The European Physical Journal Plus最新文献

We performed Monte Carlo simulations to explore the behaviors of the microscopically fourfold magnetocrystalline anisotropy and macroscopically Néel temperature (T_N) of an antiferromagnetic IrMn layer as well as the exchange bias blocking temperature (T_B) in CoFeB/IrMn bilayers under combined in-plane biaxial and out-of-plane uniaxial strains. We demonstrate that the fourfold symmetric anisotropy remains robust, with both its strength and easy-axis orientation being tunable. The exchange coupling constants between Mn–Mn pairs exhibit long-range characteristics. Through precise strain control, T_N can be significantly enhanced from 510 to 1346 K, and T_B can be increased from 420 to 1050 K. Additionally, these strains can diminish or even completely eliminate exchange bias and coercivity. This study elucidates the mechanisms underlying microscopic magnetism, T_N, and T_B via strain control, while also proposing a promising strategy for utilizing multi-dimensional strain engineering to advance the practical applications of room-temperature or high-temperature exchange-bias-based spintronic devices.

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We investigate the collider phenomenology of the standard Hierarchical VEVs Model by proposing a new version, which avoids large flavor-changing neutral current interactions, thus rendering the scale of new physics as low as the electroweak scale. The resulting collider signatures are distinctive and testable at the High-Luminosity LHC, the High-Energy LHC, and future 100 TeV hadron colliders. Remarkably, one of the pseudoscalars in the model can account for the 95.4 GeV di-photon excess observed by ATLAS and CMS. In addition, the model naturally accommodates a new class of neutrino-philic dark matter candidate, neutrinic dark matter, that interacts exclusively with neutrino pairs.

We show that an ansatz for (1+3+n) dimensional static spacetime with spherical symmetry in three dimensions and Euclidean symmetry in n dimensions, parametrized by only one function of radial coordinate, leads to a limited set of vacuum solutions of the Einstein field equations. They can also be identified as Weyl solutions. We investigate properties of these spacetimes through the Kretschmann scalar, Newtonian mass defined through the Newtonian limit, Komar mass, Einstein, Landau–Lifshitz, and ADM mass. In addition to (1+3+n) dimensional Minkowski spacetime, there are two classes of solutions. The first class is a trivial product of the Schwarzschild spacetime and Euclidean spaces in extra dimensions, while the second class is non-trivial. In the case with no horizon, there is a naked singularity, all masses are equal, and they are negative. In the case when there is a horizon, this horizon accommodates a physical singularity, which corresponds to Kaluza–Klein bubbles featuring exotic properties. Einstein, Landau–Lifshitz, and ADM masses are positive, while Newtonian and Komar masses are negative. This differentiates these solutions from trivial higher-dimensional extensions of the Schwarzschild solution.

Copper is a prime candidate for fusion divertor heat sinks due to its superior thermal conductivity and irradiation resistance. Nevertheless, atomic-level mechanisms underlying the synergies of irradiation-induced defects and helium in copper remain poorly understood. Herein, helium-mediated irradiation damage mechanisms are investigated in copper via atomistic simulations across helium concentrations (0–8000 appm), cascade energies (1–7 keV), and temperatures (100–900 K). Results show that helium reduces the threshold displacement energy and forms He_nV_k clusters that suppress Frenkel pair recombination, yielding a characteristic double-peak defect evolution with elevated secondary peaks in helium-doped systems. A helium concentration of 4000 appm optimizes He_nV_k formation before competitive trapping reduces cluster efficacy at 6000 appm. Cascade energy dominates defect dynamics, extending cascade duration and increasing displacement peak amplitudes linearly with energy while inducing minor stress-field-driven peaks. Elevated temperatures amplify defect production and helium diffusion, widening the divergence between pure and helium-doped systems. Notably, 500 K disrupts standard clustering behavior due to He_nV_k formation energy variations. Residual defect populations scale with operational parameters. These findings provide critical insights for radiation-resistant copper alloy design in fusion environments.

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The structural, mechanical, electronic, and optical properties of novel two-dimensional material–lead tetrafluoride (2D PbF₄) are systematically investigated using first-principles calculations. The results indicate that 2D PbF₄ features distorted PbF₆ octahedra structure with tetragonal P4/mmm space group symmetry. Density functional perturbation theory (DFPT) and ab-initio molecular dynamics (AIMD) simulations confirmed its dynamic and thermodynamic stability. Mechanical property calculations indicate that its Young’s modulus and Shear modulus display strong anisotropy, and a Poisson’s ratio of 0.87 along the [110] direction is obtained. Electronic band structure calculations revealed an indirect semiconductor nature with varying bandgaps (3.01 eV by SCAN, 4.73 eV by HSE06, 10.01 eV by GW₀), reflecting robust quasiparticle interactions in 2D PbF₄. Bethe–Salpeter equation methods combined with GW₀ calculations found 2D PbF₄ has a large exciton binding energy (2.8 eV), higher than that of traditional 2D materials, endowing excitonic devices better thermal tolerance, light absorption/emission efficiency, and photodetection sensitivity. Additionally, due to enhanced nonlinear optical properties from strong electron–hole interactions, great promise was shown for optical communication and computing.

This work theoretically designs the g-C(_{3})N(_{4}) nanoribbons (CNNRs) with different widths, by cutting graphitic carbon nitride (g-C(_{3})N(_{4})) in a specific direction. And then, spin-dependent transport features are investigated in the molecular magnetic tunnel junctions (MMTJs) formed by the serially coupling between CNNRs and two zigzag graphene nanoribbons, with the help of density functional theory (DFT) and nonequilibrium Green’s function approach. The calculated results show that such MMTJs display special transport behaviors, including the notable spin-filtering effects, abnormal magnetoresistance, and negative differential resistance. Moreover, altering the spin configurations generates two distinct net spin currents, and the tunneling magnetoresistance magnitude may approach its maximum order of (10^{4}%) under the appropriate conditions. We thus believe that these findings propose g-C(_{3})N(_{4})-based materials to be promising MMTJs well suited for the utilization in future spintronic devices.

Biometric authentication systems are increasingly adopted in critical domains such as smart healthcare, IoT, and finance, where robust, privacy-preserving, and inclusive identity verification is essential. While multimodal, cross-modal, and sequential biometric fusion techniques have significantly improved authentication accuracy and resilience, their effectiveness is often constrained by data scarcity, demographic bias, and privacy regulations. This paper presents a comprehensive review of synthetic data augmentation approaches enabled by generative models such as GANs, diffusion models, and simulation-based frameworks and examines their role in advancing biometric fusion systems. We introduce a systematic taxonomy of fusion strategies and synthetic data generation paradigms, and critically analyze how existing synthetic augmentation techniques enhance fusion performance across diverse scenarios, including modality alignment, adversarial robustness, and adaptive authentication. Furthermore, we identify key limitations in current literature, such as domain mismatch, underexplored biometric modalities, and ethical considerations, and outline future research directions for developing scalable, fair, and secure biometric authentication systems. By consolidating recent advances at the intersection of generative AI and biometric fusion, this review provides a structured foundation for future research and real-world deployment.

With the growing demand for information security, the need for protecting both images and audio continues to increase. While several multimedia encryption schemes have been proposed, their ability to simultaneously handle both data types with high efficiency and security remains limited, largely due to the distinct structural characteristics of images (spatial correlations) and audio (temporal correlations). This study introduces an integrated solution inspired by the structure of gift box ribbons. We propose a multi-image and audio-compatible encryption algorithm based on a hyperchaotic memristive map and cross-cube confusion. First, images and audio signals were vectorized and fused into three-dimensional cubes, enabling their simultaneous encryption within a unified spatial structure. Next, point-to-point confusion was applied to the entire cube, followed by block-wise confusion, where the specific confusion method was dynamically selected by random sequences. Finally, modular diffusion was performed to obtain the ciphertext, effectively randomizing all data values. Performance tests and security analyses confirmed that all evaluation metrics met the required standards while offering advantages in robustness and encryption speed. This algorithm provides a novel and practical approach for integrated multimedia encryption.

Most of previously protocols for remote state preparation via nonmaximally entangled state are probabilistic where the parameters of the entangled state are given to the receiver who accomplishes the task probabilistic by introducing the auxiliary qubits and performing unitary operation according to his knowledge of the entangled state. In this paper, we construct a partially entangled state and present a protocol for multiparty hierarchical controlled remote implementation of quantum operation (RIO) where the receivers have different authorities to prepare the desired state via the partially entangled state. Different from the previously protocols, the parameters of the quantum state are given to the high-grade agent. The unit success probability can be achieved via the partially entangled state since the high-grade agent can perform some proper rotation operations on his entangled qubit according to his knowledge of the parameters. The protocol requires the parties of the communication neither to have the maximally entangled state nor to implement nonlocal operations, which makes the scheme more convenient to applications than others. Moreover, the protocol for hierarchical controlled remote implementation of partially unknown operation is discussed.

Induced radioactivity is an inherent consequence of proton therapy (PT), arising from nuclear interactions of high-energy proton beams and their secondary neutrons with facility materials. This review synthesizes current knowledge on the mechanisms, measurement, and mitigation of residual radioactivity in PT facilities. Key activation pathways include proton-induced reactions and secondary neutron capture, producing radionuclides with half-lives from seconds to several years, with the majority of radiological concern in the range of minutes to years. These isotopes can pose radiation exposure risks to maintenance staff, particularly in activated components such as brass apertures, steel assemblies, and concrete shielding. Measurement techniques include gamma spectrometry, activation foils, and Monte Carlo simulations (e.g., FLUKA, GEANT4), although uncertainties in reaction cross sections and material composition can limit the accuracy of predictions, especially for long-lived species. Mitigation strategies encompass material selection with low-activation alloys and concretes, adoption of pencil-beam scanning to minimize component irradiation, engineering controls such as modular shielding, ventilation for airborne radionuclides, and remote handling, as well as administrative protocols including cooldown periods and decay storage. Proactive management through evidence-based design and ALARA-compliant monitoring ensures regulatory compliance and sustains PT as a safe treatment modality. Continued improvement in nuclear data and shielding materials will enhance predictive capability and support further reduction of residual doses in future facilities.