This work presents a first-principles study of the structural, mechanical, dynamical, electronic, and thermoelectric properties of the ternary Heusler compounds Ir 2 YSi (Y = Be, Ca, Sr). These materials crystallize in the cubic L2 1 structure (space group [Formula: see text]) and are found to be thermodynamically stable, with the non-magnetic state being energetically favored. The calculated elastic constants satisfy the Born criteria, confirming mechanical stability for all compounds, although Ir 2 SrSi shows relatively lower rigidity. Phonon dispersion curves exhibit no imaginary frequencies, indicating dynamical stability, with vibrational properties influenced by atomic mass differences. Electronic structure analysis reveals a metallic character for all compounds, with dominant Ir-[Formula: see text] states near the Fermi level and notable hybridization with Si-[Formula: see text] orbitals. A pseudo-gap observed in Ir 2 CaSi and Ir 2 SrSi suggests enhanced stability compared to Ir 2 BeSi. Thermoelectric properties show metallic behavior with increasing electrical and thermal conductivities as temperature rises. Despite some improvement across the series, the maximum figure of merit remains low ([Formula: see text]), limiting their efficiency for thermoelectric applications.
The magnetic properties and magnetocaloric effects (MCEs) of a mixed-spin Ising model composed of spins [Formula: see text] and [Formula: see text] on a hexagonal nanowire structure have been investigated using Monte Carlo simulations based on the Metropolis algorithm. The effects of exchange couplings, crystal fields, magnetic fields, and temperature on the magnetization, susceptibility, order parameter, compensation points, entropy, and adiabatic temperature have been analyzed in detail. This study reveals the existence of interesting critical phenomena, particularly the compensation behavior. Furthermore, the ground-state phase diagrams in the [Formula: see text], [Formula: see text], [Formula: see text] and [Formula: see text] planes were established, showing multiple stable configurations that are highly sensitive to exchange interactions and crystal fields. The compensation points appear for specific ranges of the system parameters. It was found that the compensation temperature emerges when [Formula: see text] and [Formula: see text] for the spin-[Formula: see text] sublattice, while the [Formula: see text] and [Formula: see text] parameters show no threshold effect. In this case, the compensation temperature remains constant. Regarding the MCE, characterized by the magnetic entropy change [Formula: see text] and the adiabatic temperature change [Formula: see text], significant variations were observed around the compensation temperature [Formula: see text] and the critical temperature [Formula: see text], indicating a strong potential for advanced magnetic cooling applications.
Following the initiation of artificial intelligence (AI) and machine learning (ML) methodologies for their prediction, optimization and synthesis toward spintronic device development. Ferrites and their related spinel oxides are becoming very useful for spintronics due to their tunable magnetic, electronic and structural properties. Thus, this review compiles recent developments in performance toward integration of knowledge and AI/ML-based applications on ferrites concerning spintronic traits. It discusses predictions regarding cation distribution engineering, surrogate modeling, defect synthetic optimization and device-level tailoring or property manipulation. The whole spectrum of studies includes ferrites (e.g., Mn–Zn ferrites, doped nickel ferrites), and these advances are also spelt out in terms of how AI/ML could distinguish fresh designs. Issues such as data scarcity, interpretability and how AI could integrate with experimental validation will also be touched on. It outlines the various opportunities for AI to be coupled to autonomous laboratories, high-throughput simulations, or even quantum ML.
In this study, we have theoretically investigated the influence of the anisotropy field and the Dzyaloshinskii-Moriya (D-M) type coupling on bulk and surface spin excitations. Two applications of the formalism developed here have been done on the trifluorides MF 3 (M=Fe, Cr) structures which provides a good illustration of the presence of magnetic frustration due to competing interactions and the existence of non-collinear structures. In the first part the bulk and surface spin dynamics are analyzed under the influence of anisotropy field whereas in the second step the antisymmetric interaction (D-M) is considered thus enabling a detailed analysis on the influence of the Dzyaloshinskii-Moriya (D-M) term on the propagating and evanescent precessional fields occurring in the neighborhood of the bulk-surface region. The bulk-surface spin dynamics are studied using theoretical formalism based on the symmetry properties obtained from the semi-infinite system by examining the matching equations for evanescent and propagating solutions deduced from the bulk secular equation, satisfying surface boundary conditions. The calculations have been carried out considering the competing inter-sublattices nearest and intra-sublattices next nearest neighbors exchange interactions occurring in the bulk and surface. It was found that the spin wave dispersion associated with the bulk as well as with the surface ar estrongly dependent on the values of ratio of bulk-surface parameter (J S /J AB ) and the canting angle Θ. An energy gap which illustrates a new magnetic ground state for surface spin quantum configuration is evidenced. In addition, it was observed that this energy gap increases as the non-collinearity increases.
This paper presents a comprehensive study of new technetium-based MXenes (Tcn+1Cn, for n=1 and n=2), exploring their structural, dynamic, electronic and thermodynamic properties. These materials, which adopt a 2D hexagonal structure, are analyzed in both the Nonmagnetic (NM) and Ferromagnetic (FM) phases. Cohesion energies show that the NM phase is more stable than the FM phase. Phonon calculations confirm the dynamic stability of these structures. The analysis of the electronic properties reveals their metallic behavior. The study of the thermoelectric properties of the Tc2C and Tc3C2 materials highlights interesting metallic behaviors, which vary with temperature. The electrical conductivity of both materials follows similar trends, showing that they maintain good electrical conductivity even at high temperatures. Their thermal conductivities also follow a typical metallic pattern, with linear increases, indicating that free electrons dominate thermal transport and enhance their ability to conduct heat at high temperatures. The evolution of the thermoelectric figure of merit (ZT) reveals interesting performance. The results suggest that these materials offer optimal performance at moderate temperatures, but their thermoelectric efficiency decreases at high temperatures due to the increase in thermal conductivity and the decrease in electron mobility. Our new materials Tc2C and Tc3C2 exhibit strong thermoelectric potential at room and intermediate temperatures. They are therefore better suited for thermoelectric applications at moderate temperatures.
This study investigates the magnetic properties and quantum correlations of a mixed-spin Ising nanotube with a core–shell architecture ([Formula: see text], emphasizing its potential for quantum information processing. Using Monte Carlo simulations (MCS) and mean-field theory (MFT), we examine the influence of longitudinal anisotropy — modeled through the crystal field — and exchange coupling parameters on the system’s phase transitions. Our results reveal that geometric frustration within the core–shell interface significantly modulates the magnetic susceptibility and the occurrence of compensation points. Crucially, we identify a regime where quantum entanglement is maximized near the critical temperature ([Formula: see text], where thermal and quantum fluctuations converge. By mapping these stability regions, we demonstrate that such nanostructured systems can serve as robust blueprints for maintaining coherence in qubit architectures. This work bridges the gap between statistical mechanics of spin systems and the practical requirements of scalable quantum computing.
The atoms of three spin-1/2 are positioned at the vertices of an equilateral triangle, while the remaining three are located at the midpoints, creating an inverted equilateral triangle with half the length of the original sides. Subsequently, they are arranged vertically in a manner that aligns the atoms in identical positions to create the nanowire. The spins at various sites are presumed to engage with five kinds of bilinear interaction parameters either [Formula: see text] or [Formula: see text] corresponding to the antiferromagnetic (AFM) and ferromagnetic (FM) interactions, respectively. The formulation is conducted using the exact recursion relation (ERR) approach. The magnetizations of six spins are computed based on the ERRs, followed by an examination of their thermal behaviors to derive the model’s phase diagrams. The FM phase is found to be intriguingly compressed between the AFM and PM phases at some negative J values which is reminiscent to semiconductor junctions and may have some utility as a magnetic junction in future technological applications.
This study investigates the thermoelectric (TE) performance of asymmetric resonant-tunneling magnetic tunnel junctions (A-RT-MTJs) incorporating an ultra-wide-bandgap [Formula: see text]-Ga 2 O 3 semiconductor and dissimilar ferromagnetic electrodes (CoFeB and La[Formula: see text]Sr[Formula: see text]MnO[Formula: see text]. Using a tight-binding model combined with the nonequilibrium Green’s function (NEGF) method, we analyze spin-dependent quantum transport under thermal gradients. The asymmetric design introduces sharp resonant-tunneling states within [Formula: see text]-Ga 2 O 3 layer, enabling energy-selective spin transport and enhanced spin filtering. Compared to single-barrier MTJs and symmetric RT-MTJs, A-RT-MTJs exhibit improvements in TE properties due to amplified energy filtering and suppressed thermal conductivity. These results demonstrate that A-RT-MTJs with tailored resonant states and material asymmetry offer a promising pathway for high-efficiency thermal-to-spin energy conversion, advancing applications in spincaloritronic devices.
A Co-Nb-Zr amorphous soft magnetic thin-film can be prepared to have in-plane uniaxial magnetic anisotropy and low coercivity. Various methods have been reported for inducing this anisotropy in sputter-deposited amorphous thin films. Among these, magnetic field sputtering and magnetic field annealing are well-known and industrially viable techniques. Magnetic field sputtering is a deposition method that applies a static magnetic field during the sputtering process. In contrast, magnetic field annealing is a post-deposition heat treatment performed in a static magnetic field. While both techniques are effective in inducing low-coercivity uniaxial magnetic anisotropy in Co-Nb-Zr amorphous soft magnetic thin-films, the resulting electrical device properties differ in ways that cannot be explained solely by the difference in the anisotropy field (H k ). In this study, we reveal a distinct difference in the internal magnetic structure that arises from these two induction processes. This is accomplished by comparing the multi-resonance properties of the high-frequency permeability of Co 84.5 Nb 7.5 Zr 8 films, which possess a positive magnetostriction coefficient.
The effect of Pt substitution on the structural and magnetic properties of NiPtMnGa alloys was investigated using ab-initio calculations. For ordered systems, the FM structure was found to be the most stable among competing magnetic ones. However, the calculated magnetic moment of 4.13 mu B was significantly overestimated compared with the experimental value of 2.2 mu B. This spin rearrangement was unable to reproduce the experimental magnetic moment. To solve this problem, the effect of disorder was also studied. Five magnetic configurations, namely Ferromagnetic (FM), Antiferromagnetic (AFM-1), Antiferromagnetic (AFM-2), Ferrimagnetic (FiM) and Anti-site ferrimagnetic (AS) phases, were investigated and compared. The FM phase remained most stable with an overestimated magnetic moment of the order of 4.174 mu B. However, FiM and AS phases were found to accurately reproduce the experimental magnetic moment value. Calculations show that FiM is better suited for the NiPtMnGa alloy compared to the AS phase, exhibiting a more stable equilibrium energy and a magnetic moment of 2.068 mu B.
Two-dimensional (2D) materials exhibit unique electronic and structural properties, but accurately predicting these characteristics remains challenging due to complex feature interactions and computational constraints. This paper proposes a Prediction of Electronic and Structural Properties in 2D Materials employing Spiking Deep Residual Network (PESP-2D-SDRN). Initially, Input data is sourced from the 2DMatPedia dataset and preprocessed using the Multivariate Fast Iterative Filter (M-FIF), which effectively removes noise. Relevant features from preprocessed data are then selected using the Oscillating Spider Monkey Optimization Algorithm (OSMO), enhancing the model’s focus on informative inputs. The selected features are given to the Spiking Deep Residual Network (SDRN) for precise property prediction across diverse material classes, including semiconducting, metallic, magnetic, insulating and topological systems. Implemented in MATLAB, the proposed method demonstrates superior performance, achieving 98.5% precision and 99.4% accuracy. These results confirm that PESP-2D-SDRN offers a robust and computationally efficient solution for high-dimensional material property prediction.
By taking into account both Zeeman interaction (ZI) and spin-orbit coupling (SOC), we theoretically explore dwell time for electrons in a single ferromagnetic-stripe device (SFSD), which can be experimentally fabricated by depositing a nanowide ferromagnetic stripe on the top of the GaAs/AlxGa1-x As heterostructure. When only ZI is involved, the dwell time of electrons is independent of the spins owing to an intrinsic symmetry in the SFSD device. However, the symmetry is broken by SOCs, thereby leading to spin-dependent dwell time in the SFSD device. This allows for the separation of electron spins in the time dimension and the generation of the spin polarization effect in semiconductors. Spin polarization ratio can be tuned by interfacial confining electric-field or strain engineering, contributing to the SOC-dependent effective potential experienced by electrons in the SFSD device. These findings not only deepen the understanding of the mechanism of spin separation in time domain, but also provide an SFSD-based excellent temporal electron-spin splitter for semiconductor spintronics device applications.
Using first-principles calculations with the HSE06 hybrid functional, we systematically investigate the structural, electronic and magnetic properties of 2D MOFs based on four transition metals (Co, Ni, Cu, Zn) with hexaaminobenzene (HAB) linkers. All four MOFs are thermodynamically stable. Notably, they exhibit distinct magnetic ground states: Co-3(HAB)(2), Cu-3(HAB)(2) and Zn-3(HAB)(2) are ferrimagnetic, while Ni-3(HAB)(2) is ferromagnetic. Their electronic structures also differ significantly. Co-3(HAB)(2) is a bipolar magnetic semiconductor (BMS), Ni-3(HAB)(2) is a half-metallic ferromagnet (HMF) with 100% spin polarization, Cu-3(HAB)(2) is a half-semiconductor (HSC) and Zn-3(HAB)(2) is a unipolar magnetic semiconductor (UMS). These findings demonstrate that the magnetic and electronic properties of 2D MOFs can be effectively tuned by selecting appropriate transition-metal centers.
A Co-Nb-Zr amorphous soft magnetic thin-film can be prepared with in-plane uniaxial magnetic anisotropy and low coercivity. Various methods have been reported for inducing this anisotropy in sputter-deposited amorphous thin films. Among these, magnetic field sputtering and magnetic field annealing are well-known and industrially viable techniques. Magnetic field sputtering is a deposition method that applies a static magnetic field during the sputtering process. In contrast, magnetic field annealing is a post-deposition heat treatment performed in a static magnetic field. While both techniques are effective in inducing low-coercivity uniaxial magnetic anisotropy in Co-Nb-Zr amorphous soft magnetic thin-films, the resulting electrical device properties differ in ways that cannot be explained solely by the difference in the anisotropy field (Hk). In this study, we reveal a distinct difference in the internal magnetic structure that arises from these two induction processes. This is accomplished by comparing the multi-resonance properties of the high-frequency permeability of Co84.5Nb7.5Zr8 films, which possess a positive magnetostriction coefficient.
In this work, we investigate the spin dependence of the magnetic susceptibility of the simple cubic lattice by using the Kaneyoshi theory (or effective field theory). We find that there is a strong relationship between the magnetic susceptibility, magnetoresistance and magnetoconductance. Our results are in good agreement with the experimental magnetoresistance results of G. Binasch et al., [Phys. Rev. B 39, 4828 (1989)] and M. N. Baibich et al., [Phys. Rev. Lett. 61, 2472 (1988)]. Therefore, we suggest that the absolute values of spin dependence of the susceptibility, resistivity and conductivity are the same versus external magnetic field.
This study investigates the thermoelectric (TE) performance of asymmetric resonant-tunneling magnetic tunnel junctions (A-RT-MTJs) incorporating an ultra-wide-bandgap beta-Ga2O3 semiconductor and dissimilar ferromagnetic electrodes (CoFeB and La0.7Sr0.3MnO3). Using a tight-binding model combined with the nonequilibrium Green's function (NEGF) method, we analyze spin-dependent quantum transport under thermal gradients. The asymmetric design introduces sharp resonant-tunneling states within beta-Ga2O3 layer, enabling energy-selective spin transport and enhanced spin filtering. Compared to single-barrier MTJs and symmetric RT-MTJs, A-RT-MTJs exhibit improvements in TE properties due to amplified energy filtering and suppressed thermal conductivity. These results demonstrate that A-RT-MTJs with tailored resonant states and material asymmetry offer a promising pathway for high-efficiency thermal-to-spin energy conversion, advancing applications in spincaloritronic devices.
Multiferroic GaFeO 3 powders were synthesized by the solid-state method. X-ray diffraction results show that GaFeO 3 crystallizes in an orthorhombic structure with a Pc21n space group. The lattice parameters were determined by Reitveld rafinement to be [Formula: see text] Å, [Formula: see text] Å and [Formula: see text] Å. According to magnetic measurements, the sample displays a ferrimagnetic transition at [Formula: see text] [Formula: see text]K. The experimental calculation of the effective moment [Formula: see text] for [Formula: see text] ions in the compound GaFeO 3 was performed through a linear fitting of the inverse susceptibility [Formula: see text] at temperatures above [Formula: see text]. This analysis yields an effective moment value of [Formula: see text], which closely aligns with the theoretically derived value [Formula: see text]. Magnetization data of GaFeO 3 were analyzed using two-sublattices of the two types of Fe occupying sites 1 and 2 using mean-field theory (MFT) and the molecular field coefficients [Formula: see text], [Formula: see text] and [Formula: see text] were derived. The MFT has been used to determine the temperature dependence of the magnetization of the two-sublattices magnetization. Spin-wave theory has enabled us to model separately the temperature dependence of Fe1 and Fe2 magnetization at low temperatures. This has enabled the determination of several key magnetic parameters, including spin-wave rigidity and the interatomic distance denoted by [Formula: see text]. Near the Curie temperature, both magnetization and coercivity adhere to a statistical law supported by the Heisenberg model.
Cloud computing has become indispensable for modern digital services in healthcare, finance and education, yet its distributed and multi-tenant nature exposes it to increasingly sophisticated cyberattacks. With the anticipated integration of quantum computing into cloud infrastructures, the need for robust, privacy-preserving and fault-tolerant security mechanisms is greater than ever. Traditional threat detection models, including Convolutional Neural Networks, Support Vector Machines and Autoencoders, rely on raw or partially anonymized data, which risks user privacy and lacks the ability to effectively capture sequential dependencies in dynamic cloud traffic. To address these limitations, we propose a Hybrid BiLSTM-Attention and Homomorphic Encryption Framework for intrusion detection in cloud environments. The BiLSTM component extracts bidirectional temporal dependencies from encrypted traffic, while the attention mechanism highlights critical time steps to improve detection accuracy. Homomorphic Encryption ensures sensitive data remains encrypted throughout the detection pipeline, supporting privacy without sacrificing computational performance. Experimental results on a benchmark intrusion detection dataset demonstrate superior performance, achieving 99.28% accuracy, 99.26% precision, 99.89% recall and a 99.5% F1-score, along with a low false-negative rate (0.1%) and high AUC (0.9847). Training (1.2 s) and prediction (0.2 s) times confirm the framework's suitability for real-time deployment in privacy-critical applications. Importantly, the proposed system embodies principles of fault tolerance by maintaining resilience against adversarial interference and data leakage, a requirement that closely parallels the reliability demands of emerging quantum-classical hybrid systems. This synergy between deep learning, encryption and fault tolerance provides a pathway toward secure and privacy-preserving cloud infrastructures in the quantum computing era.
By using the series expansion of exponentials for the spin matrices, the antiferromagnetic spin-1 XYZ model with Dzyaloshinskii–Moriya Interaction (DMI) is investigated in the Mean-Field Approximation (MFA). The Hamiltonian includes the bilinear interaction parameters J, the external magnetic field H, and the DMI parameter ([Formula: see text]) in three-dimensional component form. For the coordination numbers of four, their effects are taken into account for the sublattice magnetization components. In order to compute the phase diagrams on the ([Formula: see text]) and ([Formula: see text]) planes, the temperature variations of magnetizations are thoroughly investigated. Ferromagnetic (FM), Antiferromagnetic (AFM) and random or oscillatory phase regions (R) are found in the model. Only when DMI is disabled does the AFM phase appear. Additionally, it is discovered that the R and AFM phases either only exhibit second-order phase transitions or are indistinguishable due to the erratic behaviors displayed by the magnetizations.
This study investigates the dielectric behavior and phase transitions of a Graphdiyne ferrielectric nanolattice using Monte Carlo simulations. The model explores how exchange coupling interactions, the crystal field and an external electric field affect the blocking temperature ([Formula: see text], which marks the transition between ferrielectric and superparaelectric phases. The main novelty lies in revealing how these parameters can be tuned to predict and control dielectric stability in 2D materials. The results show an almost linear increase in [Formula: see text] with stronger coupling and external field, while the crystal field exhibits a non-monotonic effect. These predictive insights support future experimental work and the design of next-generation dielectric-based nanoelectronic and energy storage devices.
