Search Results (192)

The quantity, size, and distribution of non-metallic inclusions in High-Strength Low-Alloy (HSLA) steel critically influence its service performance. Conventional detection methods often fail to adequately characterize extreme inclusion distributions in large-section components. This study developed an integrated full-process inclusion analysis system combining high-precision motion control, parallel optical imaging, and laser spectral analysis technologies to achieve rapid and automated identification and compositional analysis of inclusions in meter-scale samples. Through systematic investigation across the industrial process chain—from a dia. 740 mm consumable electrode to a dia. 810 mm electroslag remelting (ESR) ingot and finally to a dia. 400 mm forged billet—key process-specific insights were obtained. The results revealed the effective removal of Type D (globular oxides) inclusions during ESR, with their counts reducing from over 8000 in the electrode to approximately 4000–7000 in the ingot. Concurrently, the mechanism underlying the pronounced enrichment of Type C (silicates) in the ingot tail was elucidated, showing a nearly fourfold increase to 1767 compared to the ingot head, attributed to terminal solidification segregation and flotation dynamics. Subsequent forging further demonstrated exceptional refinement and dispersion of all inclusion types. The billet tail achieved exceptionally high purity, with counts of all inclusion types dropping to extremely low levels (e.g., Types A, B, and C were nearly eliminated), representing a reduction of approximately one order of magnitude. Based on these findings, enhanced process strategies were proposed, including shallow molten pool control, slag system optimization, and multi-dimensional quality monitoring. An intelligent analysis framework integrating a YOLOv11 detection model with spectral feedback was also established. This work provides crucial process knowledge and technological support for achieving the quality control objective of “known and controllable defects” in HSLA steel. Full article

This paper reviews tab-to-busbar interconnections in lithium-ion battery packs, focusing on resistance welding (RW), laser beam welding (LBW), and ultrasonic welding (USW). The functional roles of tabs and busbars and typical material choices (Al-, Cu-, and Ni-plated Cu) are outlined. Subsequently, the processes are compared in terms of heat input, interfacial metallurgy, electrical resistance, mechanical robustness, and manufacturability. USW, as a solid-state method, suppresses porosity and limits Al-Cu intermetallic growth, but is sensitive to thickness, stack geometry, and tool wear. LBW enables high-speed, automated production with precise energy delivery, yet requires careful control to mitigate spatter, porosity, and brittle IMCs in dissimilar joints. RW remains cost-effective and flexible but can suffer from electrode wear and variability with highly conductive stacks. This review also summarizes the effect of the busbar material (Al versus Cu) and thickness on the connection resistance and temperature increase under a high current. No single process is universally superior, and the selection should match the stack-up, reliability targets, and production constraints. This paper aims to provide an overview of recent and conventional research trends for each welding method and to introduce selected non-traditional approaches, thereby presenting a range of viable options for future applications. Full article

ITIC’s superior electron-accepting capacity and efficient oxygen reduction motivated the design of a sensor to enhance sensitivity, selectivity, and stability over conventional oxygen-dependent or fullerene-based systems. As oxygen acts as the terminal reagent in enzymatic glucose oxidation, we developed an ITIC-mediated glucose oxidase (GOx) biosensor on glassy carbon (GCE) and screen-printed carbon electrodes (SPCE). ITIC, a non-fullerene organic semiconductor, was drop-cast onto the electrode to catalyze oxygen reduction, followed by GOx immobilization in a chitosan matrix. Scanning electron microscopy (SEM) confirmed uniform, ultrathin coatings without significant morphological changes upon ITIC and GOx deposition. Electrochemical studies (cyclic (CV) and differential pulse voltammetry (DPV)) revealed a distinct ITIC reduction peak at –0.7 V (vs. Ag/AgCl) and a glucose-dependent current decrease, consistent with mediated electron transfer during enzymatic oxidation. Under optimized conditions, the GCE-based biosensor showed a sensitivity of 10.7 μA L mmol⁻¹, a linear dynamic range (LDR) of 0.10–1.00 mmol L⁻¹, and detection (LOD)/quantification (LOQ) limits of 0.02 and 0.06 mmol L⁻¹, respectively. The SPCE device displayed sensitivity (3.8 μA L mmol⁻¹) and maintained excellent linearity (R² > 0.99) with LOD and LOQ of 0.05 and 0.16 mmol L⁻¹. Both platforms showed good precision (RSD < 5%) and reliable recovery in deproteinized plasma and artificial tears (90–104%). The superior performance of the GCE is attributed to higher ITIC loading, faster electron transfer, and reduced background current, while the SPCE offers a low-cost, disposable format with sufficient analytical performance for point-of-care glucose monitoring. Full article

Thick (900–1500 µm), crack-free lithium manganese oxide (LMO) electrodes with a polyvinylidene fluoride (PVDF)-based polymer electrolyte were prepared using an innovated slurry casting method. The selectivity and intercalation capacity of the thick electrodes of 900–1500 μm were evaluated in aqueous chloride solutions containing main cations in synthetic Salar de Atacama brine using cyclic voltammetry (CV) measurements. The CV data indicated that a high Li⁺ selectivity of Li/Na = 152.7 could be achieved under potentiostatic conditions. With the thickest electrode, while the mass specific intercalation capacity was 6.234 mg per gram of LMO, the area specific capacity was increased by 3–11 folds compared to that for conventional thin electrodes to 0.282 mg per square centimeter. In addition, 82% of capacity was retained over 30 intercalation/dis-intercalation cycles. XRD and electrochemical analyses revealed that both Faradaic diffusion-controlled or battery-like intercalation and Faradaic non-diffusion controlled or pseudocapacitive intercalation contributed to the capacity and selectivity. This work demonstrates a practical technology for thick electrode fabrication that promises to result in a significant reduction in manufacturing and operational costs for lithium extraction from brines. Full article

Alzheimer’s Disease (AD) is one of the most commonly seen neurodegenerative disorders, where early detection of its biomarkers is crucial for effective management. Conventional diagnostic methods are often expensive, time-consuming, and highly complex, which highlights an urgent need for point-of-care biosensing technology. In this work, we developed assays on three-dimensional (3D) graphene foam electrodes by functionalising them with a 1-Pyrenebutyric acid N-hydroxysuccinimide ester (Pyr-NHS) to enable effective antibody immobilisation for the detection of amyloid beta peptides (Aβ42 and Aβ40), key biomarkers for AD. Pyr-NHS linkers were used for stable functionalisation, followed by binding with Aβ42 and Aβ40 antibodies, and then bovine serum albumin (BSA) was employed as a blocking agent to minimise non-specific bindings on the electrode surface. Differential Pulse Voltammetry (DPV) measurements showed satisfactory stability over 12 days (RDS upper limit was <10%) and highly sensitive and specific detection of Aβ42 and Aβ40, with insignificant interference of tau217 protein. The biosensor exhibited a low limit of detection (LOD) with 252 aM for Aβ42 and 395 aM for Aβ40, covering 0.125 fM–1 nM and 0.125 fM–100 pM linear ranges, respectively. Further validation was conducted on spiked-diluted human plasma. This excellent analytical performance was attributed to the stable Pyr-NHS functionalisation, the 3D graphene foam enabling superior conductivity and a larger surface area on the working electrode, and the optimisation of antibody concentration for immobilisation. These promising results suggest that 3D graphene foam-based biosensors have considerable potential for early detection of AD biomarkers and developing cost-effective, portable, and reliable point-of-care devices. Full article

Driver monitoring systems are increasingly relying on physiological signals to assess cognitive and emotional states for improved safety and user experience. Electrodermal activity (EDA) is a particularly informative biomarker of arousal but is conventionally measured with skin-contact electrodes, limiting its applicability in vehicles. This work explores the feasibility of non-contact EDA estimation using Light Detection and Ranging (LiDAR) as a novel sensing modality. In a controlled laboratory setup, LiDAR reflection intensity from the forehead was recorded simultaneously with conventional finger-based EDA. Both classification and regression tasks were performed as follows: feature-based machine learning models (e.g., Random Forest and Extra Trees) and sequence-based deep learning models (e.g., CNN, LSTM, and TCN) were evaluated. Results demonstrate that LiDAR signals capture arousal-related changes, with the best regression model (Temporal Convolutional Network) achieving a mean absolute error of 14.6 on the normalized arousal factor scale (–50 to +50) and a correlation of r = 0.85 with ground-truth EDA. While random split validations yielded high accuracy, performance under leave-one-subject-out evaluation highlighted challenges in cross-subject generalization. The algorithms themselves were not the primary research focus but served to establish feasibility of the approach. These findings provide the first proof-of-concept that LiDAR can remotely estimate EDA-based arousal without direct skin contact, addressing a central limitation of current driver monitoring systems. Future research should focus on larger datasets, multimodal integration, and real-world driving validation to advance LiDAR towards practical in-vehicle deployment. Full article

Electrical discharge machining is a non-conventional shaping technique applied to electrically conductive, difficult-to-machine alloys, such as Hastelloy C-22. This study investigates the influence of graphite electrode properties and key machining parameters on the average thickness of the recast layer under positive polarity. Two POCO graphite electrodes with different grain sizes—AF-5 (1 μm) and S-180 (10 μm)—were used to examine the effects of discharge current, pulse duration, and interval on recast layer formation. Metallographic analyses measured layer thickness and observed microstructural defects, including microcracks. Results show that discharge current and pulse duration are the primary factors controlling recast layer thickness, with higher currents and longer pulses producing thicker layers due to resolidification of molten material remaining in the plasma-formed crater. The coarser S-180 electrode caused slightly higher microcrack density and greater thickness variations due to its lower electrical resistivity. Pulse interval mainly influenced discharge stability and debris removal, with minimal effect on average layer thickness. Statistical regression models were developed to quantify the relationships between machining parameters, electrode type, and recast layer thickness, providing predictive tools for selecting optimal conditions. These findings contribute to improving surface integrity and process control in electrical discharge machining of nickel-based alloys. Full article

The discharge of ammonia-rich wastewater poses significant threats to water quality and ecosystem health, driving the need for efficient and sustainable treatment technologies. The electrochemical ammonia oxidation reaction (eAOR) has emerged as a promising alternative to conventional biological and physicochemical methods, offering advantages such as in situ oxidant generation, tunable product selectivity, and applicability under challenging water matrices. This comprehensive review systematically examines the mechanisms, catalyst design, and environmental factors influencing eAOR performance. Two primary pathways are detailed: direct eAOR, involving stepwise dehydrogenation of NH₃ on the electrode surface, and indirect eAOR, mediated by electrogenerated reactive chlorine species (RCS). The mechanisms—including the Oswin-Salomon and Gerischer-Mauerer pathways for direct oxidation, as well as breakpoint chlorination and radical-mediated routes for indirect oxidation—are critically discussed alongside experimental and theoretical evidence. Recent advances in electrocatalyst development are highlighted, covering noble metals, non-noble transition metal oxides, alloys, and hybrid materials, with an emphasis on enhancing activity, selectivity toward N₂, and durability. Key operational parameters such as pH, chloride concentration, and coexisting ions are analyzed for their impact on reaction kinetics and byproduct formation. Finally, the review identifies current challenges—including catalyst poisoning, toxic byproduct generation, and scalability—and outlines future research directions aimed at advancing eAOR toward energy-efficient, resource-recovering water treatment systems. Full article

In this work, we investigated the use of a piezoelectric flexible device for energy harvesting. The main goal of the study was to fill the nanostructured pores of anodic aluminum oxide (AAO) films with piezoelectric polymer (PVDF-TrFE) via a modified conventional screen printing technique using blade printing. In this way, it is possible to obtain a composite from nanostructured thin films of polymer nanorods that shows improved charge generation ability compared to other non-nanostructured composites or pure (non-composite) aluminum with similar dimensions. This behavior is due to the effect of the highly developed surface of the material used to fill in the AAO nanopore template and its ability to withstand the application of higher mechanical loads to the structured piezoelectric material during deformation. The contact blade print filling technique can produce nanostructured piezoelectric polymer films with precise geometric parameters in terms of thickness and nanorod diameters, at around 200 nm, and a length of 12 μm. At a low frequency of 17 Hz, the highest root-mean-square (RMS) voltage generated using the nanostructured AAO/PVDF-TrFE sample with aluminum electrodes was around 395 mV. At high frequencies above 1700 Hz, the highest RMS voltage generated using the nanostructured AAO/PVDF-TrFE sample with gold electrodes was around 680 mV. The RMS voltage generated using a uniform (non-nanostructured) layer of PVDF-TrFE was 15% lower across the whole frequency range. Full article

In the pursuit of advanced non-volatile memory technologies, ferroelectric memristors have attracted great attention. However, traditional perovskite ferroelectric materials are hampered by environmental pollution, limited applicability, and the complexity and high cost of conventional vacuum deposition methods. This has spurred the exploration of alternative materials and fabrication strategies. Herein, a flexible Pt/Zr: HfO₂ (HZO)/graphene oxide (GO)/mica memristor is successfully fabricated using the total solution-processed method. The interfacial oxygen competition mechanism between the HZO layer and the GO bottom electrode facilitates the formation of the HZO ferroelectric phase. The as-prepared device exhibits a switching ratio of approximately 150 and can maintain eight distinct resistance levels, and it can also effectively simulate neural responses. By integrating the ferroelectric polarization principle and the piezoelectric effect of HZO, along with the influence of GO, the performance variations of the as-prepared device under mechanical and thermal influences are further explored. Notably, Morse code recognition is achieved by utilizing the device’s pressure properties and setting specific press rules. The as-prepared device can accurately convert and store information, opening new avenues for non-volatile memory applications in silent communication and promoting the development of wearable electronics. Full article

Background: Patent ductus arteriosus (PDA) in dogs causes persistent left-to-right shunting, leading to pulmonary overcirculation, left heart volume overload, and potential congestive heart failure. Accurate assessment of fluid imbalance is essential but challenging with conventional echocardiography or biomarkers. Phase angle (PhA), derived from bioelectrical impedance analysis (BIA), may serve as a non-invasive marker of extracellular fluid distribution and cellular integrity. Objectives: This study aimed to evaluate PhA as an indicator of thoracic fluid imbalance in dogs with PDAby analyzing its correlation with pulmonary velocity (PV) and end-diastolic volume (eV), as well as its responsiveness to surgical correction. In addition, we assessed the relationships between PhA and echocardiographic structural indices (LA/Ao, TDI Sep E/Em, TDI Lat E/Em) and examined the influence of the measurement region. Methods: PhA was measured at 5, 50, and 250 kHz in 30 PDA-affected and 15 healthy dogs, with electrode placement across thorax, trunk, and abdomen. Echocardiography evaluated PV, eV, and PDA-specific structural parameters. Results: Thoracic PhA at 5 kHz was significantly reduced in PDAdogs, strongly correlated with PV and moderately with eV. Postoperative measurements showed progressive PhA recovery. Only TDI Lat E/Em correlated with mid-frequency PhA, while other structural indices showed minimal association. Thoracic PhA was lower than trunk or abdominal values, indicating that thoracic measurements may better capture localized extracellular fluid changes in PDAcompared with other regions. Conclusion: Thoracic PhA at 5 kHz effectively reflects extracellular fluid changes in PDA, complements structural echocardiography, and tracks postoperative fluid normalization. Its non-invasive nature supports clinical utility for monitoring hemodynamic burden and therapeutic response. Full article

Sleep monitoring is critical for diagnosing and treating sleep disorders. Although polysomnography (PSG) remains the clinical gold standard, its complexity, discomfort, and lack of portability limit its applicability for long-term and home-based monitoring. To overcome these challenges, this study introduces a novel flexible headband system designed for multi-modal physiological signal acquisition, incorporating dry electrodes, a six-axis inertial measurement unit (IMU), and a temperature sensor. The device supports eight EEG channels and enables wireless data transmission via Bluetooth, ensuring user convenience and reliable long-term monitoring in home environments. To rigorously evaluate the system’s performance, we conducted comprehensive assessments involving 13 subjects over two consecutive nights, comparing its outputs with conventional PSG. Experimental results demonstrate the system’s low power consumption, ultra-low input noise, and robust signal fidelity, confirming its viability for overnight sleep tracking. Further validation was performed using the self-collected HBSleep dataset (over 184 h recordings of the 13 subjects), where state-of-the-art sleep staging models (DeepSleepNet, TinySleepNet, and AttnSleepNet) were applied. The system achieved an overall accuracy exceeding 75%, with AttnSleepNet emerging as the top-performing model, highlighting its compatibility with advanced machine learning frameworks. These results underscore the system’s potential as a reliable, comfortable, and practical solution for accurate sleep monitoring in non-clinical settings. Full article

Tryptophan (Trp) and tryptamine (Tryp), critical biomarkers in mood regulation, immune function, and metabolic homeostasis, are increasingly recognized for their roles in both oral and systemic pathologies, including neurodegenerative disorders, cancers, and inflammatory conditions. Their rapid, sensitive detection in biofluids such as saliva—a non-invasive, real-time diagnostic medium—offers transformative potential for early disease identification and personalized health monitoring. This review synthesizes advancements in electrochemical sensor technologies tailored for Trp and Tryp quantification, emphasizing their clinical relevance in diagnosing conditions like oral squamous cell carcinoma (OSCC), Alzheimer’s disease (AD), and breast cancer, where dysregulated Trp metabolism reflects immune dysfunction or tumor progression. Electrochemical platforms have overcome the limitations of conventional techniques (e.g., enzyme-linked immunosorbent assays (ELISA) and mass spectrometry) by integrating innovative nanomaterials and smart engineering strategies. Carbon-based architectures, such as graphene (Gr) and carbon nanotubes (CNTs) functionalized with metal nanoparticles (Ni and Co) or nitrogen dopants, amplify electron transfer kinetics and catalytic activity, achieving sub-nanomolar detection limits. Synergies between doping and advanced functionalization—via aptamers (Apt), molecularly imprinted polymers (MIPs), or metal-oxide hybrids—impart exceptional selectivity, enabling the precise discrimination of Trp and Tryp in complex matrices like saliva. Mechanistically, redox reactions at the indole ring are optimized through tailored electrode interfaces, which enhance reaction kinetics and stability over repeated cycles. Translational strides include 3D-printed microfluidics and wearable sensors for continuous intraoral health surveillance, demonstrating clinical utility in detecting elevated Trp levels in OSCC and breast cancer. These platforms align with point-of-care (POC) needs through rapid response times, minimal fouling, and compatibility with scalable fabrication. However, challenges persist in standardizing saliva collection, mitigating matrix interference, and validating biomarkers across diverse populations. Emerging solutions, such as AI-driven analytics and antifouling coatings, coupled with interdisciplinary efforts to refine device integration and manufacturing, are critical to bridging these gaps. By harmonizing material innovation with clinical insights, electrochemical sensors promise to revolutionize precision medicine, offering cost-effective, real-time diagnostics for both localized oral pathologies and systemic diseases. As the field advances, addressing stability and scalability barriers will unlock the full potential of these technologies, transforming them into indispensable tools for early intervention and tailored therapeutic monitoring in global healthcare. Full article

This review provides a critical and technically grounded assessment of continuous electrocoagulation processes (CEPs) for the treatment of industrial inorganic pollutants, emphasizing recent innovations, methodological developments, and practical outcomes. A comprehensive literature survey indicates that 53 studies published over the past 25 years have investigated CEPs for inorganic contaminant removal, with 36 focusing on standalone electrocoagulation systems and 17 exploring integrated CEPs approaches. Recent advancements in reactor design, such as enhanced internal mixing, optimized electrode geometry, and modular configurations, have significantly improved treatment efficiency, scalability, and operational stability. Evidence indicates that CEPs can achieve high removal efficiencies for a wide range of inorganic contaminants, including fluoride, arsenic, heavy metals (e.g., chromium, lead, nickel, iron), nitrates, and phosphates, particularly under optimized operating conditions. Compared to conventional treatment methods, CEPs offer several advantages, such as simplified operation, reduced chemical consumption, lower sludge generation, and compatibility with renewable energy sources and complementary processes like membrane filtration, flotation, and advanced oxidation. Despite these promising outcomes, industrial-scale implementation remains constrained by non-standardized reactor designs, variable operational parameters, electrode passivation, high energy requirements, and limited long-term field data. Furthermore, few studies have addressed the modeling and optimization of integrated CEPs systems, highlighting critical research gaps for process enhancement and reliable scale-up. In conclusion, CEPs emerge as a novel, adaptable, and potentially sustainable approach to industrial inorganic wastewater treatment. Its future deployment will rely on continued technological refinement, standardization, validation under real-world conditions, and alignment with regulatory and economic frameworks. Full article

Electroencephalography (EEG) is a non-invasive biosensing platform with a spatial-frequency content that is of significant relevance for a multitude of aspects in the neurosciences, ranging from optimal spatial sampling of the EEG to the design of spatial filters and source reconstruction. In the past, simplified spherical head models had to be used for this analysis. We propose a method for spatial frequency analysis in EEG for realistically shaped volume conductors, and we exemplify our method with a five-compartment Boundary Element Method (BEM) model of the head. We employ the recently developed technique for spatial harmonic analysis (Sphara), which allows for spatial Fourier analysis on arbitrarily shaped surfaces in space. We first validate and compare Sphara with the established method for spatial Fourier analysis on spherical surfaces, discrete spherical harmonics, using a spherical volume conductor. We provide uncertainty limits for Sphara. We derive relationships between the signal-to-noise ratio (SNR) and the required spatial sampling of the EEG. Our results demonstrate that conventional 10–20 sampling might misestimate EEG power by up to 50%, and even 64 electrodes might misestimate EEG power by up to 15%. Our results also provide insights into the targeting problem of transcranial electric stimulation. Full article