Accepted
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Time-of-Flight Photoelectron Spectroscopy (TOF-PES) has emerged as a cornerstone diagnostic tool in attosecond science and ultrafast dynamics, offering exceptional energy and temporal resolution. This article presents a comprehensive review of TOF-PES technology, its underlying principles, and its crucial role in attosecond metrology. The first part introduces the historical development of TOF methods, from early ion mass spectrometry to modern photoelectron applications, detailing key innovations such as energy and spatial focusing, magnetic shielding, and delay-line detectors. The implementation of magnetic bottle spectrometers (MBES) is discussed in depth, emphasizing their advantages in wide-angle electron collection and enhanced energy resolution, achieved through trajectory collimation and magnetic gradient design.
We then focus on the application of TOF-PES in attosecond pulse characterization, particularly in the RABBITT (Reconstruction of Attosecond Beating by Interference of Two-photon Transitions) and attosecond streaking techniques. A broad array of experimental breakthroughs is reviewed, including ultrafast delay scanning, energy-time mapping through photoelectron modulation, and the use of MBES to resolve phase and amplitude of attosecond pulse trains with sub-50 attosecond precision. These advances demonstrate TOF-PES as a critical enabler of temporal phase reconstruction and group delay measurement across extreme-ultraviolet (XUV) spectral regimes.
Further sections explore the integration of TOF-based detection in time- and angle-resolved photoemission spectroscopy (TR-ARPES and ARTOF), enabling full 3D momentum-resolved detection without mechanical rotation or slits. The synergy between TOF and ultrafast laser sources facilitates simultaneous energy and momentum resolution across the Brillouin zone, with applications spanning topological materials, superconductors, and charge-density wave systems.
Finally, the review extends to momentum-resolved ultrafast electron-ion coincidence techniques. The use of TOF in COLTRIMS (Cold Target Recoil Ion Momentum Spectroscopy) and VMI (Velocity Map Imaging) is evaluated, highlighting its indispensable role in resolving correlated electron-ion dynamics, few-body fragmentation processes, and tunneling time delays on attosecond and even zeptosecond scales.
Overall, this work underscores the central role of TOF-PES in pushing the frontiers of ultrafast science. While current challenges include space-charge effects, detector response limitations, and data handling complexity, future advances in quantum detection, AI-driven trajectory correction, and high-repetition-rate light sources are poised to overcome these barriers. TOF-PES, through its continuous evolution, remains a critical platform for probing quantum dynamics at the fastest timescales known.
We then focus on the application of TOF-PES in attosecond pulse characterization, particularly in the RABBITT (Reconstruction of Attosecond Beating by Interference of Two-photon Transitions) and attosecond streaking techniques. A broad array of experimental breakthroughs is reviewed, including ultrafast delay scanning, energy-time mapping through photoelectron modulation, and the use of MBES to resolve phase and amplitude of attosecond pulse trains with sub-50 attosecond precision. These advances demonstrate TOF-PES as a critical enabler of temporal phase reconstruction and group delay measurement across extreme-ultraviolet (XUV) spectral regimes.
Further sections explore the integration of TOF-based detection in time- and angle-resolved photoemission spectroscopy (TR-ARPES and ARTOF), enabling full 3D momentum-resolved detection without mechanical rotation or slits. The synergy between TOF and ultrafast laser sources facilitates simultaneous energy and momentum resolution across the Brillouin zone, with applications spanning topological materials, superconductors, and charge-density wave systems.
Finally, the review extends to momentum-resolved ultrafast electron-ion coincidence techniques. The use of TOF in COLTRIMS (Cold Target Recoil Ion Momentum Spectroscopy) and VMI (Velocity Map Imaging) is evaluated, highlighting its indispensable role in resolving correlated electron-ion dynamics, few-body fragmentation processes, and tunneling time delays on attosecond and even zeptosecond scales.
Overall, this work underscores the central role of TOF-PES in pushing the frontiers of ultrafast science. While current challenges include space-charge effects, detector response limitations, and data handling complexity, future advances in quantum detection, AI-driven trajectory correction, and high-repetition-rate light sources are poised to overcome these barriers. TOF-PES, through its continuous evolution, remains a critical platform for probing quantum dynamics at the fastest timescales known.
, , Received Date: 2025-03-20
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In an electronic double-layer system composed of two spatially adjacent but electrically insulated conductors, when current flows through one conductor (drive layer), its charge carriers transfer energy/momentum to the charge carriers in the other conductor (drag layer) through interlayer Coulomb coupling, thus generating a measurable voltage or current in the drag layer, This phenomenon is known as interlayer drag effect. This effect provides a critical approach for studying quasiparticle interactions and investigating interlayer-correlated quantum states. Two-dimensional layered materials with highly tunable properties provide new opportunities for exploring the drag effect. In this study, we fabricate an electronic double-layer structure consisting of graphene and NbSe2 to systematically investigate the drag effect between a two-dimensional semimetal and a two-dimensional superconductor, wherein a thin hBN layer serves as the insulating spacer. When graphene acts as the drive layer and NbSe2 acts as the drag layer, a significant positive drag response is observed within the superconducting transition temperature range of NbSe2. In contrast, the drag signal vanishes when NbSe2 is in its normal metallic state. The measurements of magnetic field dependence reveal that the drag response disappears under high fields where the superconductivity of NbSe2 is suppressed, further confirming its direct correlation with the superconducting transition. The gate-voltage modulation experiments reveal that the drag response peaks when adjusting the Fermi level of graphene across the Dirac point. This is attributed to the reduced screening of interlayer interactions due to the ultra-low carrier concentration at this point. Notably, the sign of the supercurrent drag does not depend on the carrier type in graphene, ruling out the traditional momentum-transfer drag mechanism. Our results collectively demonstrate the realization of supercurrent drag effect, which has been attributed to Coulomb coupling between the quantum fluctuations of the superconducting phases in a superconductor and the charge densities in a normal conductor in previous study. Notably, by comparing different devices, it is found that this type of supercurrent drag responses occurs only in the thin NbSe2 layers cleaved in air. No significant signals are detected in thick NbSe2 layers or thin layers cleaved under the protection of argon. These results establish the importance of superconducting inhomogeneity in NbSe2 for generating supercurrent drag effect, indicating that drag measurements can also serve as a novel probe for investigating superconducting properties. Further investigation into the polarity and intensity of supercurrent drag signals may advance our understanding of inhomogeneous superconductivity, as well as interactions between normal carriers and Cooper pairs.
, , Received Date: 2025-02-21
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Terahertz (THz) time-domain spectroscopy and imaging techniques on a nanoscale are crucial for material research, device detection, and others. However, traditional far-field THz time-domain spectroscopy faces inherent diffraction limitations, which limits the applications of carrier dynamics analysis that require femtosecond time resolution and nanoscale spatial precision. We present a scattering-type scanning near-field optical microscopy that overcomes these limitations by combining ultrafast THz time-domain spectroscopy with atomic force microscopy (AFM). The utilization of the near-field interaction between the needle tip and the sample surface is demonstrated to facilitate the study of semiconductor materials and devices by using static THz spectroscopy with a lateral spatial resolution of ~60 nm. This, in turn, enables the acquisition of static THz conductivity distributions of the semiconductor materials. Additionally, it facilitates the acquisition of transient conductivity distributions of semiconductor materials and laser THz emission ultrafast via photoexcited transient carrier kinetic processes, which provides substantial support for studying the performances of materials and devices in nanometer spatial resolution, ultrafast time resolution, and THz spectroscopic imaging. The experimental results show that the system has a signal-to-noise ratio as high as 56.34 dB in the static THz time-domain spectral mode, and can effectively extract the fifth-order harmonic signals covering the 0.2–2.2 THz frequency band with a spatial resolution of up to ~60 nm. Carrier excitation and complexation processes in topological insulators are successfully observed by optical pump-THz probe with a time resolution better than 100 fs. Imaging of SRAM samples by the system reveals differences in THz scattering intensity due to non-uniformity in doping concentration, thereby validating its potential application in nanoscale defect detection. This study not only provides an innovative means for studying the nanoscale electrical characterization of semiconductor materials and devices, but also opens a new way for applying the THz technology to interdisciplinary subjects such as nanophotonics and spintronics. In the future, by integrating the superlens technology, optimizing the probe design, and introducing deep learning algorithms, it is expected to further improve the temporal- and spatial-resolution and detection efficiency of the system.
, , Received Date: 2025-02-27
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, , Received Date: 2025-02-28
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, , Received Date: 2025-03-14
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Optical systems based on bound states in the continuum (BIC) generally possess higher quality factor (Q) values and narrower operational linewidths than traditional photonic crystals or metasurfaces. The higher Q values offer extensive possibilities for high-performance optoelectronic devices. However, the narrower linewidths often pose challenges in practical applications, as fabrication errors during production inevitably lead to discrepancies between real optical devices and their ideal designs, which results in mismatches between actual and ideal operating wavelengths. To solve this problem, we explore the dynamic tuning effect of liquid crystal (LC) on quasi-bound states in the continuum (q-BIC) so as to compensate for wavelength shifts caused by fabrication errors. A photonic crystal slab with cross-shaped holes serves as the platform for generating q-BIC. Compared with the modulation induced by the tilt angles of incident light on q-BIC, LC has a less influence on the system’s Q factor when the same operational wavelength is shifted. For instance, shifting the central wavelength λ0 of q-BIC by 5.32 nm by using a tilted incident angle results in the Q factor decreasing to 75.84% (from 3809.05 to 920.28). Whereas shifting the central wavelength λ0 by 5.63 nm through the tilt angle θ of LC leads Q factor to increase 14.27% (from 3809.05 to 4352.65). This demonstrates the significant potential of LC dynamic tuning in high-Q and ultra-narrowband q-BIC devices. Finally, the mechanism of LC within the q-BIC system is discussed. The smaller influence of LC on the Q factor is attributed to its minimal disruption of the q-BIC system’s symmetry. Although LC also affects system symmetry within the cross-shaped holes, after adjusting the asymmetry parameters of the system, the Q factor and the LC tuning process can be well matched. The results of our research provides valuable references for carrying on extensive research on q-BIC.
, , Received Date: 2025-03-18
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In the near-field of a subsonic jet, complex energy transport and transformation processes occur between kinetic energy, thermal energy, and acoustic energy, which play a crucial role in jet instability and noise radiation. Accurately characterizing the transport features of each energy component is essential for developing effective noise suppression technologies. According to Myers’ precise energy equation for total disturbances in any steady flow [1991 J. Fluid Mech. 226 383], the present study develops a modified energy equation based on hydro-acoustic mode decomposition to separate the contributions of vortical, entropic, and acoustic modes to the total disturbance energy. The method begins with the decomposition formulas for velocity, pressure, and density, following the hydro-acoustic mode decomposition method proposed by Han et al. [2023 Phys. Fluids 35 076107]. In Myers’ energy equation framework, the disturbances of primitive variables (velocity, pressure, and density) are expressed as linear combinations of their vortical, entropic, and acoustic components. With this formula, the vortical (entropic, acoustic) energy is defined as being contributed only by the disturbance of the corresponding mode, while the nonlinear energy is attributed to interaction between vortical, entropic, and acoustic components. This approach yields a modified energy equation capable of distinguishing the individual contributions of vortical, entropic, and acoustic modes to both total disturbance energy and energy flux, thus making it particularly suitable for analyzing energy transport characteristics in the near flow field. The developed equation is used to analyze a subsonic jet with a Mach number of 0.9, revealing different spatial distributions and transport mechanisms of hydrodynamic energy and acoustic energy. The results indicate that vortical energy and entropic energy are mainly concentrated in the near-field, convecting downstream at a velocity about 0.8 times the jet velocity. In contrast, acoustic energy exhibits dual propagation characteristics: it radiates outward to the far field through acoustic waves outside the potential core, while propagating upstream through trapped waves inside the potential core. The energy related to multi-mode nonlinear interactions is mainly concentrated in the jet wake and propagates without obvious directionality. The total disturbance energy is mainly contributed by vortical energy, while the acoustic energy only accounts for a small part of the total disturbance energy, approximately 10–3 of the total. This refined analysis provides deeper insights into the complex energy dynamics in subsonic jets and valuable information for predicting and controlling jet noise strategies. The modified energy equation provides a robust framework for understanding and quantifying the intricate energy transport processes in jet flows.
, , Received Date: 2025-02-21
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With the continuous growth of global demand for renewable energy, the utilization of rainwater resources has gradually become a focal point of research. Piezoelectric energy harvesting has received significant attention because the harvester has simple structure, high energy conversion efficiency, and self-powering capability. However, traditional piezoelectric energy harvesters are limited by the narrow resonance frequency bandwidth and the insufficient waterproofing ability, which restricts the adaptability of energy conversion to variable environmental excitations. To solve this problem, a broadband piezoelectric cantilever energy harvester for rainwater energy harvesting is designed in this work. The influence mechanisms of droplet impact parameters, waterproof encapsulation technology, and MFC cantilever structure on the electrical output performance are studied through theoretical analysis, numerical simulation, and experimental validation. It reveals that the droplet’s Weber number exhibits a direct proportionality with the impact force, which is distributed within the 0–80 Hz frequency range. Simulations and experimental results demonstrate that the U-shaped piezoelectric energy harvester significantly outperforms other designs in terms of broadening the resonant frequency range and extending oscillation duration, achieving an oscillation time of 23.7 s, a charge transfer of 2.82 μC, and an output power density of 37.76 W/m2 under a single impact. It demonstrates its efficient energy harvesting capability in a wide resonance frequency range. Additionally, the U-shaped design also improves its waterproof performance, thus further enhancing its applicability in rainwater environments. This study provides a novel, universally applicable approach for collecting rainwater energy, expands the application scenarios of piezoelectric energy harvesting technology, and provides theoretical references and practical guidance for designing and applying broadband energy harvesters.
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In recent years, the physics of systems with non-reciprocal interactions has become an increasing research focus. Systems with non-reciprocal interactions are ubiquitous across soft matter, active matter, as well as biological and artificial nanoscale systems. The directional transport of coupled Brownian particles with nonreciprocal interactions was investigated by establishing a nonreciprocal coupled Brownian ratchets model. The effects of parameters such as the coupling free length, thermal noise intensity, and the ratio of nonreciprocal coupling strength coefficients on the ratchet's directional transport were systematically examined.
Research reveals that the flow reversal of particles can be induced by adjusting the coupling free length. Meanwhile, there exists an optimal ratio of coupling strength coefficients that maximizes the directional transport of the nonreciprocally coupled Brownian particles. These findings demonstrate that nonreciprocal interactions indeed enhance directional transport of coupled systems. Additionally, directional transport control can be achieved by modulating parameters such as thermal noise intensity, asymmetry coefficient, and external potential barrier height. Future research may further explore the dynamical mechanisms of nonreciprocal interactions in complex environments, especially the swarm behaviors in many-particle systems. Furthermore, by combining relevant experimental and theoretical studies, deeper insights can be gained into the regularity and universality of non-reciprocal interactions across both natural and artificial nanoscale systems.
Research reveals that the flow reversal of particles can be induced by adjusting the coupling free length. Meanwhile, there exists an optimal ratio of coupling strength coefficients that maximizes the directional transport of the nonreciprocally coupled Brownian particles. These findings demonstrate that nonreciprocal interactions indeed enhance directional transport of coupled systems. Additionally, directional transport control can be achieved by modulating parameters such as thermal noise intensity, asymmetry coefficient, and external potential barrier height. Future research may further explore the dynamical mechanisms of nonreciprocal interactions in complex environments, especially the swarm behaviors in many-particle systems. Furthermore, by combining relevant experimental and theoretical studies, deeper insights can be gained into the regularity and universality of non-reciprocal interactions across both natural and artificial nanoscale systems.
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Experimental opacity data were used to evaluate the opacity models and their accuracy of the calculated results. In order to study the opacity of carbon material in the shell of the inertial confinement fusion ignition target, the experimental study of the spectral-resolved opacity of radiation heated carbon plasma was carried out on the Shenguang III prototype laser facility. Eight nanosecond lasers were injected into a conical-cylindrical gold hohlraum and converted to intense X-ray radiation，the high temperature plasma was obtained by radiatively heating the CH film in the center of the hohlraum. Temporal evolutions of temperature and density of carbon plasma were simulated with the Multi-1D code. By using a spatially resolved gated flat field grating spectrometer combined with the ninth beam smoothing surface backlight technology, the absorption spectra and backlighter spectra of CH sample were measured in one shot. Finally, the experimental transmission spectra of carbon plasma (with temperature of 65eV and density of 0.003g/cm3) in the 300eV-500eV region have been obtained and compared with the calculated results of a DCA/UTA opacity code.
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The rapid advancement of artificial intelligence has transformed materials science research, with large language models (LLMs) emerging as a pivotal driver of innovation. This review explores the comprehensive role of LLMs in accelerating materials design across the entire research lifecycle, from knowledge mining to intelligent design. The study aims to highlight how LLMs can address challenges in traditional materials research, such as data fragmentation, high experimental costs, and limited reasoning capabilities, by leveraging their strengths in information retrieval, cross-modal data integration, and intelligent reasoning.
Key methodologies include the application of LLMs in knowledge discovery through techniques like retrieval-augmented generation (RAG), multi-modal information retrieval, and knowledge graph construction. These approaches enable efficient extraction and structuring of materials data from vast repositories of scientific literature and experimental records. Additionally, LLMs are integrated with automated experimental platforms to optimize workflows, from natural language-driven experiment design to high-throughput iterative testing.
The results demonstrate that LLMs significantly enhance materials research efficiency and accuracy. For instance, in knowledge mining, LLMs improve information retrieval precision by up to 29.4% in tasks like predicting material synthesis conditions. In materials design, LLMs enable accelerated computational modeling, structural and property prediction, and inverse design, reducing experimental trial-and-error cycles. Notably, LLMs excel in cross-scale knowledge integration, linking material composition, processing parameters, and performance metrics to guide innovative synthesis pathways.
However, challenges persist, including the reliance on high-quality data, the "black-box" nature of LLMs, and limitations in handling complex material systems. Future directions emphasize enhancing data quality through multi-source integration, improving model explainability via visualization tools, and deepening interdisciplinary collaboration to bridge gaps between AI and domain-specific expertise.
In conclusion, LLMs are reshaping materials science by enabling data-driven, knowledge-intensive research paradigms. Their ability to integrate vast datasets, predict material properties, and automate experimental workflows positions them as indispensable tools for accelerating materials discovery and innovation. As LLMs evolve, their synergy with physical constraints and experimental platforms promises to unlock new frontiers in materials design.
Key methodologies include the application of LLMs in knowledge discovery through techniques like retrieval-augmented generation (RAG), multi-modal information retrieval, and knowledge graph construction. These approaches enable efficient extraction and structuring of materials data from vast repositories of scientific literature and experimental records. Additionally, LLMs are integrated with automated experimental platforms to optimize workflows, from natural language-driven experiment design to high-throughput iterative testing.
The results demonstrate that LLMs significantly enhance materials research efficiency and accuracy. For instance, in knowledge mining, LLMs improve information retrieval precision by up to 29.4% in tasks like predicting material synthesis conditions. In materials design, LLMs enable accelerated computational modeling, structural and property prediction, and inverse design, reducing experimental trial-and-error cycles. Notably, LLMs excel in cross-scale knowledge integration, linking material composition, processing parameters, and performance metrics to guide innovative synthesis pathways.
However, challenges persist, including the reliance on high-quality data, the "black-box" nature of LLMs, and limitations in handling complex material systems. Future directions emphasize enhancing data quality through multi-source integration, improving model explainability via visualization tools, and deepening interdisciplinary collaboration to bridge gaps between AI and domain-specific expertise.
In conclusion, LLMs are reshaping materials science by enabling data-driven, knowledge-intensive research paradigms. Their ability to integrate vast datasets, predict material properties, and automate experimental workflows positions them as indispensable tools for accelerating materials discovery and innovation. As LLMs evolve, their synergy with physical constraints and experimental platforms promises to unlock new frontiers in materials design.
, , Received Date: 2025-03-04
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, , Received Date: 2025-02-21
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Femtosecond laser excited terahertz waves have been widely used in various fields. Herein, we demonstrate a novel method to generate terahertz radiation from a terahertz electro-optic crystal excited by infrared supercontinuum radiation (wavelengths > 1 μm), which is produced via the interaction between a femtosecond laser and a transparent solid medium. This approach yields single-cycle, low-frequency, broadband terahertz radiation. In the femtosecond laser-induced ionization process in a medium, both infrared supercontinuum radiation and terahertz radiation are simultaneously generated. When the resulting infrared supercontinuum radiation and terahertz radiation concurrently enter into an electro-optic crystal, the presence of the infrared supercontinuum radiation may interfere with the detection of the intrinsic terahertz radiation. By filtering the infrared supercontinuum radiation with narrowband filters, a new strategy is proposed for investigating the response of the electro-optic crystal in infrared spectral region.
, , Received Date: 2025-01-30
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Dielectric laser accelerators (DLAs), as compact particle accelerators, rely critically on their structural design to determine both the energy gain and beam quality of accelerated bunches. Although most existing DLAs are driven by near-infrared lasers with a wavelength of approximately 1 μm, the use of long-wave infrared (LWIR) lasers at a wavelength ten times that of this wavelength indicates that it is possible to achieve excellent beam quality without sacrificing acceleration gradient. To address the lack of optimized structural designs in the LWIR band where long-distance acceleration poses unique challenges—we introduce a deep learning–based design method for LWIR dielectric grating accelerator structures. Our approach integrates geometric parameters, material properties, and optical-field energy metrics into a unified evaluation framework and uses a surrogate model to predict particle energy gain with high precision. Optimal structural parameters are then extracted to realize the final design. The simulation results show that the energy gain is 99.5 keV (a year-over-year increase of 19.9% ), the transmission efficiency is 100%, the beam spot radius of 14.5 μm, and the average beam current is 20.4 fA, which is 6.9 times higher than similar near-infrared gratings, while maintaining equivalent beam brightness. This work provides a feasible technical route for designing high-netgain LWIR dielectric grating accelerators and a novel framework for optimizing the structure of complex optoelectronic devices.
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Three-dimensional ultrasonic waves with amplitudes of 14, 18, and 22 μm were applied during the solidification of (FeCoNiCrMn)92Mo8 high-entropy alloy, and its microstructural evolution and mechanical property were investigated. Under static condition, the solidification microstructure was composed of primary γ phase dendrites with FCC structure and stripe-shaped σ phase with tetragonal structure. As the ultrasonic amplitude increased, the mean transient cavitation intensity rose to trigger a significant nucleation rate increase of the primary γ phase to 5.6×1012 m-3·s-1, leading to the remarkable grain size reduction by two orders of magnitude. The maximum and average acoustic streaming velocity increased concurrently, which accelerated atomic diffusion at the liquid/solid interface, reducing Cr content in the primary γ phase from 18.6 at.% to 13.1 at.% and Mo content from 6.8 at.% to 3.4 at.%. This atomic redistribution subsequently caused the liquid composition approaching the eutectic point and facilitated the formation of (γ+σ) eutecticss, which took up more than 50% volume fraction. The two eutectic phases exhibited a semi-coherent interface relationship characterized by (110)γ//(110)σ and (1-1-1)γ//(-110)σ. Furthermore, due to the progressive enrichment of Cr atoms in the remaint liquid phase, a small amount of metastable μ phase with Cr content up to 62.3 at.% formed in the final microstructure. The maximum compressive yield strength of the ultrasonically solidified microstructure reached 876.2 MPa, which was nearly twice of that for static solidification microstructure, and the compressive strain reached 33.2%. The formation of (γ+σ) eutectics represented as the dominant factor to contribute an enhancement of 527.1 MPa to the alloy's yield strength.
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