Accepted
Abstract +
Chiral magnons are collective spin excitations whose dispersions break momentum inversion symmetry, $\omega(\boldsymbol{k}) \neq \omega(-\boldsymbol{k})$, leading to intrinsically nonreciprocal spin-wave propagation. This built-in directionality offers new opportunities for spin information transfer, thermal-spin interconversion, and low-dissipation nonreciprocal microwave devices, in a manner complementary to but distinct from topological magnonics. This review develops a unified framework for chiral magnons, covering symmetry-breaking mechanisms, material realizations, transport responses and many-body non-Hermitian dynamics, and evaluates routes toward room-temperature, device-relevant platforms. The discussion is based on symmetry analysis, model Hamiltonians and spin-wave theory, in combination with first-principles calculations and recent spectroscopic and transport measurements. The microscopic origins of chiral magnons are organized into three interrelated aspects, spin-orbit coupling (SOC)-driven Dzyaloshinskii-Moriya interactions (DMI) in non-centrosymmetric magnets and interfaces, altermagnetism in the weak SOC regime without DMI, and the spin space group (SSG) framework. On this basis, representative materials such as CrSb, α-MnTe, RuO2 and MnF2 are compared in terms of energy scales, coherence, momentum anisotropy and experimental visibility, clarifying how magnon splittings and lifetimes are reflected in direction-dependent spin Seebeck, spin Nernst and thermal Hall signals. The review further summarizes bulk-gap and Berry-curvature induced chiral edge states, enhancement of nonreciprocity via chiral spin pumping and cavity-magnon hybrids, and non-Hermitian features arising from multiparticle damping and gain-loss competition. Furthermore, remaining challenges, such as the stability of physical properties at room temperature, quantitative calibration of spectral and transport properties, as well as many-body competition also outlined. Finally, the possible strategies based on SSG-guided materials screening, multi-modal metrology and geometry phase engineering toward efficient spin logic, THz isolators and quantum routing based on chiral magnons also proposed.
, , Received Date: 2025-09-15
Abstract +
, , Received Date: 2025-09-02
Abstract +
In recent years, topological valley physics with the degrees of freedom of valley pseudospin has attracted great attention. The topological valley boundary states in phononic crystals have important application prospects in efficient guidance and sensing for acoustic and elastic wave due to their unique transmission characteristics with backscattering immunity. However, the coupling effect of the valley edge states in multi-layer topological heterostructure is still a challenge in the elastic system due to the complicated multi-mode polarization of elastic waves. In this work, a valley topological phononic crystal plate with a multi-layer heterostructure is constructed to explore the multi-mode interference characteristics of the valley edge states based on the analogy of elastic wave quantum valley Hall effect. The coupling behavior of valley edge states for the out-of-plane polarized elastic wave in multi-layer topological heterostructure is systematically studied. By adjusting the layer numbers of the topological heterostructures, the formation mechanism and regulation law of coupled valley edge states for elastic wave in finite size multi-layer heterogeneous structures are revealed. Furthermore, through topological transmission calculations, the multi-mode interference effect of coupled valley edge states for elastic wave is achieved and its transmission robustness is well verified. Finally, as an application example, an elastic topological wavelength demultiplexing device is designed based on the multi-mode interference effect of valley edge state. By utilizing the difference in coupling wavelengths of elastic valley edge states at different coupling frequencies, directional separation of incident elastic waves in defect resistant channels is achieved, which can be used as a prototype model for the novel application of elastic wavelength demultiplex device. This work provides a new paradigm for the manipulation of elastic wave topological transport, which is also expected to promote the practical design of new multifunctional elastic wave coupling and sensing devices.
,
Abstract +
, , Received Date: 2025-09-05
Abstract +
Phase change fibers, as an advanced functional material for human body thermal management, have significant potential for practical applications. However, current research systems face critical limitations: traditional phase change fibers prepared via wet spinning and electrospun phase change fiber films encounter insufficient thermal insulation due to their structural compactness deficiencies, thereby failing to effectively prevent body heat loss in cold environments. To tackle this technical challenge, this work breaks through traditional material system limitations by innovatively employing electrospinning technology to integrate polyethylene glycol (PEG) into polyacrylonitrile (PAN) fiber systems. We successfully fabricate fluffy-tructured phase change fibers that integrate both phase change thermoregulation and thermal insulation functions using the principle of non-solvent-induced phase separation. The internal porous structure of the fluffy fibers constructs an effective cold protection layer, exhibiting an ultra-low thermal conductivity of 0.0395 W/m·K. At the same time, the PEG phase change componentprovides a high latent heat of 80.6 J/g, achieving a synergistic effect of temperature regulation and thermal insulation. The material exhibits excellent structural and thermal stability: maintaining stable phase change performance after 500 thermal cycles and exhibiting exceptional thermal reliability up to 300 ℃. Even above the phase change melting point, the material effectively prevents leakage of the phase change component. Furthermore, it possesses sufficient mechanical properties to withstand various deformations such as bending, compression (668.7 Pa), and stretching (253.5 kPa) without structural collapse. Practical application evaluations further demonstrate that the material’s cold protection performance significantly exceeds that of natural cotton. This study not only provides an innovative strategy for fabricating integrated “heat storage-thermal insulation” fibers, but also conceptually expands the design dimensions of phase change fibers in thermal management, offering important solutions and theoretical guidance for developing high performance wearable cold-protection materials.
, , Received Date: 2025-10-09
Abstract +
Ferroelectric thin films and their device applications have drawn wide attentions since the 1990s. However, due to the critical size effect, ferroelectric thin films cannot maintain their ferroelectric properties as their thickness decreases to the nanometer size or one atomic layer, posing a significant challenge to the development of related nano-electronic devices. With a naturally stable layered structure, two-dimensional materials possess many advantages such as high-quality and smooth interface without dangling bonds, no interlayer interface defects, and the ability to maintain complete physical and chemical properties even at limited atomic thickness. Thus, it is gradually realized that two-dimensional materials are a good hotbed for the two-dimensional ferroelectricity. CuInP2S6, α-In2Se3, WTe2, and other intrinsic ferroelectric 2D materials have been reported successively while artificially stacked sliding ferroelectrics such as t-BN have also emerged, which expands the types of 2D ferroelectric materials and opens a new avenue for the further miniaturization and flexibility of ferroelectric electronic devices. This article reviews the recent research progress of two-dimensional ferroelectric materials, discusses their compositional characteristics, structural features and property modulation, and also prospects their application potential and future research hotspots.
, , Received Date: 2025-11-09
Abstract +
The mass of the atomic nucleus, as one of the fundamental physical quantities of the atomic nucleus, plays an important role in understanding and researching the structure of the atomic nucleus and nuclear reactions, the basic interactions between nucleons. However, accurately predicting the mass of nuclei far from the β stability line remains a huge challenge. Based on the machine-learning-refined mass model, the newly measured atomic nucleus masses since 2022, the residual proton-neutron interaction ($\delta V_{pn}$), and the α-decay energy of heavy nucleus are studied. It is found that: (1) For the 23 newly measured atomic nuclei, the root mean square deviations obtained by the machine-learning-refined mass models are between 0.51 and 0.58 MeV, which are significantly lower than the 3.275, 1.058, 0.752, and 0.785 MeV given by the liquid droplet model (LDM), Weizsäcker-Skyrme-4 (WS4), finite-range droplet model (FRDM), and Duflo-Zucker (DZ), respectively. (2) The $\delta V_{pn}$ of the atomic nucleus with N = Z obtained from machine-learning-refined mass models is consistent with the latest experimental data. (3) The root mean square deviations of the α-decay energy of heavy nuclei obtained from the machine-learning-refined mass models have also been significantly reduced. Furthermore, by using the Bayesian model average approach to consider the results of different machine-learning-refined mass models, a more accurate prediction can be obtained. These results demonstrate that the machine-learning-refined mass models possess good extrapolation capabilities and can provide useful insight for further researches. The datasets presented in this paper, are openly available at https://doi.org/10.57760/sciencedb.j00213.00246 .
, , Received Date: 2025-09-22
Abstract +
In recent years, two-dimensional (2D) ferroelectric materials have attracted widespread interest due to their ultrathin geometry, high stability, and switchable polarization states. Ferroelectric tunnel junctions (FTJs) made from 2D ferroelectric materials exhibit exceptionally high tunnel electroresistance (TER) ratios, making them leading candidates for next-generation non-volatile memory and logic devices. However, advancing FTJ technology depends on overcoming the critical challenge of precisely controlling quantum tunneling resistance. Therefore, this study proposes a strategy of interfacial work function engineering, which actively modulates the band alignment of a heterostructure through ferroelectric polarization switching, induces a reversible metal-insulator transition in the barrier layer, and modulates TER. Using a van der Waals heterostructure composed of Al2Te3/In2Se3 as a model system, we demonstrate through first-principles calculations that the strategic manipulation of interfacial work functions can induce a reversible metal-insulator transition in the barrier, thereby drastically changing the tunneling conductance. Further analysis indicates that a work function mismatch between the two ferroelectric materials causes varying degrees of interfacial charge transfer, thereby triggering a metal-insulator transition in the van der Waals ferroelectric heterostructure as the external electric field is reversed. Non-equilibrium transport simulations reveal an unprecedented TER ratio of 2.69×105%. Our findings not only highlight Al2Te3/In2Se3 as a promising platform for high-performance FTJs but also establish a universal design strategy for engineering ultrahigh TER effects in low-dimensional ferroelectric memory devices. This work opens new avenues for developing energy-efficient, non-volatile memory with enhanced scalability and switching characteristics.
, , Received Date: 2025-09-21
Abstract +
,
Abstract +
Tunneling Magnetoresistance (TMR) sensors have emerged as a leading technology in high-performance magnetic sensing, distinguished by their high sensitivity, low power consumption, and miniaturization. To address the evolving demands of cutting-edge applications like biomagnetic imaging and smart grid monitoring, continuous performance enhancement is crucial. This review systematically outlines the key strategies for optimizing TMR sensors, focusing on thin-film material engineering and sensitive microstructure design. Material advancements are dissected along two paths: developing high-sensitivity systems via MgO barriers and composite free layers, and creating wide-linear-range systems through anisotropy engineering, including both perpendicular (PMA) and in-plane (IMA) configurations, as well as dynamic methods like electric-field and strain modulation. Structurally, we highlight innovations such as vortex-state MTJs and magnetic flux concentrators to enhance linearity and sensitivity, alongside advanced noise modulation techniques that effectively suppress low-frequency 1/f noise. The practical impact of these optimizations is evidenced by TMR sensors now capable of measuring magnetocardiograms (MCG) outside shielded environments and providing high-accuracy current sensing in smart grids. Future development is directed towards novel material systems that balance high sensitivity with a wide linear range, the realization of monolithic three-axis vector sensors, and the deep integration of TMR technology with artificial intelligence for smart sensing systems. This work provides a comprehensive reference for advancing TMR sensor technology and its applications in high-precision magnetic field detection.
,
Abstract +
Borohydrides (XBH4, X = Li, Na, K) exhibit an ”elemental synergy” effect, characterized by the high neutron absorption cross-section of boron and the excellent moderation capability of hydrogen, making them promising candidates for neutron shielding materials. However, the current lack of experimental and evaluated thermal scattering data for borohydrides in international nuclear data libraries hinders the accurate assessment of their shielding and moderation performance.In this study, material properties including lattice parameters, electronic structures, and phonon densities of states were calculated based on first-principles density functional theory. Subsequently, the corresponding S(α, β) data and thermal neutron scattering cross-sections were developed. The simulated lattice parameters show good agreement with experimental data. By comparing the electronic structures and phonon densities of states of XBH4, the coherent elastic, incoherent elastic, and inelastic scattering cross-sections for the cations X, B, and H were obtained. The results indicate that the thermal neutron cross-sections of the constituent nuclides in XBH4 exhibit significant differences depending on the cation X.To evaluate the impact of thermal scattering data on neutron shielding effects, a simplified fusion source model was employed using the OpenMC code to compare the leaked neutron energy spectra under different physical models. The results demonstrate that the Free Gas Model (FGM) provides an inaccurate description of neutron moderation due to its neglect of lattice binding effects. Furthermore, owing to the large incoherent scattering cross-section of hydrogen, the coherent elastic scattering cross-sections of the various nuclides have a negligible impact on the neutron energy spectrum. This research fills the gap in thermal neutron cross-section data for borohydrides and establishes a foundation for further investigations into their application as neutron shielding materials. These findings partially fill the gap in thermal neutron cross-section data for borohydrides and lay a foundation for their future application as neutron shielding materials.The datasets presented in this paper, including the ScienceDB, are openly available at https://www.doi.org/10.57760/sciencedb.j00213.00219(Please use the private access link https://www.scidb.cn/s/3meuq2).
,
Abstract +
Based on the Gradient Boosting Decision Tree (GBDT) machine learning algorithm, this study develops a model for predicting the fusion reaction cross-section (CS) of 99-103Mo*, aiming to explore the optimal synthesis pathway for the medical isotope 99Mo. The model inputs include characteristic quantities such as reaction energy, proton number, mass number, and binding energy, as well as relevant parameters calculated based on phenomenological theoretical models, with the output being the fusion reaction cross-section. It is found that the mean absolute error (MAE) between the machine learning-predicted CS and experimental values on the test set is 0.0615, which is superior to the 0.1103 predicted by the EBD2 model. On this basis, combined with the GEMINI++ program, the survival probabilities of the neutron decay channels for 99-103Mo* were calculated to derive the evaporation residue cross-section of 99Mo. It is found that the evaporation residue cross-section of the 2n de-excitation channel for 4He+97Zr at a center-of-mass energy of 18.51 MeV is 1199.80 mb, making it the optimal pathway for synthesizing 99Mo. This research validates the reliability of physics-informed machine learning methods in predicting fusion reaction cross-sections and provides a reference for optimizing reaction system selection and producing medical isotopes through fusion reactions in heavy-ion accelerators.
,
Abstract +
The interaction of nanosecond laser pulses with metallic materials involves multiple complex physical processes, and constructing a self-consistent model capable of uniformly describing all stages remains a significant challenge. This work establishes a multi-physics coupled model for pure iron, encompassing laser energy deposition, solid-liquid phase transition, gas-liquid interfacial kinetic transport, plasma expansion and ionization, and spectral radiation. The numerical solution employs a partitioned approach, utilizing an implicit compact difference scheme for the target region and a Mac-Cormack explicit scheme for the ambient atmosphere, to simulate the ablation dynamics.
The simulations elucidate the emergence of plasma shielding and its inhibitory effect on the evaporation process. They confirm that the early-stage ablation products are primarily transported via a supersonic expansion mode, which accounts for 81.6% of the total ablated mass transfer. The model successfully captures the complete evolution of the plasma plume from a high-temperature, highly ionized state (dominated by Fe3+) to a low-temperature, neutral atomic state (dominated by Fe0). Based on this, spectral calculations demonstrate the dynamic evolution of radiative characteristics from an early stage featuring a “strong continuum background dominated by ion lines” to a later stage where “the continuum attenuates, atomic lines become prominent, and self-absorption appears”. The emergence of self-absorption proves the model’s capability to effectively capture the optical thickness effects arising from spatial inhomogeneity within the plasma.
Through systematic comparison with experimentally measured spectra and calculated results from the PrismSPECT and NIST LIBS spectral programs, the model presented here achieved the highest comprehensive scores in quantitative evaluations across multiple channels. This validates the necessity and superiority of the full-chain self-consistent modeling approach over traditional methods relying on spatial averaging or the optically thin approximation, particularly in describing plasma inhomogeneity and radiation transport. It also provides a numerical simulation framework for applications such as laser processing parameter optimization, quantitative spectroscopic analysis, and the design of novel plasma light sources.
The simulations elucidate the emergence of plasma shielding and its inhibitory effect on the evaporation process. They confirm that the early-stage ablation products are primarily transported via a supersonic expansion mode, which accounts for 81.6% of the total ablated mass transfer. The model successfully captures the complete evolution of the plasma plume from a high-temperature, highly ionized state (dominated by Fe3+) to a low-temperature, neutral atomic state (dominated by Fe0). Based on this, spectral calculations demonstrate the dynamic evolution of radiative characteristics from an early stage featuring a “strong continuum background dominated by ion lines” to a later stage where “the continuum attenuates, atomic lines become prominent, and self-absorption appears”. The emergence of self-absorption proves the model’s capability to effectively capture the optical thickness effects arising from spatial inhomogeneity within the plasma.
Through systematic comparison with experimentally measured spectra and calculated results from the PrismSPECT and NIST LIBS spectral programs, the model presented here achieved the highest comprehensive scores in quantitative evaluations across multiple channels. This validates the necessity and superiority of the full-chain self-consistent modeling approach over traditional methods relying on spatial averaging or the optically thin approximation, particularly in describing plasma inhomogeneity and radiation transport. It also provides a numerical simulation framework for applications such as laser processing parameter optimization, quantitative spectroscopic analysis, and the design of novel plasma light sources.
, , Received Date: 2025-09-04
Abstract +
, , Received Date: 2025-12-29
Abstract +
- 1
- 2
- 3
- 4
- 5
- ...
- 18
- 19
