Technology and design in electronic equipment

Topological transformation of eddy currents in anisotropic electrically conductive structures

2026-08-11T15:01:14+02:00

This paper presents numerical modeling and a comprehensive topological analysis of the eddy current density component jz distribution in homogeneous anisotropic electrically conductive plates. The analysis is performed using a spectral-domain solver based on the Fourier transform of the Poisson equation and covers a wide range of anisotropy coefficients (0.05 ≤ K ≤ 150) at a crystallographic axis orientation angle γ = 45°. The results demonstrate that the classical interpretation of eddy current structure 'destruction' at extreme K values is actually a qualitative topological transformation—specifically, a transition from closed elliptical trajectories to quasi-linear directed flows. We prove the invariance of this transformation mechanism with respect to the reciprocal transformation K → 1/K accompanied by a 90° coordinate system rotation. Furthermore, by analyzing the curvature radius of eddy current lines at the ellipse vertices, we propose a physically justified criterion for determining critical operating regimes. This criterion directly links the plate's geometric parameters (thickness dlayer, major and minor semi-axes l and m) to the critical anisotropy coefficient K_cr. Practically, these findings allow for deliberate control over the eddy current field topology in anisotropic electrically conductive transducers. Transitioning to the quasi-linear regime enables significant adjustments in device impedance, control of the transformation ratio and inductance, and the realization of directed energy flows. This opens up new avenues for developing efficient matching elements, directed electromagnetic radiation sources, antenna systems, and optimized wideband infocommunication devices with enhanced energy efficiency.

Characteristics of nanocluster subsystem components of heterojunctions

2026-08-11T15:00:38+02:00

A calculation and analysis of the characteristics of nanocluster (NC) subsystem components as structural elements for silicon electronics materials have been performed. Effective computational models were selected to evaluate the structural, energetic, and kinetic characteristics of NCs of various sizes. To analyze geometric topology stability and electron density distribution, a physical model based on quantum-chemical methods and interatomic interaction potentials is proposed. Atomic structure optimization and electronic property analysis of silicon nanostructures revealed that chemical bond lengths increase during cationization and decrease during anionization. The influence of the matrix environment on nanocluster properties was analyzed. A phenomenon defined as the “switching” of interatomic chemical bonds within the nanocluster was identified. This effect yields practical optical capabilities that can be utilized to design color-sensitive semiconductor devices.

Modeling of a photodiode structure based on a heterojunction ZnO/Si

2026-08-11T15:01:35+02:00

In this work, a self-powered photodetector based on a bulk ZnO/Si p–n heterojunction is numerically investigated and analyzed using the Solar Cell Capacitance Simulator in One Dimension (SCAPS-1D). The energy band diagram, electron-hole generation and recombination rates, current-voltage (J–V) characteristics, spectral photosensitivity response, and specific detectivity are examined. To optimize photodetector performance, the effects of absorber layer thickness, shallow acceptor and donor densities, and defect density were systematically studied. Various electron transport parameters of ZnO were also considered. The responsivity and specific detectivity of the simulated photodetector are 0.23 A/W and 1.1·10¹⁰ Jones, respectively.

Hardware software true random number generator based on a semiconductor photodiode array and logical combinations of cellular automata

2026-08-11T15:01:00+02:00

Primary binary sequences obtained directly from semiconductor photodiode arrays of standard CMOS webcams exhibit significant non-uniform frequency distributions and high inter-frame correlation. Experimental measurements reveal critical defects, including anomalous byte gaps in the [0...25] range and a 30% correlation in darkness. Primary binary sequences obtained directly from semiconductor photodiode arrays of standard CMOS webcams exhibit significant non-uniform frequency distributions and high inter-frame correlation. Experimental measurements reveal critical defects, including anomalous byte gaps in the [0...25] range and a 30% correlation in darkness. The primary entropy source is the stochastic photocurrent of the array elements, captured at 25 frames per second and transformed into discrete numbers via analog-to-digital conversion. Local statistical correlations are eliminated using post-processing based on logical combinations of one-dimensional cellular automata. The developed algorithm combines chaotic rule-switching and a multi-component XOR-MIX combination of equivalent primitives.. For high computational efficiency, a lightweight algorithm for adaptive control of evolution iterations based on express root-mean-square deviation control is introduced. The low complexity of bitwise Boolean operations enables real-time data processing on personal computers and embedded microcontrollers. Experimental results show that the developed algorithm provides a real-time generation speed of 47.8 Mbps, with an additional CPU load of only 0.3% and a frame latency of less than 0.1 ms. The normalized stream completely eliminates inherent hardware defects, successfully passing all 15 NIST STS test groups with a stable proportion of over 96%, confirming the cryptographic strength of the method and its high suitability for modern information security applications.

Neural network-based methods for spread spectrum signal classification in radio monitoring systems

2026-08-11T15:01:28+02:00

Automatic classification of spread spectrum signals — frequency-hopping, direct-sequence, and chirp — is a key task in modern radio monitoring systems, particularly relevant for distributed sensor networks with constrained computational resources. A critical review of existing approaches shows that none of the three generations of classification methods — classical deterministic, feature-based machine learning, and deep learning on time-frequency representations — simultaneously meets three essential requirements: high accuracy at negative signal-to-noise ratios, computational complexity below 10⁵ multiply–accumulate operations per realization, and compatibility with integer arithmetic for embedded deployment. This paper proposes a method that addresses this gap through
a compact, informative feature vector combining frequency-domain, time-frequency, and statistical characteristics. The informativeness of Hjorth parameters is theoretically justified via their analytical link to spectral moments of the power spectral density, enabling O(N) time-domain computation equivalent to frequency-domain analysis. A formalized ablation analysis with three quantitative selection criteria (individual significance, pairwise correlation below 0.7, and absence of negative contribution) yields a reduced vector of five components. Complexity analysis confirms approximately 3·10⁴ operations per realization and 2 kB model memory in integer configuration — four orders of magnitude less than convolutional network–based approaches. Experimental evaluation of a multilayer perceptron classifier demonstrates stable accuracy above 91% across a wide SNR range, 93.2% at 20 dB and 87% at −10 dB, with negligible degradation under integer quantization, confirming practical applicability to embedded and distributed radio monitoring systems.

Adaptation of the weighted efficiency assessment method for photovoltaic inverters to climatic and operational conditions of Ukraine

2026-08-11T15:00:52+02:00

A reproducible methodology for deriving region-specific weighted efficiency coefficients for photovoltaic inverters from publicly available PVGIS data is developed and applied to 19 Ukrainian locations across five climate zones. Full 19-year hourly radiation series from PVGIS SARAH-3 (2005–2023) are used instead of TMY (typical meteorological year) data to avoid systematic bias in the distribution tails.

Results reveal that the Ukrainian inverter operating profile differs substantially from the EU standard (EN 50530): the dominant 50% load point weight decreases from 0.48 (EU) to 0.32 (Ukraine), while the 75% load point — which is absent from the EU formula — captures 0.36 of annual energy. The 100% load point weight drops from 0.20 to 0.004, indicating that Ukrainian inverters virtually never reach full rated power. A clear north-south gradient is observed across five climate zones.

Application to six commercial inverters popular in the Ukrainian market demonstrates ranking changes between the EU and Ukraine-specific metrics. Uncertainty analysis using the resampling method (1000 resamples) confirms statistical robustness with 95% confidence intervals below ±0.006 for all weighting coefficients. Sensitivity analysis shows that the results are stable for inverter loading ratios up to 1.2. The impact of Ukraine’s grid instability (1,951 hours of blackouts in 2024) on effective inverter utilization is discussed. The methodology is transferable to any region covered by PVGIS.

Keywords: photovoltaic inverter, weighted efficiency, power conversion efficiency, national weighted efficiency, PVGIS, European efficiency, California efficiency.

Inactive power components in UAV power system based on DC-DC boost converter

2026-08-11T15:01:07+02:00

This article analyzes the issue of inactive power components in DC power systems, with a particular focus on unmanned aerial vehicle (UAV) power networks. Analytical expressions were derived to determine the exchange power under various states of the power switch. A model based on the equivalent circuit of the converter–motor system was developed in MATLAB/Simulink. The simulation results demonstrate the presence of exchange power in a system utilizing a DC-DC boost converter, and the maximum values of this exchange power were determined. Finally, the study concludes that compensatory measures are necessary to minimize inactive power components.

Pulse method for determining the current state of health of an electrochemical energy storage device

2026-08-11T15:00:30+02:00

A single-pulse galvanostatic method for rapid determination of the current State of Health (SOH) of electrochemical energy storage devices in dynamic operating modes has been developed and experimentally validated. The proposed method enables SOH assessment without interrupting normal load operation. It relies on the Haar wavelet transform to process the response signal of the energy storage device to a short-term test pulse. Considering the specific profile of the response signal, which reflects multi-stage electrochemical kinetics and is described by slowly changing functions, applying the Haar wavelet transform yields a real-time time-frequency representation of the electrochemical process. Processing the depolarization curve of the response signal following the test pulse via the Haar wavelet transform restricts the area under the voltage curve, which correlates directly with the utilization factor of active materials. Thus, the derived wavelet parameters serve as informative indicators for evaluating the current SOH within a specified time window of the depolarization voltage curve. Experimental results reveal an irreversible, gradual decline in SOH over operational time driven by degradation processes, with the degradation rate accelerating in the later stages of service life. This behavior highlights the complex, dynamic, and non-linear nature of degradation in electrochemical energy storage systems. Unlike existing diagnostic techniques, the developed single-pulse galvanostatic method eliminates the need to disconnect the energy storage unit from the load, allowing real-time SOH monitoring under actual operating conditions.

Mathematical modeling of current density distribution in electrodes of electrosurgical instruments with rectangular working surfaces

2026-08-11T15:00:45+02:00

This study investigates the influence of the skin effect on electromagnetic processes occurring in the rectangular electrodes of electrosurgical instruments during alternating current flow. The mathematical modeling was performed by solving partial differential equations using the numerical finite element method. The simulation results demonstrate an uneven current density distribution along the perimeter of the rectangular electrode. The current is highly concentrated in the corners of the electrode and is practically absent in its center. The active resistance of a copper rectangular electrode (with a cross-section of 3 х 15 mm and a length 3 mm) was analyzed within the frequency range of 22 to 880 kHz. It was established that increasing the current frequency leads to higher joule heating losses in the electrodes due to a reduction in the effective cross-sectional area caused by the skin effect. Modifying the electrode geometry by rounding its corners allows for equalizing the current density distribution and reducing the total resistance.

Parametric analysis of an orthogonal eddy current transducer for measuring the thickness of dielectric coatings

2026-08-11T15:01:21+02:00

This paper investigates the parameters of orthogonal eddy current transducers (ECTs) for measuring dielectric coating thickness on electrically conductive substrates—a critical task for ensuring product durability and material savings in mechanical engineering, aerospace, and energy applications. The study aims to determine how transducer geometry, excitation frequency, and lift-off influence the useful signal amplitude and signal-to-noise ratio (SNR). Experiments were performed using three ECT variants of different sizes on brass, aluminum, and steel substrates. The results show that the signal amplitude changes monotonically with lift-off, exhibiting maximum sensitivity at small gaps. Signal normalization reveals that the calibration curves are practically frequency-independent, enabling a common normalized characteristic for transducers of the same type. SNR analysis indicates a maximum near 800 kHz for small-sized ECTs, whereas larger transducers peak within the 200–400 kHz range. Furthermore, the upper limit of measurable coating thickness is determined by the width of the active zone b, requiring larger transducers for thicker coatings. The practical significance of this work lies in optimizing the frequency and geometric parameters of ECTs to improve measurement accuracy, simplify high-frequency circuitry, and reduce material waste during quality control.