Accepted
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Abstract +
As a core component of modern optoelectronic systems, photodetectors play an indispensable role in optical communications, environmental monitoring, medical imaging, and military detection. With the rapid development of related technologies, the development of novel photodetector materials featuring high sensitivity, fast response, and excellent stability has become a key research focus. Among various candidate materials, A₂BX₆-type vacancy-ordered double perovskites have attracted significant attention due to their unique crystal structures and outstanding optoelectronic properties. These materials not only possess tunable bandgap structures and high carrier mobility but also demonstrate excellent environmental stability, showing broad application prospects in the field of photodetection.This study systematically investigated the optoelectronic response behavior of a representative lead-free double perovskite, Cs2TeCl6, under high-pressure conditions. Precise experimental observations revealed an anomalous transition in photocurrent from decrease to increase when the pressure reached 18 GPa. By employing advanced characterization techniques, including high-pressure in situ Raman spectroscopy, UV-Vis absorption spectroscopy, and synchrotron X-ray diffraction, we elucidated the underlying physical mechanism:at the critical pressure of 18 GPa, the material enters an intensified compression stage, leading to a significantly accelerated bandgap narrowing rate. This continuous reduction in bandgap effectively mitigates the weak absorption limitation of the indirect bandgap, enabling efficient absorption of previously unexcitable low-energy photons and ultimately resulting in enhanced photocurrent.This discovery not only clarifies the intrinsic relationship between the structure and optoelectronic properties of Cs2TeCl6 at the microscopic level but, more importantly, provides new insights for regulating the optoelectronic performance of perovskite materials through pressure engineering. The findings offer important guidance for developing novel high-performance photodetection devices and establish a valuable research methodology for optimizing other semiconductor materials. In the future, by further refining material compositions and pressure modulation strategies, the design and fabrication of more efficient and stable photodetector materials can be anticipated.
Abstract +
Recent advancements in metasurfaces indicate that achieving high efficiency requires nonlocal designs where the coupling between constituent units is fully considered. However, most metasurfaces for elastic waves are still designed as local structures based on the Generalized Snell's Law (GSL), which ignore the coupling between sub-units, often results in low efficiency. In this paper, we extend a previously proposed method based on the Multi-port Structural Model (MPSM) for acoustic metasurfaces, to design nonlocal structures for flexural wave in thin elastic plate. Using this method, we can design anomalous reflector/refractor with large diffraction angle and planar focuser with large numerical aperture for flexural waves in thin elastic plates.
As shown in Fig. A1(a), we consider an infinite free thin elastic plate with elastic cylinder pairs assembled symmetrically on both surfaces. The design target is to optimize the height of the cylinder pairs, by which anomalous reflection or refraction for flexural wave in plate can be realized. We show that, by modelling the structure as a MPSM, configurations with the desired functionalities can be efficiently determined. Through three-dimensional finite element simulations, we demonstrate that the proposed anomalous reflectors and refractors can both achieve near-unity efficiencies, even for structures with a deflection angle as large as 80°. As illustration, the field distribution of the scattering wave in two example structures under normal incidence is shown in Fig. A1(b). For the figure, the structures are designed as the 60° anomalous refractor (left panel) and reflector (right panel) under normal incidence.
By the same method, we further design a planar focuser with functionality illustrated schematically in Fig. A2(a). We show that, by optimizing the heights of each cylinder pair, the normally incident flexural wave can be focused on the incident side or the transmitting side of the metasurface with arbitrary focal length. As illustration, we show in Fig. A2(b) the focusing effect of a reflection-type and a transmission-type focuser. The illustrated structures have lateral length of 20λ0 and focal length of 2λ0. We find the focusing efficiency of our nonlocal designs is significantly higher than that of their GSL-based counterparts, particularly for structures with numerical apertures approaching unity.
This work not only introduces an effective design method for nonlocal metasurfaces for flexural waves in thin elastic plates, but also provides two highly efficient nonlocal structures with promising applications in areas such as sensing, energy harvesting, and more.
As shown in Fig. A1(a), we consider an infinite free thin elastic plate with elastic cylinder pairs assembled symmetrically on both surfaces. The design target is to optimize the height of the cylinder pairs, by which anomalous reflection or refraction for flexural wave in plate can be realized. We show that, by modelling the structure as a MPSM, configurations with the desired functionalities can be efficiently determined. Through three-dimensional finite element simulations, we demonstrate that the proposed anomalous reflectors and refractors can both achieve near-unity efficiencies, even for structures with a deflection angle as large as 80°. As illustration, the field distribution of the scattering wave in two example structures under normal incidence is shown in Fig. A1(b). For the figure, the structures are designed as the 60° anomalous refractor (left panel) and reflector (right panel) under normal incidence.
By the same method, we further design a planar focuser with functionality illustrated schematically in Fig. A2(a). We show that, by optimizing the heights of each cylinder pair, the normally incident flexural wave can be focused on the incident side or the transmitting side of the metasurface with arbitrary focal length. As illustration, we show in Fig. A2(b) the focusing effect of a reflection-type and a transmission-type focuser. The illustrated structures have lateral length of 20λ0 and focal length of 2λ0. We find the focusing efficiency of our nonlocal designs is significantly higher than that of their GSL-based counterparts, particularly for structures with numerical apertures approaching unity.
This work not only introduces an effective design method for nonlocal metasurfaces for flexural waves in thin elastic plates, but also provides two highly efficient nonlocal structures with promising applications in areas such as sensing, energy harvesting, and more.
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Abstract +
X-ray Photon Correlation Spectroscopy (XPCS) is vital for probing mesoscale material dynamics using synchrotron radiation, yet the complex influence of parameters such as light source properties, beam propagation, detector response on speckle dynamics is hard to directly observe. This study develops a Monte Carlo-based full optical path numerical model to systematically analyze these effects, aiding experimental optimization.
A simulation framework integrating Brownian dynamics, beam coherence, and detector response was constructed to replicate the entire photon emission-to-detection process. A Fraunhofer diffraction-based speckle generation algorithm reproduced speckle fluctuations via atomic position evolution and phase modulation. Feasibility was validated via Siegert relation fitting (β, γ), Γ - q2 linearity (R2=0.99904), and consistency with the Einstein-Stokes law.
Key parameter sensitivity analysis revealed:(1) Optimal aperture matching (r/σ=1) balances coherence and photon flux; (2) Mechanical vibrations with Δx/s=1500 induce periodic oscillations in g2(q, τ), masking intrinsic relaxation, as validated by a 24.658 Hz pump experiment; (3) Poisson noise and intensity fluctuations degrade low-light SNR, with Poisson noise causing discrete errors and classical noise inducing baseline shifts.
This framework clarifies how source properties, optical parameters, and noise affect results, providing guidance for XPCS optimization and a foundation for extending its applications to high-precision coherent scattering scenarios.
A simulation framework integrating Brownian dynamics, beam coherence, and detector response was constructed to replicate the entire photon emission-to-detection process. A Fraunhofer diffraction-based speckle generation algorithm reproduced speckle fluctuations via atomic position evolution and phase modulation. Feasibility was validated via Siegert relation fitting (β, γ), Γ - q2 linearity (R2=0.99904), and consistency with the Einstein-Stokes law.
Key parameter sensitivity analysis revealed:(1) Optimal aperture matching (r/σ=1) balances coherence and photon flux; (2) Mechanical vibrations with Δx/s=1500 induce periodic oscillations in g2(q, τ), masking intrinsic relaxation, as validated by a 24.658 Hz pump experiment; (3) Poisson noise and intensity fluctuations degrade low-light SNR, with Poisson noise causing discrete errors and classical noise inducing baseline shifts.
This framework clarifies how source properties, optical parameters, and noise affect results, providing guidance for XPCS optimization and a foundation for extending its applications to high-precision coherent scattering scenarios.
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Abstract +
In recent years, soft lattices have been considered a primary physical origin of defect tolerance in lead-halide perovskite materials, with bulk modulus serving as a key indicator of lattice "softness." In this work, we focus on cubic perovskites and construct a dataset of bulk moduli for 213 compounds based on DFT calculations. A total of 138 features were compiled, including 132 statistical features extracted using the Matminer toolkit and 6 manually selected elemental descriptors. Four conventional machine learning regression models (RF, SVR, KRR, and EXR) were employed for prediction, among which the SVR model showed the best performance, achieving a test-set RMSE of 7.35 GPa and R2 of 97.86%. Feature importance analysis revealed that thermodynamic-structural features such as melting point, covalent radius, and atomic volume play dominant roles in determining bulk modulus. Based on the 12 most important features, a thermodynamic-structural coupling descriptor was constructed using the SISSO method, yielding a test-set RMSE of 7.41 GPa and R2 of 97.80%. The resulting descriptor indicates that bulk modulus is proportional to melting point and inversely proportional to atomic volume. Furthermore, the VS-SISSO method was applied by incorporating a random subset selection and iterative variable screening strategy, enabling the selection of electronic-level features such as electronegativity, valence state, and number of unpaired electrons. The resulting electronic-thermodynamic-structural coupling descriptor further improved prediction accuracy, reaching an RMSE of 5.34 GPa and R2 of 98.35% on the test set. Notably, this model effectively distinguishes chalcogen-based (divalent) from halogen-based (monovalent) perovskites in terms of their bulk moduli due to differences in valence states. Based on this model, high-throughput screening was performed on over 10,000 cubic chalcogenide and halide perovskites, identifying approximately 170 lead-free candidates with bulk moduli in the range of 10-20 GPa, comparable to Pb-I perovskites. These results provide preliminary evidence supporting the applicability of the soft-lattice mechanism in lead-free systems and offer theoretical guidance and data support for the high-throughput discovery of stable, defect-tolerant, lead-free perovskite materials.The dataset for this paper is available in the (Scientific Data Bank) database https://www.scidb.cn/s/A3IBBn.
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Abstract +
The average β and γ energies data of the β——decay nuclei plays an important role in many fields of nuclear technology and scientific research, Such as the decay heat and antineutrino spectrum calculation of different kinds of reactors. However, for many nuclei, the reliable experimental measurements of their average energy are lacking, and the theoretical calculation needs to be improved to meet the accuracy requirements of the technical applications.
In this study, the average β, γ and neutrino energies of the β—decay nuclei were investigated by the neural network approach based on the newly evaluated experimental data of 543 nuclei from a total of 1136 β—decay nuclei. For the neural network approach, three different feature groups are used for model training. Each feature group contains a characteristic feature value (one of the T1/2, (1/T1/2)1/5, and 1/3Q), along with five identical feature values (Z, N, parity of Z, parity of N, and ΔZ).
The three characteristics feature values were selected based on the physical mechanism below:1. the average energy is obviously related with Q value and approximately taken as 1/3Q in the reactor industry. Hence the 1/3Q was selected as one characteristics feature value; 2. the half-live is relative with the Q value of β—decay, and T1/2 was considered; 3. considering the Sargent' s law, (1/T1/2)1/5 ∝ Q, a more accurate (1/T1/2)1/5 value were selected.
As a result, for the feature group of T1/2, the training results for all three types of average energy were unsatisfactory. For the other groups, for the average β energy data, the relative errors are 19.32% and 28.11% for(1/T1/2)1/5 and 1/3Q feature groups in the training set and 82% and 56.9% in the validation set; for the average γ energy, the relative errors were 28.9% and 76.9% for (1/T1/2)1/5 and 1/3Q feature groups and >100% and >100% in the validation set; for the average neutrino energy, the relative errors in the training set were 27.82% and 35.33% for (1/T1/2)1/5 and 1/3Q feature group and 76.32% and 37.76% in the validation set.
Considering the accuracy comparison of the three groups, 1/3Q feature group were selected to predict the average energy data of nuclei in the fission product region (mass numbers ranging from 66 to 172) for which miss reliable experimental data. As a result, we supplemented the average energy data with predicted values for 291 nuclei. Besides, a comparison were performed between the calculated data and the evaluated experimental data through the nuclide chart. It is found that the neural network provides good prediction of the experimental data for the average β and neutrino energies which exhibit relatively strong regularity. However, it shows significant deviations in predictions for average γ energy (relative error in the training set was 76.9%). Large deviation also emerges in the odd-odd nuclei and nuclei near magic numbers. This study confirms that incorporating empirical relationships and physical principles can effectively enhance the performance of the neural network, and simultaneously reveals the relationship between data regularity and model generalization capability. These findings provide a basis for future integration of physical mechanisms to optimize machine learning models.
In this study, the average β, γ and neutrino energies of the β—decay nuclei were investigated by the neural network approach based on the newly evaluated experimental data of 543 nuclei from a total of 1136 β—decay nuclei. For the neural network approach, three different feature groups are used for model training. Each feature group contains a characteristic feature value (one of the T1/2, (1/T1/2)1/5, and 1/3Q), along with five identical feature values (Z, N, parity of Z, parity of N, and ΔZ).
The three characteristics feature values were selected based on the physical mechanism below:1. the average energy is obviously related with Q value and approximately taken as 1/3Q in the reactor industry. Hence the 1/3Q was selected as one characteristics feature value; 2. the half-live is relative with the Q value of β—decay, and T1/2 was considered; 3. considering the Sargent' s law, (1/T1/2)1/5 ∝ Q, a more accurate (1/T1/2)1/5 value were selected.
As a result, for the feature group of T1/2, the training results for all three types of average energy were unsatisfactory. For the other groups, for the average β energy data, the relative errors are 19.32% and 28.11% for(1/T1/2)1/5 and 1/3Q feature groups in the training set and 82% and 56.9% in the validation set; for the average γ energy, the relative errors were 28.9% and 76.9% for (1/T1/2)1/5 and 1/3Q feature groups and >100% and >100% in the validation set; for the average neutrino energy, the relative errors in the training set were 27.82% and 35.33% for (1/T1/2)1/5 and 1/3Q feature group and 76.32% and 37.76% in the validation set.
Considering the accuracy comparison of the three groups, 1/3Q feature group were selected to predict the average energy data of nuclei in the fission product region (mass numbers ranging from 66 to 172) for which miss reliable experimental data. As a result, we supplemented the average energy data with predicted values for 291 nuclei. Besides, a comparison were performed between the calculated data and the evaluated experimental data through the nuclide chart. It is found that the neural network provides good prediction of the experimental data for the average β and neutrino energies which exhibit relatively strong regularity. However, it shows significant deviations in predictions for average γ energy (relative error in the training set was 76.9%). Large deviation also emerges in the odd-odd nuclei and nuclei near magic numbers. This study confirms that incorporating empirical relationships and physical principles can effectively enhance the performance of the neural network, and simultaneously reveals the relationship between data regularity and model generalization capability. These findings provide a basis for future integration of physical mechanisms to optimize machine learning models.
, , Received Date: 2025-04-24
Abstract +
Attosecond transient absorption spectroscopy (ATAS) is an all‐optical pump-probe technique that employs attosecond pulses (from the extreme ultraviolet to soft X-ray) to excite or probe a system, enabling real‐time tracking of electronic transitions, quantum state evolution, and energy transfer processes. This approach possesses some key advantages: 1) ultrafast temporal resolution (sub‐femtosecond) combined with high spectral resolution (millielectronvolt level); 2) broadband excitation of multiple quantum states, allowing simultaneous detection of multiple energy levels; and 3) element- and site-specific insights provided by the measurements of inner-shell to valence transition reveal charge transfer dynamics, spin state changes, and local structural evolution. To date, significant breakthroughs have been achieved in atomic/molecular physics, electronic coherent dynamics, and strong-field physics by using ATAS. This paper systematically reviews the technical principles and theoretical models related to ATAS by using medium intensity near-infrared pulses, analyzes the recent progress of the applications in gas-phase systems and condensed-phase systems, and explores their future prospects in ultrafast physical chemistry and quantum materials. In gas-phase environments, the ATAS has demonstrated significant capabilities in probing energy level shifts and population transfers in atomic systems, as well as capturing nonadiabatic dynamics and charge migration in diatomic and polyatomic molecules. While in condensed-phase systems, this technique has been effectively used to study the ultrafast dynamics of carriers in semiconductors and to examine the interaction dynamics of localized electrons in insulators and transition metals. Given the rapid evolution of attosecond laser technologies and the unique advantages of the ATAS detection method, this paper also outlines potential future directions. These prospects are expected to further expand the frontiers of ultrafast spectroscopy and drive advancements in a range of disciplines in basic research and technological applications.
, , Received Date: 2025-04-15
Abstract +
Compton scattering is defined as an inelastic scattering process in which the interaction between strong laser fields and electrons in matter leads to photon emission. In recent years, with the rapid development of X-ray free-electron lasers, the intensity of X-ray lasers has steadily increased, and the photon energy in Compton scattering process has risen correspondingly. Previous studies focus on single-photon Compton scattering of free electrons. However, the mechanism of non-relativistic X-ray photon scattering by bound electrons remains to be elucidated. Therefore, we develop a frequency-domain theory based on non-perturbative quantum electrodynamics to investigate single-photon Compton scattering of bound electrons in strong X-ray laser fields. Our results show that the double-differential probability of Compton backscattering decreases with the increase of incident photon energy. This work establishes a relationship between Compton scattering and atomic ionization in high-frequency intense laser fields, thereby providing a platform for studying atomic structure dynamics under high-intensity laser conditions.
, , Received Date: 2025-04-15
Abstract +
Plasmon-induced transparency (PIT) is a class of electromagnetically induced transparency phenomenon that enhances the interaction between light and matter, thereby improving the performance of nano-optical devices. However, traditional PITs usually rely on near-field coupling between bright modes and dark modes. In order to break through the limitation of this mechanism, in this study we propose a dual-polarized graphene hypersurface structure, which consists of four groups of symmetric L-shaped graphene surrounding cross-shaped hollow graphene, forming a triple PIT through the synergistic effect between two single PITs. The accuracy of the results is verified by simulating the transmission spectra using the finite-difference time-domain (FDTD), which is highly similar to that of the coupled-mode theory (CMT) results. It is found that by modulating the Fermi energy levels and carrier mobility, this structure exhibits a group refractive index of up to 500 as a slow-light device, demonstrating excellent slow-light control capability. As a polarizing device, this structure has dual polarization characteristics and can generate a triple PIT window under both x and y polarized light incidence. In particular, the resonant frequency f6 is not affected by the direction of polarization of the incident light. This good stability and resistance to interference in various polarized light conditions are particularly important for designing polarization devices. Meanwhile, we adjust the length parameter of graphene L2 and find that the resonance frequency f6 is still highly stable, showing a better tolerance to structural changes. Therefore, in this study, a multifunctional integrated device with slow light modulation and polarization selection in one device is designed, providing new theoretical guidance and research directions for synergistic effects based on polarization insensitivity.
, , Received Date: 2025-04-21
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Low-dimensional material systems benefit from their extremely high carrier mobility and flexible integrability, making them a subject of research in the terahertz detection field and demonstrating significant potential for applications. At present, software is mainly used to simulate and analyze the structures relied upon for semiconductor terahertz detection of bulk materials, while the simulation analysis for terahertz detection in low-dimensional material systems is still relatively unexplored. Due to the low degrees of freedom in carrier motion in low-dimensional materials, the probability of scattering caused by collisions between electrons and the lattice in the channel during electron movement is effectively reduced, making these materials have immense potential in high-sensitivity detection. Their low equivalent noise power and high signal-to-noise ratio performance in signal detection highlight the broad development prospects of these materials in the field of communication. This work simulates and analyzes the plasmon wave effect in a monolayer MoS2 field-effect transistor (FET) for THz detection for the first time, and systematically elucidates the principle and analysis process of using plasmon waves for THz detection. The transmission characteristic curve of the device is simulated and measured at a source-drain voltage of 0.5 V, and, a gate-to-drain voltage of –0.1 V is selected based on this curve to preliminarily investigate the THz response performance of the device. By adjusting key parameters such as Ugs, THz wave irradiation frequency, and HfO2 layer thickness, it is found that the monolayer MoS2 FET THz detector can produce a maximum DC voltage signal of 14 μV. This signal exhibits a complex variation trend related to the bias voltage between the gate and drain. This trend correlates with the bias voltage-induced changes in carrier concentration and the corresponding momentum relaxation time. The research results obtained in this paper can provide an important reference for designing low-dimensional material THz detectors. Furthermore, they lay a foundation for optimizing the performance of two-dimensional material THz detectors through simulation analysis, thereby providing deeper insights into the study of THz photoelectric responses in 2D materials.
, , Received Date: 2025-04-15
Abstract +
Homologous recombination is a central mechanism for maintaining genome stability and biodiversity. RecA, as the first discovered homologous recombinase, plays a crucial role in homologous recombination strand exchange. In recent years, with the development of structural biology, significant breakthroughs have been made in understanding the static structure of the RecA nucleoprotein filament. However, research on the kinetic process of homologous recombination strand exchange mediated by RecA continues to encounter significant challenges. Research into the dynamic process has been ongoing for decades. In recent years, the use of single-molecule techniques has resulted in significant breakthroughs in this field. Among these techniques, single-molecule fluorescence resonance energy transfer (FRET) technology is widely used due to its ultra-high temporal and spatial resolution, making it well suitable for studying RecA-mediated homologous recombination strand exchange. However, the fluorescent labels required for FRET experiments may affect the RecA-mediated strand exchange process, which is often overlooked by researchers. Most of related articles focus on the effect of fluorescent labels on local structure. This paper primarily examines the effect of DNA fluorescent labeling on protein function, focusing on its effects on strand exchange from two perspectives: strand specificity and conformational sensitivity of the fluorescent labeling. Using experiments such as double-strand binding, single-strand invasion, and strand exchange, we develop a labeling scheme with the minimal effect—9 bp spaced C-strand double-base labeling in triplet— that can effectively improve the efficiency of studying the homologous recombination process. This result enhances the understanding of the effect of fluorescent labeling, allowing researchers to rapidly optimize the position and method of fluorescent labeling, and reduce its negative effects on the strand exchange process. Moreover, it provides some inspirations for other fluorescent labeling experiments.
, , Received Date: 2025-04-08
Abstract +
The rapid advancement of micro-nano acoustic devices has led their core acoustic structures to shrink to the nanoscale level. The influence of surface effects on the mechanical properties of thin-film materials on a nanoscale becomes increasingly prominent, and the classical elasticity theory struggles to accurately describe their mechanical behavior on this scale. In this paper, a mechanical model of nano-SiO2/Si heterostructured thin films that considers surface effects is developed using surface elasticity theory. This model incorporates the key parameter of surface energy density. In this paper, a mechanical model of heterostructured nano-SiO2/Si films is developed using the surface elasticity theory, incorporating surface effects through the introduction of surface energy density as a key parameter . Using the Fourier integral transform method, analytical expressions for stress and displacement fields under surface traction are systematically derived, revealing the influence of surface effects on the mechanical behavior of materials on a nanoscale by comparing the analytical solution with that from the classical theory. The results show that when the surface stress distribution deviates by 3% from that predicted by the classical theory, the microscopic properties of the material become significant, and the surface effect cannot be ignored in a range of five times the width of the excitation region 2a. As the size of the excitation region decreases, the surface effect is significantly increases and the stress distribution within the excitation region and near the boundary becomes more concentrated than the counterparts in the classical theory. The shear stress is no longer zero, and an extreme value is observed at the boundary, which is significantly different from that predicted by the classical theory of elasticity. The transverse and longitudinal displacements are reduced compared with those from the classical theory, and the surface stiffness and deformation resistance of the material are greatly enhanced. Significant surface effects occur on nano-heterostructure thin films, leading to large deviations in stress and displacement distributions from the results of elasticity theory. Therefore, the classical elasticity assumptions are no longer applicable in the corresponding nanoscale range. The results demonstrate that the propagation of ultrahigh-frequency nano- length acoustic waves in nanoscale solid film surfaces is significantly affected by the scale effect. The failure of the classical elastic wave theory on a nanoscale is of great value for the study of nanoscale acoustic theory. Furthermore, these findings provide a theoretical basis for the subsequent development of more precise models of interfacial effects and a more detailed investigation of the influence of the film-substrate modulus ratio.
, , Received Date: 2025-04-10
Abstract +
The technology of space-based wireless power transfer presents a potential solution for supplying energy to spacecraft. However, this method transmits energy through high-power electromagnetic pulses, which may pose a potential threat to gallium arsenide (GaAs) solar cells. Currently, the damage mechanisms affecting solar cells in these conditions remain unclear. To solve this issue, the thermo-electrical coupled damage mechanism of single-junction GaAs solar cells is investigated using a comprehensive multiphysics simulation model in this work. The damage characteristics of the solar cells under varying voltage and frequency inputs are simulated and analyzed. Furthermore, the relationship between burnout time and both input voltage and frequency are investigated, and the differences in damage mechanisms observed at different frequencies are elucidated. The results indicate that due to high current density and contact resistance, burnout mainly occurs at the cathode electrode contacts. Additionally, the PN junction and the anode contact experience significant temperature elevations, which is more likely to affect the cell performance. By deepening our understanding of how high-power electromagnetic pulses damage space solar cells, this study will provide support for designing electromagnetic protection systems for spacecraft power architectures.
, , Received Date: 2025-04-03
Abstract +
, , Received Date: 2025-03-24
Abstract +
In recent years, people have increased their efforts to use spoof surface acoustic waves (SSAWs) to achieve subwavelength-scale modulation. However, obstacles on the transmission path often cause strong scattering of SSAWs, which limits their practical applications in communications and other fields. In this paper, we propose a new type of acoustic metasurface that supports the SSAWs’ propagation on both sides and design an acoustic stealth device based on such a metasurface. This metasurface is composed of periodically arranged Helmholtz resonators with bidirectional apertures, whose unique structure enables SSAWs to achieve interlayer transitions between the top surface and bottom surface. Remarkably, the total thickness of the structure is only 1/20 of the incident wavelength, exhibiting obvious subwavelength characteristics. We theoretically calculate the dispersion curve of SSAWs, and establish the dependency relationship between the propagation wave vector and the structural parameters. By optimizing the structural parameters of the double-sided metasurface, the wave vector matching during propagation is ensured, thereby achieving efficient transitions with minimal losses between the top and bottom surfaces. We construct a “sound-transparent path” through numerical simulations, allowing waves to bypass obstacles without scattering, and demonstrate that thermoviscous effects exert a negligible influence on transmission efficiency. Furthermore, an experiment is carried out to validate this metasurface’s dual-sided wave-manipulation capability, which demonstrates that the SSAWs maintain their wavefronts during interfacial propagation, showing excellent robustness against large-sized obstacles. The proposed stealth device possesses notable advantages, including a lightweight structure and high flexibility, providing new research perspectives and technical pathways for manipulating SSAWs and designing acoustic devices on a deep subwavelength scale.
, , Received Date: 2025-04-15
Abstract +
The magnetoelectric (ME) antenna based on the piezoelectric resonance principle can solve the problems of large size and high power consumption of traditional low-frequency electrical antennas. However, the acoustic impedance mismatch between the adhesive layer in the magnetoelectric composite and the piezoelectric and ferromagnetic phases significantly hinders the stress transfer in the magneto-mechanical-electric coupling process, ultimately limiting the magnetic radiation intensity of the magnetoelectric composite. To improve the magnetic emission performance of the PZT MFC/Metglas magnetoelectric composite, in this work, the two-dimensional filler MoS2 is adopted to fill and modify the adhesive layer of the PZT MFC/Metglas magnetoelectric composite, aiming to improve the acoustic impedance match between the adhesive layer and the ferroelectric and ferromagnetic phases. The influence of the MoS2 content on the magnetic emission intensity of the PZT MFC/Metglas magnetoelectric composite is systematically studied. The results show that when the filling weight percent of MoS2 is 1%, the magnetic emission intensity of the PZT MFC/Metglas magnetoelectric composite can reach 331 μT under the optimal bias, which is 1.5 times higher than that of the magnetoelectric composite without MoS2 filling. At a distance of 1 m, the magnetic emission intensity can reach 2.7 nT. The stress wave transfer mechanism in the electro-mechanical-magnetic coupling is discussed in conjunction with acoustic impedance matching theory. In addition, the amplitude shift keying modulation method demonstrates the lossless signal transmission capability of the magnetoelectric antenna composed of MoS2-modified PZT MFC/Metglas magnetoelectric composite. This method of optimizing the interfacial adhesive layer is simple and effective to expand the magnetoelectric response by increasing the stress wave transfer efficiency. Meanwhile, it provides a feasible solution for communication systems such as low-frequency underwater communication, underground sensing, and distributed wireless networks.
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