key sensing modalities, including electrochemical, optical, thermal, and piezoelectric approaches, highlighting their advantages for wearable integration and performance in biofluid sensing. Finally the review also outlines recent developments and applications of these systems in biofluid sensing. In the end we highlights existing challenges, potential solutions, and future directions toward clinically deployable, AI-assisted precision healthcare systems. Full article

Poly(3,4-ethylenedioxythiophene) (PEDOT)-based gels have emerged as a prominent class of functional conductive materials, owing to their unique electromechanical coupling characteristics that integrate electrical functionality and mechanical adaptability. This review systematically elucidates the electromechanical properties of PEDOT-derived gels—defined as the synergistic response of electrical behaviors (conductivity, carrier mobility, electrochemical stability) and mechanical performances (flexibility, stretchability, tensile strength, bending resistance)—under mechanical deformation, as well as their mutual regulatory mechanisms. Focusing on how preparation processes and structural regulation modulate these electromechanical properties, this work first introduces the development history, intrinsic conductive mechanisms, and inherent electromechanical characteristics of PEDOT. It then systematically summarizes mainstream synthesis methods, analyzing their effects on balancing mechanical flexibility and electrical conductivity. Addressing the brittleness and poor electromechanical stability of pure PEDOT, this review further explores composite synergistic mechanisms with conductive/non-conductive polymers, metallic materials, inorganic nanoparticles, and biomaterials, clarifying how interfacial interactions optimize mechanical deformability while preserving or enhancing electrical performance. Finally, it summarizes the applications of PEDOT-based composites in electromechanically compatible fields including flexible sensing, micro/nano patterning, implantable biomedicine, anti-corrosion protection, and energy storage. This review aims to clarify the connotation of PEDOT’s electromechanical properties, refine the focus of relevant research, and provide a theoretical basis for designing high-performance PEDOT-based gels with balanced electromechanical properties. Full article

Accurate quantification of glucose is vital for quality control in the food industry. While earth-abundant Cu has emerged as a promising candidate for non-enzymatic electrochemical sensing, conventional electrode fabrication relying on powder coating with polymeric binders inevitably buries active catalytic sites and impedes both electron transfer and mass transport. In this study, a binder-free, self-supporting Cu nanoparticles/Ni foam (Cu NPs/NF) electrode was developed via a facile one-step hydrothermal method. Benefitting from the enhanced charge-transfer efficiency and a substantially enlarged electrochemical active surface area, the Cu NPs/NF-based electrochemical glucose sensor exhibited a wide linear detection range (0.25–3310.52 μM), a high sensitivity of 7000 μA mM⁻¹ cm⁻², a low detection limit of 0.32 μM, and a rapid response time of 3 s. Furthermore, the developed Cu NPs/NF electrode displayed favorable reproducibility, storage stability, and high selectivity against common interferents present in food matrices, demonstrating its reliability for practical applications. The feasibility of the proposed sensor was successfully validated in real beverage samples. Given the simplicity of the one-step hydrothermal synthesis and the portability afforded by the self-supporting electrode architecture, this Cu NPs/NF electrode emerges as a highly attractive candidate for commercial glucose sensors. Beyond glucose, the design strategy can be readily extended to the detection of other electroactive food-quality markers, enabling the broader applicability of this electrode platform in comprehensive food analysis. Full article

Sweat contains abundant ions, offering a rich source of physiological information for non-invasive health monitoring. Wearable sweat sensors have become a promising technology due to advances in electrochemical devices, sensing materials and structural design. The current monitoring platforms primarily employ two fundamental sensing modalities to convert sweat chemical information into detectable numerical signals: electrochemical (potentiometric, voltammetric, transistor-based) and optical (colorimetric) transduction mechanisms. The demand for more comprehensive physiological and biochemical data in clinical diagnosis and daily health monitoring is driving sensors towards multi-ion detection. Building on these modalities, researchers have optimized hardware and software algorithms based on the characteristics of different ions, thereby promoting the transition of wearable devices from the laboratory to practical applications. Here, we summarize recent progress in wearable sweat ion sensors, focusing on their mechanisms, advantages, and limitations. Finally, current challenges and future prospects of wearable sweat ion sensors for research applications, clinical use, and market demands are discussed. Full article

Magnetic sensors offer a physically grounded and non-invasive approach to probing biological processes that remain inaccessible to optical, electrochemical, and radio-frequency techniques in complex agricultural environments. In recent years, advances in both classical and quantum magnetic sensors have enabled the detection of bioelectromagnetic signals across plants, soils, animals, and aquatic systems, spanning spatial scales from ionic currents to organ-level electrophysiology and population-level dynamics, positioning magnetometry as an emerging modality within the broader biosensor landscape. This review surveys the evolution of magnetic sensing technologies for agricultural and animal systems, from robust classical sensors used in navigation and soil mapping to quantum-enabled platforms, including Optically Pumped Magnetometers (OPMs) and Nitrogen-Vacancy (NV) centers, capable of resolving pT to fT biomagnetic signals. We synthesize the characteristic amplitudes, frequency ranges, and physiological origins of agriculturally relevant magnetic signals, and critically assess how techniques originally developed for medical magnetoencephalography, magnetocardiography, and low-field magnetic resonance imaging (LF-MRI) are being translated into field-deployable agricultural applications. Beyond sensing hardware, we highlight the essential role of artificial intelligence in extracting weak biological signals from dominant environmental noise, enabling synthetic gradiometry, low-field image reconstruction, and scalable interpretation in unshielded settings. Finally, we discuss how the integration of magnetic biosensing with digital twins supports predictive, multiscale monitoring of plant, animal, and ecosystem health. Together, these developments position magnetometry as an enabling technology for next-generation biosensors in precision and sustainable agriculture. Full article

Existing deep learning methods for lithium-ion battery State of Health (SOH) prediction rely almost exclusively on discharge voltage–current curves, ignoring electrochemical impedance spectroscopy (EIS) data that directly reflects internal degradation mechanisms. Fusing these two modalities is non-trivial: discharge curves are high-dimensional temporal sequences residing on a continuous dynamical manifold, while impedance features are low-dimensional static snapshots with fundamentally different statistical distributions. However, naive concatenation introduces modal conflicts rather than complementary gains. We propose the Hybrid Sensing Synergy Architecture (HSSA), which combines a Mamba backbone ($O\left(L\right)$ complexity) for discharge curve modeling with a Q-former module that aligns impedance features into the temporal representation space via learnable query tokens and cross-attention. A prepend fusion strategy injects the aligned queries as prefix tokens, enabling the backbone to condition on internal electrochemical context from the first time step. On the NASA battery dataset, HSSA achieves MAE of 0.887 (large-scale, 11 batteries, a 9.8% improvement over unimodal Mamba), 1.457 (medium-scale, five batteries, a 28.0% improvement), and 2.705 (small-scale, four batteries, an 8.7% improvement), demonstrating consistent improvements across all data regimes. On out-of-sample battery B28, HSSA achieves 65.3% improvement. Ablation studies confirm that Q-former alignment is essential and prepend fusion significantly outperforms concatenation-based alternatives. Full article

In the present research, lanthanum ferrite nanoparticles (LaFeO₃ NPs) and lanthanum ferrite polypyrrole (LaFeO₃/PPy) nanocomposites were synthesized and evaluated for electrochemical sensing of TNZ in biological and pharmaceutical samples. LaFeO₃ NPs were synthesized using the sol–gel auto-combustion method, whereas LaFeO₃/PPy nanocomposites were produced through an in situ chemical oxidative polymerization process. The obtained materials were subjected to comprehensive characterization by multiple analytical techniques, including XRD, which confirms an orthorhombic crystal structure; SEM micrographs of LaFeO₃ NPs and LaFeO₃/PPy nanocomposites exhibit a highly agglomerated structure with non-uniform particle distribution and a more homogeneous, smoother surface morphology, respectively, with an average size of <70 nm. The LaFeO₃/PPy nanocomposites exhibited an electron-transfer process governed by diffusion, as evidenced by cyclic voltammetry (CV) analysis. Using differential pulse voltammetry (DPV), the sensor achieved quantitative detection across a linear concertation range of 0.1–230 µM (R² = 0.997), with a detection limit (0.023 µM). The developed sensor demonstrated excellent stability, remarkable sensitivity, and high reproducibility, confirming reliability and suitability (RSD% < 4.0) for the quantitative determination of TNZ in both biological and pharmaceutical matrices. Full article

Rising global demand for safe, high-quality foods has accelerated the development of rapid, sensitive, and cost-effective analytical technologies for detecting harmful substances and quality markers. Electrochemical sensors have emerged as promising tools for food safety monitoring due to their high sensitivity, fast response, portability, and affordability compared with conventional laboratory methods. This review highlights recent advances in nanostructured electrochemical sensors for detecting key food analytes, including antioxidants, mycotoxins, allergens, and flavor compounds in diverse food matrices. It examines advanced nanomaterials such as metal oxides, MXenes, doped carbon nitrides, and noble metal-decorated graphene, which enhance sensor performance through improved surface area, conductivity, and electrocatalytic activity. Integrated with screen-printed or glassy carbon electrodes, these materials achieve ultra-low detection limits, wide linear ranges, and strong selectivity in complex food systems. The review also explores next-generation applications such as NFC-enabled smart packaging for continuous, non-invasive monitoring across the supply chain. Emerging trends in miniaturization, multiplex sensing, and artificial intelligence are discussed, along with key challenges in translating laboratory innovations into practical commercial solutions for global food safety. Full article

Chronic kidney disease (CKD) is a progressive and irreversible disorder affecting over 850 million individuals globally and is associated with significant morbidity, mortality, and healthcare burden. Conventional diagnostic approaches rely on intermittent laboratory measurements, including serum creatinine, estimated glomerular filtration rate (eGFR), and urinary albumin, which provide limited temporal resolution and fail to capture dynamic physiological changes. Recent advances in wearable biosensing technologies offer new opportunities for continuous, non-invasive monitoring of biochemical and physiological markers relevant to renal function. This review provides a comprehensive analysis of wearable biosensors for CKD monitoring, focusing on sensing mechanisms (electrochemical, optical, and field-effect transistor), biofluid interfaces (sweat, interstitial fluid, and saliva), and materials engineering strategies enabling flexible, high-performance devices. Emphasis is placed on biofluid transport dynamics, analytical performance across sampling matrices, and system-level integration with wireless communication and digital health platforms. Key challenges limiting clinical translation, including biofouling, enzymatic instability, and variability in biofluid composition, are examined—alongside emerging solutions such as antifouling interfaces, synthetic recognition elements, and multimodal sensing architectures. Finally, regulatory pathways and the role of artificial intelligence in digital nephrology are discussed. This review highlights the potential of wearable biosensors to transform CKD management through continuous monitoring, early detection, and personalized therapeutic intervention. Full article

Sweat is a valuable biofluid for non-invasive health monitoring, as it contains electrolytes, metabolites, and organic compounds that can correlate with blood levels, making it highly attractive for wearable sensing. Building on advances in low-cost, portable electrochemical sensors, sweat analysis enables tracking of hydration status, metabolic stress, and energy availability via key markers such as sodium, potassium, lactate, and glucose. In the sports context, such wearable platforms can support performance optimization and recovery by assessing fluid loss and electrolyte balance in real time. Here, a multiplexed wearable sweat patch is developed to simultaneously monitor temperature, pH, ammonium, sodium, and sweat rate. The integrated platform demonstrates sensitivities of 10.1 mV/ln[NH₄⁺], 9.1 mV/ln[K⁺], 1.11 mV/ln[Na⁺], 14 mV/pH, 0.19% °C⁻¹, and approximately −1.0 mA (mL/min)⁻¹ for sweat rate, with stable signals and linear calibration responses over relevant physiological ranges. The sensor is implemented on a lightweight, biocompatible laser-scribed graphene on a PDMS substrate suitable for prolonged skin contact and mechanical deformation. In addition, a custom PDMS adhesive patch with optimized suction-cup microstructures is engineered to improve skin adhesion under both dry and wet conditions. Finally, the design of the platform was inspired by an adaptive cycling marathon across Saudi Arabia, where an earlier prototype of a wearable patch was deployed for real-time monitoring during a 30-day campaign. Full article

Durable concrete has emerged as a key material strategy for enhancing the performance and extending the service life of infrastructure in chloride-containing environments, owing to its resistance to chloride ingress and corrosion-induced deterioration. This paper presents a systematic review of recent advances in durable concrete, establishing a comprehensive technical framework encompassing material design, transport mechanisms, and lifecycle durability management. Research demonstrates that supplementary cementitious materials, corrosion inhibitors, and non-metallic reinforcements significantly mitigate chloride penetration and corrosion while improving durability performance in various structures, including marine, coastal, and transportation infrastructures. The effectiveness of these approaches is fundamentally attributed to pore structure refinement, electrochemical regulation, and the elimination of corrosion-prone components. However, transitioning durability technologies from “effective” to “reliable and designable” still faces critical challenges: the mechanisms of multi-factor coupling under complex environments remain unclear, transport models under non-steady conditions require further development, and inconsistencies persist among international durability design codes. Accordingly, this paper highlights that future research should focus on developing multi-scale coupled models, refining environmental classification and prediction methods, integrating intelligent sensing technologies, and establishing unified lifecycle-based design frameworks. These advancements are essential to promote durable concrete from material-level optimization toward system-level, intelligent durability design, thereby supporting the development of sustainable infrastructure. Full article

As a promising class of catalysts for enzymatic glucose sensors, Prussian blue analogues (PBAs) exhibit exceptional biomimetic activity. However, their performance is often constrained by poor intrinsic conductivity, which typically limits their sensitivity. To address this limitation, this study presents an effective approach using direct in situ growth of PBAs on the electrode substrates, which enables the effective integration of PBA-based electrochemical systems. A porous Ni framework was first electrodeposited onto a screen-printed gold electrode substrate, followed by the reduction of Pt onto the porous Ni. Subsequently, NiFe PBA was synthesized in situ using the porous Pt/Ni structure as a sacrificial template. Functionalized with glucose oxidase (GO_x), the PBA/Pt/Ni biosensor exhibited excellent performance for glucose detection in buffer solution, with a high sensitivity of 262.6 μA mM⁻¹·cm⁻² and an ultra-low detection limit of 1.45 μM (calculated at a signal-to-noise ratio of 3, S/N = 3). Notably, its sensitivity corresponds to a two-fold enhancement relative to the electrodes modified with commercial Prussian blue using the conventional drop-casting method. Even when tested in human sweat samples, the biosensor achieved a high sensitivity of 236.4 μA mM⁻¹·cm⁻² and a linear detection range of 20–1000 μM, with the broad sensing range fully encompassing the typical physiological concentrations of glucose in human sweat. This excellent performance arises from the high specific surface area of the porous Pt/Ni structure and the tight connection between PBA and the sacrificial Ni anode. This research presents a promising design strategy for advanced, wearable, and non-invasive health-monitoring platforms. Full article