Search Results (218)

The unauthorized addition of silver nitrate and excessive heavy metals in hair dye creams poses serious health risks, creating an urgent need for rapid and sensitive detection methods. In this study, a spark discharge-enhanced fiber laser-induced breakdown spectroscopy (SD-LIBS) system was developed for the simultaneous detection of five heavy metal ions (Ag, Pb, Cd, As, Hg) in hair dye creams. The system combines three signal enhancement strategies: high-voltage spark discharge, Au nanoparticle-assisted enhancement, and analyte enrichment on a superhydrophobic–hydrophilic patterned graphite substrate. Hydrophilic micro-pits were fabricated by laser scanning on the superhydrophobic graphite surface to confine and concentrate analyte residues upon droplet drying. Under optimized discharge conditions of 22 nF and 2000 V, the spark discharge achieved a signal-to-noise ratio enhancement of approximately 12 times. Au nanoparticle enhancement further increased the signal intensity by 49.3%. The optimal pit diameter and sample loading volume were 0.1 mm and 30 μL, respectively. The calibration curves for all five elements showed good linearity with R² values close to 0.99, and the lowest detection limits reached 1.9 μg/L for Ag. The average spiked recovery was 82.07%. The method was applied to four commercial hair dye cream samples, and the Ag detection results agreed well with ICP-OES reference values with an average error of 16.41%. This work demonstrates that the proposed SD-LIBS system offers a low-cost, rapid, and sensitive approach for on-site screening of heavy metals in cosmetics and other consumer products. Full article

This study developed a detection method for hymexazol residues in sugar beet, targeting its low molecular weight, high polarity, and lack of chromophores. The method optimized mass spectrometry conditions, liquid chromatography parameters, and extraction/purification protocols to address the matrix characteristics of sugar beet. Specifically, the sample pretreatment involved extraction with acetonitrile, followed by purification using GCB, silica, and C18 sorbents to minimize matrix interference. Sensitivity was enhanced by reducing flow rate and spray voltage. The method demonstrated high performance and was applied to analyze real samples. The LOD and LOQ were theoretically determined to be 1.22 and 3.80 μg/kg, respectively, using the blank standard deviation method. At the spiked levels of 5.0, 10, and 50 μg/kg, the intraday and interday recoveries were 80.2–97.9% and 78.1–101.7%, with corresponding RSDs of 4.8–6.4% and 4.6–8.8%, respectively. These results could meet the requirements for pesticide residue analysis and regulatory monitoring. Full article

Organophosphate esters (OPEs) are commonly used flame retardants and plasticizers, which can easily be released into the soil environment and have potential hazards such as neurotoxicity and developmental toxicity. Establishing an efficient and sensitive detection method plays a crucial role in soil pollution assessment. Currently, there have been numerous studies on the detection of OPEs in soil using ultrasonic extraction and solid-phase extraction, while relatively few studies have focused on the analysis of multiple OPEs in soil by accelerated solvent extraction combined with d-SPE clean-up and ultra-high performance liquid chromatography–tandem mass spectrometry. The d-SPE purification method eliminates the need for column passage, shortens sample preparation time, and avoids the risk of background contamination from OPEs that may be introduced by SPE. This study developed a liquid chromatography–tandem quadrupole mass spectrometry (LC-MS/MS) method for the determination of 25 OPEs in soil, and systematically optimized the pretreatment and instrumental analysis conditions. Accelerated solvent extraction was used for pretreatment, and dichloromethane–methanol (1:1, V/V) was determined as the optimal extraction solvent. A mixed adsorbent of N-propyl ethylenediamine (PSA) and C18 was selected for dispersive purification, effectively removing matrix interference and improving recovery rates. The mass spectrometry parameters such as collision energy and declustering voltage were optimized, significantly enhancing ion response intensity and detection sensitivity. The method showed good linearity within the concentration range of 1–100 ng/mL, with correlation coefficients all greater than 0.994. The spiked recovery rates ranged from 70.6% to 111% with a relative standard deviation (RSD) of 1.2–11.8%. The precision and accuracy met the requirements for environmental sample analysis. The method was applied to the detection of actual soil samples, and the results were stable and reliable. This method is simple to operate, highly sensitive, and widely applicable, providing reliable technical support for the pollution monitoring, source tracing, and ecological risk assessment of OPEs in soil. Full article

Large-scale spiking neural network simulation requires numerical integration that preserves membrane dynamics and spike timing without making fine-resolution updates prohibitively expensive. This balance is difficult for conductance-based leaky integrate-and-fire (LIF) networks because synaptic decay, threshold crossings, resets, and refractory periods form a hybrid dynamical system. To address this difficulty, we introduce a spike-aware propagation (SAP) approximation method that combines exact receptor-trace updates, analytic homogeneous membrane propagation, Gauss–Legendre quadrature, and spike localization, improving the accuracy–efficiency Pareto frontier. We establish an error bound and conditional convergence under consistent refinement for the proposed SAP. At h = 1 ms, the single-realization T = 1000 ms comparison showed a lower voltage RMSE for SAP than for Euler at the same width in the two high-activity regimes. The five-seed T = 200 ms robustness experiment likewise showed lower voltage RMSE for SAP than for NEST at the same width. At the highest drive, the paired mean reduction was 3.91 mV (95% CI, 3.85–3.97 mV). This quantified gain supports SAP as a practical route to an improved accuracy–efficiency balance in large-scale conductance-based LIF simulation while underscoring the method’s configuration-dependent and regime-dependent scope. Full article

This paper explores methods to eliminate high-voltage spikes during dead time ($t_{dt}$) in high-frequency inverters for Wireless Power Transfer (WPT) systems, focusing on the transition from traditional Silicon IGBTs to enhancement-mode Gallium Nitride (GaN) HEMTs. At elevated switching frequencies, dead-time parameters strongly govern system efficiency and signal integrity. While IGBTs suffer from reverse-recovery charge ($Q_{rr}$) in antiparallel freewheeling diodes that generates severe voltage spikes, hard-switching GaN systems require precise dead-time minimization to prevent shoot-through while limiting third-quadrant conduction losses. Unlike prior WPT studies bounded by specific hardware setups, this paper presents a baseline technology benchmark that explicitly decouples intrinsic semiconductor commutation physics, specifically $Q_{rr}=0$ versus third-quadrant conduction, from macro-system parameters ($f_{sw}$, power level, and resonant topology). Experimental evaluation of a 130 kHz L-S-tuned GaN full-bridge inverter confirms that primary current commutates via third-quadrant conduction during dead time, completely eliminating reverse-recovery voltage spikes ($I_{rr}=0$). Ultimately, this work demonstrates that GaN’s spike-free operation is an intrinsic device-level property, reframing the dead-time optimization objective from transient overvoltage suppression to third-quadrant conduction loss minimization in next-generation WPT systems. Full article

To address the transient power surges and DC-link voltage fluctuations arising from fast frequency response demands in new power systems, this paper proposes a Natural Switching Surface (NSS) control strategy for active neutral-point clamped (ANPC) converters. First, the operating modes and working principles of the ANPC converter are analyzed, and the phase trajectory relationship between the inductor current and DC-side voltage under diverse operating conditions is mathematically derived. On this basis, a systematic NSS control law is established according to the piecewise mathematical model of the converter. Furthermore, a current-limited NSS control scheme is developed to suppress transient current spikes, which realizes smooth voltage and current output regulation and effectively mitigates power transients and DC voltage fluctuations induced by fast frequency response operations and external power disturbances. Comprehensive simulation and prototype experimental results validate the superior performance of the proposed method. Quantitative comparisons demonstrate that, compared with the conventional PI control, the proposed strategy shortens the converter startup time by 1.5 s, restricts the DC voltage drop within 15 V under power disturbance conditions (in contrast to over 60 V with PI control), and achieves faster dynamic recovery and higher operation stability. The proposed method provides an effective solution for high-performance fast frequency response and stable grid integration of renewable energy and energy storage systems. Full article

The arm multiplexing alternate arm converter (AM-AAC) can reduce the number of submodule capacitors, but transient voltage spikes may appear at commutation instants when phase-shifted carrier pulse-width modulation (PSC-PWM) is used with a low submodule count. This paper analyzes the spike-generation mechanism from the discrete sampling behavior of symmetric regular sampling. The analysis shows that interleaved carrier phases produce nonuniform response delays among submodules, so the arm voltage follows a staircase transition rather than an ideal step change. After mirror folding by the commutation switches, this transition is coupled to the ac side as a voltage spike. Analytical expressions are derived for the spike duration and amplitude, revealing their dependence on the submodule number and phase-shift conduction angle. A suppression strategy is then proposed by shifting the carrier phase of the commutation switches so that commutation occurs near the midpoint of the spike duration. MATLAB R2024b simulations and RTDS hardware-in-the-loop experiments verify that the proposed method substantially reduces the spike amplitude without additional hardware, while PSC-PWM maintains lower output-current THD than nearest-level modulation in low-submodule AM-AAC applications. Full article

High-channel-count neural recording requires wireless links with high throughput, low power, and compact implementation, yet commercial protocols and phase-locked loop (PLL)-based transmitters often trade data rate against power and complexity. We present a low-power, PLL-less wideband on–off keying (OOK) neural-signal transmitter fabricated in a 180 nm CMOS process. The transmitter employs a free-running inductor–capacitor voltage-controlled oscillator (LC-VCO), a Gilbert mixer for OOK modulation and reverse isolation, and a current-reuse stacked power amplifier. It consumes 8 mA from a 3.3 V supply (26.4 mW), demonstrates modulation and receiver frame acquisition at a maximum raw input rate of 90 Mbps, corresponding to a 180 Mbps Manchester-coded line rate, and tunes from 3.266 to 3.445 GHz. End-to-end bit error rate (BER) was measured at raw rates of 15 and 31.2 Mbps, corresponding to encoded rates of 30 and 62.4 Mbps; the latter matches the in vivo data stream. The transmitter was integrated with a 128-channel recording chip and evaluated in freely moving adult C57 mice. Wireless hippocampal spike and local field potential (LFP) recordings, wired-system comparison, and event-locked LFP analysis support its feasibility for untethered neural recording. Full article

Organic memristors are attractive building blocks for neuromorphic computing owing to their intrinsic synaptic functionalities and solution-processability. However, their operational instability remains a major challenge, primarily arising from poorly controlled semiconductor crystallization and stochastic conductive filament formation. Here, we report a high-performance solution-processed organic memristor based on a TIPS-pentacene/PMMA/CdSe-ZnS quantum-dot hybrid system, in which a dual-engineering strategy is employed to simultaneously regulate film crystallization and filament dynamics. Specifically, the PMMA matrix templates the molecular ordering of TIPS-pentacene to improve film uniformity and crystallinity, while CdSe/ZnS quantum dots locally modulate the electric field to direct and confine conductive filament formation. As a result, the device exhibits ultralow and highly uniform switching voltages (0.473 V for set and −0.430 V for reset), suppressed device-to-device variation, long retention exceeding 10⁴ s, and endurance over 1200 switching cycles. In addition, the memristor supports multilevel data storage and successfully emulates key synaptic functions, including long-term potentiation/depression, paired-pulse facilitation, and spike-timing-dependent plasticity. This work provides a materials-level strategy for achieving reliable and low-power organic memristors, offering a viable route toward high-density nonvolatile memory and neuromorphic computing hardware. Full article

Conductive silicone interfaces are promising polymeric materials for wearable bioelectronic systems because they combine electrical continuity with elastomeric compliance, environmental durability, and moldability. In low-voltage wearable microcurrent interfaces, however, functional performance is governed not only by intrinsic material conductivity, but also by conductive network continuity, molded geometry, interfacial contact, and transient electrical response. In this study, we developed a spike-structured conductive silicone interface using a commercially available electrically conductive two-component silicone rubber and investigated its structure–electrical property relationships as a volume-resistive polymer interface. The interface consisted of a conductive silicone body with protrusions 7 mm in height and 3.6 mm in diameter, supported by a 1 mm base layer and electrically integrated through an Ag-paste-connected upper conduction region. Using a representative electrode-level resistance of 47.08 Ω, the geometry-derived apparent interfacial resistive response was estimated as 18.0 Ω·cm for the three-spike configuration and 24.0 Ω·cm for the four-spike configuration. The corresponding effective conductive areas were 0.305 cm² and 0.407 cm², respectively, giving analytical current-density amplification factors of 9.82 and 7.37 relative to a planar 3 cm² reference interface. Positional resistance mapping yielded an overall mean resistance of 47.80 ± 4.57 Ω, indicating acceptable electrical reproducibility across the structured conductive silicone interface. In addition, oscilloscope-based transient response analysis under a 5 V, 1 kHz square-wave input showed that the conductive silicone interface maintained the overall pulse waveform while showing a modest reduction in overshoot from 3.4 ± 0.1% to 2.7 ± 0.1%, with FFT traces used as qualitative waveform-monitoring displays. Formulation-dependent comparison further showed that increasing the silicone-rich fraction increased the measured resistance from 105 Ω to 145 Ω, whereas increasing conductive carbon loading reduced resistance but aggravated surface transfer. These results show that the conductive silicone interface functions not simply as a soft conductor, but as a volume-resistive, geometry-defined current-transfer medium whose behavior is governed by the coupled effects of conductive network formation, spike architecture, electrode-level resistance, and transient pulse response. This study provides a practical materials/interface design framework for spike-structured conductive silicone electrodes in wearable bioelectronic and electroceutical devices. Full article

This paper presents a primary side model predictive control (MPC) strategy for wireless power transfer (WPT) based charging of light electric vehicle (LEVs). A battery simulator develops a model to accurately reproduce constant-current (CC) charging profile from Open Ciruit Voltage (OCV) and State of Charge (SoC) parameters of the battery. This model forms the foundation of the predictive control design, allowing accurate prediction of the charging trajectory while avoiding reliance on secondary-side feedback signals. The WPT system employs a phase-shifted full-bridge (PSFB) inverter with S-S compensation, where the primary-side controller regulates the secondary-side charging current using only primary-side current measurements. In contrast to conventional secondary side control, which is tuned around nominal coupling, requires explicit feedback, and degrades under coil misalignment and parameter variations, the proposed MPC leverages integrated system and battery models to predict future states and optimally adjust the phase shift for robust charging operation. Simulation and experimental validation on a real-time LEV charging prototype under aligned, lateral, and angular misalignment conditions demonstrate significant reduction in current-settling time compared to fixed-gain proportional-integral (PI) and known adaptive feedback controllers for same system, with lower RMS current and reduced current spikes at the battery. On the embedded controller, the proposed MPC executes within approximately 1 µs per 85 kHz PWM cycle, corresponding to less than 10% CPU utilization, confirming its practical real-time feasibility. Full article

As power grids transition towards highly renewable generation on a global scale, maintaining dynamic stability is becoming a major challenge. Replacing traditional synchronous generators with inverter-based renewables strips the grid of rotational inertia, leaving active distribution networks highly vulnerable to frequency deviations and voltage spikes. To avoid expensive poles and wires upgrades, Battery Energy Storage Systems (BESS) are increasingly being deployed as Non-Network Solutions (NNS). However, the current literature reveals a distinct gap between the macro-scale economic planning of these storage assets and the micro-scale dynamic control actually required to keep the grid resilient. To address this gap, this review proposes a multi-layer deterministic synthesis framework that links physical renewable modelling, degradation-aware techno-economic planning, deterministic forecasting, and EMS dispatch through offline time-domain control validation for AC-microgrid energy storage integration. The research examines how advanced central control units within battery management systems can rigorously and jointly estimate State of Charge (SoC) and State of Energy (SoE) to ensure accurate grid-aware dispatch. Furthermore, the study explores the integration of degradation-aware economic modelling in HOMER Pro with dynamic transient control in MATLAB/Simulink R2025b, driven by hybrid metaheuristic optimization algorithms like Grey Wolf Optimizer (GWO) and Particle Swarm Optimization (PSO). This analysis demonstrates that integrating energy storage must be treated as a tightly coupled multidimensional optimization problem to successfully deliver the secure and sustainable infrastructure needed to solve the modern energy trilemma. Full article

Telmisartan (TEL) is a non-peptide, orally administered antihypertensive agent primarily known as angiotensin II type 1 (AT1) blocker. In this review, we provide a detailed overview of how TEL modulates voltage-gated Na⁺ current (I_Na) and affects action potential (AP) firing behavior. TEL exerts differential stimulatory effects on the peak and late components of I_Na when subjected to brief depolarizing pulses across a range of cell types, such as mHippoE-14 hippocampal neuron, cultured dorsal root ganglion neurons, and HL-1 atrial cardiomyocytes. TEL can augment the non-inactivating (persistent) I_Na elicited by ascending long ramp pulse in mHippoE-14 cells. By using a parvalbumin-expressing interneuron-based modeled cell combined with bifurcation analysis, it is possible to predict how applied current influences subthreshold oscillations and the generation of somatic spiking in the presence of TEL. According to the Hodgkin-Huxley model, mimicking the action of TEL—characterized by an increased peak amplitude of I_Na and a slowed inactivation time course—leads to the emergence of periodic oscillations in membrane potential. Using a Markovian process, a separate model can also be mathematically constructed, showing that changes in certain rate constants can simulate the effect of TEL on I_Na in cardiac cells. The molecular docking prediction between TEL and the Na_V1.7 channel was made by expected formation of hydrophobic interactions as well as hydrogen bonding. In addition to its antagonistic action at the AT1 receptor and its agonistic activation of peroxisome proliferator-activator-γ, TEL may also directly enhance I_Na, thereby modulating AP firing in a variety of excitable cells. Current evidence supports TEL’s modulatory impact on Na_V channel activity and cellular excitability, while also acknowledging that the mechanism—whether direct or indirect—remains under investigation. Full article

We perform stochastic simulations of the Hodgkin–Huxley and Morris–Lecar models with different numbers of ion channels in order to describe the effects of periodic electrical driving on spike rates and the regularity of spiking in a single neuron. For stochastic modeling, we use an efficient method that reduces the piecewise-deterministic Markov process of the membrane potential evolution to an ordinary differential equation between random opening and closing events. To characterize a regular component in the resulting voltage time series, we adopt a Wiener order parameter based on the autocorrelation function. We show that the effect of ion channel stochasticity on the spike rate is stronger at lower external force frequencies. The regular component of neural activity exhibits resonant-like behavior as a function of the driving frequency, with a maximum in the beta range. Full article

To address the issue of coordination failure in multi-stage surge protective devices (SPDs) under lightning surges in communication power systems, this study employs traveling wave propagation theory and electromagnetic transient simulations using the PSCAD/EMTDC platform. It systematically evaluates how lightning strike location, interstage cable length, and load type affect energy coordination and overvoltage response in a two-stage SPD configuration. By combining time-domain and frequency-domain analysis, the coupling mechanism of SPD conduction timing is revealed. There exists a critical length for the interstage cable to ensure coordinated operation of the SPDs. This critical length decreases with increasing surge intensity but increases significantly with greater lightning strike distance. Incorporating an appropriate series inductor can provide the necessary time delay, serving as an alternative to using a long cable. For capacitive loads, although an excessively short cable can reduce the amplitude of oscillatory voltage spikes, it aggravates the surge steepness, thereby stressing the SPD. These oscillations can be effectively suppressed by installing a damping resistor in front of the SPD2. Furthermore, the study reveals a strong coupling between energy coordination and overvoltage behavior under capacitive load conditions, indicating that the two must be jointly optimized. The parameter configurations and practical recommendations presented offer quantitative design guidance for SPD selection, cable layout, and resonance suppression in communication power systems. Full article