NiFe2-xYxO4 spinel ferrites doped with Y3+ (x = 0-0.02) were prepared by the solution-combustion method and extensively investigated in order to study the structural, electrical, magnetic and electrochemical effects of controlled rare-earth doping. From X-ray-diffraction measurements, the materials were figured to be of a singlephase and cubic spinel (Fd-3m) structure. The substitution by larger Y3+ (0.90 & Aring;) cations into the octahedral Fe3+ sites in the lattice gave rise to an increase in the lattice dimensions (a = 8.338 -> 8.356 & Aring;), unit-cell volume, increase in microstrain of the network of the lattice and a decrease in the crystallite size (32.4 -> 25.7 nm). XRF mapping and quantitative spectra showed a uniform distribution of the elements and gradual addition of the Y. As a result of the increase of the lattice dimensions, the FTIR spectra exhibited systematic red-shifts of the A and B-site metal-oxygen vibrational modes together with calculated weakened force constants and softening of the lattice itself. The results of UV-Vis diffuse reflectance spectroscopic determinations exhibited a decrease in the bandgap energy from 2.14 to 1.99 eV. This behavior can be attributed to the formation of defect states, enhanced electron-phonon coupling, and modifications in Fe-O covalency. Although first-principles calculations are not included in the present study, the experimentally observed bandgap narrowing is consistent with density functional theory (DFT) reports on rare-earth-doped NiFe2O4 and related spinel ferrites. These studies demonstrate that substitution of larger trivalent ions at octahedral Fe3+ sites induces localized defect states near the conduction band edge, alters Fe 3d-O 2p hybridization, and enhances electron-phonon coupling, collectively leading to a reduced bandgap. Additionally, strain-induced symmetry breaking and oxygen-vacancy-related states further contribute to sub-band-gap electronic transitions, in agreement with the present UV-Vis and XRD-derived microstrain results. The magnetic investigations showed soft ferrimagnetic behaviour with a decrease of coercivity (183.3 -> 162.9 Oe) and remanence (9.77 -> 7.99 emu/g). The reason for the above being due to the dilution of B-cations, abrogation of the superexchange coupling and the spin-canting. The decrease of magnetocrystalline anisotropy, exchange stiffness, pinning strength and irreversible switching was confirmed by the law of the approach to saturation (LAS) and FORC analyses giving rise to the Y doping producing a general decrease in the magnetic response. The electrochemical properties were greatly improved being lower over-potentials, smaller Tafel slopes, increased areas of the CV, longer discharge periods, greater capacitances and lower charge transfer resistances (Rct). The Nyquist and Bode plot characteristics for the materials showed an increase in conduction, faster ion diffusion and better pseudocapacitive behaviour. The GCD and Persistency tests showed that the more doped samples show very stable symmetric curves and better reversibility.
Methods of producing targets from high-entropy alloys for coating application by ion plasma sputtering are analyzed. The alloy composition is selected (Co–Cr–Fe–Mn–Ni–Cu), and the proportions of the chemical elements are determined. A technology is proposed for sintering pressed powder mixtures and producing targets of the required size and shape.
High-entropy alloys (HEAs) demonstrate exceptional thermodynamic stability, making them promising candidates for extreme thermal environments, including near-space applications. However, their performance under such conditions remains insufficiently studied. Moreover, the range of HEA synthesis techniques continues to expand, and a relatively novel development involves the deposition of high-entropy coatings by vacuum ionplasma technology. There are also a range of insufficiently studied issues in this area, in particular those related to the implementation of protective functions of coatings under barothermal conditions. The present study is aimed at investigating the stability of ion-plasma high-entropy coatings on contact surfaces operating under load in conditions of significant temperature differences. The results of such a study are relevant, for example, from the point of view of using HEA in the form of antifriction coatings on open contact surfaces of hinges, variators, drives and other kinematic units of the friction type, eliminating the use of lubricants, in spacecraft operating in low Earth orbits (LEO). The work safety and precision of such friction units in outer space directly affects the space flight safety as a whole. High-entropy coatings from CrTiZrNbHf, CuCrMnFeCoNi, (CrTiZrNbHf)N, and (CuCrMnFeCoNi)N systems were synthesized using vacuum cathode-arc deposition and magnetron sputtering, with comprehensive microstructural and functional characterization. To assess their performance under extreme thermal conditions, tribological testing was conducted at temperatures of -60 degrees C and +150 degrees C. Key findings demonstrate that nitride high-entropy coatings exhibited significantly superior wear resistance compared to non-nitrided metallic counterparts across all tested temperatures. (CrTiZrNbHf)N coating maintained exceptional tribological stability across the entire temperature range, making it the most promising solution for loaded friction units requiring reliable performance under thermally cyclic conditions, such as those encountered in space environments on the LEO. Thus, we found the optimal composition for high-entropy coatings operating within the investigated thermal regime. For nitrogen-containing ion-plasma coatings, the most effective performance is achieved when incorporating Group IV and V transition metals (e.g., Ti, Zr, Nb, Hf, V) characterized by high enthalpy of formation for their respective nitrides (MeN). Crucially, these nitrides must adopt a face-centered cubic crystalline solid-solution structure (NaCl-type) within the coating matrix.
This article presents the theoretical and methodological foundations of neural network forecasting of key performance indicators in the context of the digital transformation of corporate governance. The feasibility of using multilayer and recurrent architectures for modeling complex nonlinear relationships between financial, production, and market indicators is substantiated. Approaches to forming a feature space, data normalization, selecting an objective function, and assessing predictive accuracy are systematized. A conceptual framework for a neural network model is proposed, aimed at improving the validity of management decisions, reducing information asymmetry, and increasing the enterprise’s adaptability to environmental fluctuations and internal structural constraints over time.
The article discusses modern trends in the automation and control of energy systems in the context of the growth of distributed generation, the introduction of renewable energy sources, storage devices, digital substations, and controlled loads. It shows that the transition from a centralized model of the electric power industry to a distributed digital architecture requires multi-level monitoring, state estimation, optimization of modes, emergency control, and enhanced cybersecurity. Special attention is given to observability, frequency and voltage regulation, relay protection and automation, demand management, digital twins, and intelligent analytics.
