Frontiers of Physics最新文献

In spintronics, transverse anomalous transport properties have emerged as a highly promising avenue surpassing the conventional longitudinal transport behaviors. Here, we explore the transverse transport properties of monolayer and bilayer Fe_3−xCo_xGaTe₂ (x = 0.083, 0.167, 0.250, and 0.330) systems. All the systems exhibit ferromagnetic ground states with metallic features and also have perpendicular magnetic anisotropy. Besides, the magnetic anisotropy is substantially enhanced with increasing Co-doping concentration. However, unlike magnetic anisotropy, the Curie temperature is suppressed by increasing the Co-doping concentration. For instance, the monolayer and bilayer Fe_2.917Co_0.083GaTe₂ hold a Curie temperature of 253 K and 269 K, which decreases to 163 K and 173 K in monolayer and bilayer Fe_2.67Co_0.33GaTe₂ systems, respectively. We find a giant anomalous Nernst conductivity (ANC) of 6.03 A/(K·m) in the monolayer Fe_2.917Co_0.083GaTe₂ at −30 meV, and this is further enhanced to 11.30 A/(K·m) in the bilayer Fe_2.917Co_0.083GaTe₂ at −20 meV. Moreover, the bilayer Fe_2.917Co_0.083GaTe₂ structure has a large anomalous thermal Hall conductivity (ATHC) of −0.14 W/(K·m) at 100 K. Overall, we find that the Fe_3−xCo_xGaTe₂ (x = 0.083, 0.167, 0.250, and 0.330) structures have better anomalous transverse transport performance than the pristine Fe₃GaTe₂ system and can be used for potential spintronics and spin caloritronics applications.

Laser-induced breakdown spectroscopy (LIBS) is a spectroscopic analytic technique with great application potential because of its unique advantages for online/in-situ detection. However, due to the spatially inhomogeneity and drastically temporal varying nature of its emission source, the laser-induced plasma, it is difficult to find or hard to generate an appropriate spatiotemporal window for high repeatable signal collection with lower matrix effects. The quantification results of traditional physical principle based calibration model are unsatisfactory since these models were not able to compensate for complicate matrix effects as well as signal fluctuation. Machine learning is an emerging approach, which can intelligently correlated the complex LIBS spectral data with its qualitative or/and quantitative composition by establishing multivariate regression models with greater potential to reduce the impacts of signal fluctuation and matrix effects, therefore achieving relatively better qualitative and quantitative performance. In this review, the progress of machine learning application in LIBS is summarized from two main aspects: i) Pre-processing data for machine learning model, including spectral selection, variable reconstruction, and denoising to improve qualitative/quantitative performance; ii) Machine learning methods for better quantification performance with reduction of the impact of matrix effect as well as LIBS spectra fluctuations. The review also points out the issues that researchers need to address in their future research on improving the performance of LIBS analysis using machine learning algorithms, such as restrictions on training data, the disconnect between physical principles and algorithms, the low generalization ability and massive data processing ability of the model.

Single-photon detections (SPDs) represent a highly sensitive light detection technique capable of detecting individual photons at extremely low light intensity levels. This technology mainly relies on the mainstream SPDs, such as photomultiplier tubes (PMTs), avalanche photodiodes (SAPD), superconducting nanowire single-photon detectors (SNSPDs), superconducting transition-edge sensor (TES), and hybrid lead halide perovskite. However, the complexity and high manufacturing cost, coupled with the requirement of special conditions like a low-temperature environment, pose significant challenges to the wide adoption of SPDs. To address the challenges faced by SPDs, significant efforts have been devoted to enhancing their performance. In this review, we first summarize the principles and technical challenges of several SPDs. Conductors, superconductors, semiconductors, 3D bulk materials, 2D film materials, 1D nanowires, and 0D quantum dots have all been discussed for single-photon detectors. Methods such as special optical structure, waveguide integration, and strain engineering have been employed to elevate the performance of single-photon detectors. These techniques enhance light absorption and modulate the band structure of the material, thereby improving the single-photon sensitivity. By providing an overview of the current situation and future challenges of SPDs, this review aims to propose potential solutions for photon detection technology.

Modern particle physics experiments usually rely on highly complex and large-scale spectrometer devices. In high energy physics experiments, visualization helps detector design, data quality monitoring, offline data processing, and has great potential for improving physics analysis. In addition to the traditional physics data analysis based on statistical methods, visualization provides unique intuitive advantages in searching for rare signal events and reducing background noises. By applying the event display tool to several physics analyses in the BESIII experiment, we demonstrate that visualization can benefit potential physics discovery and improve the signal significance. With the development of modern visualization techniques, it is expected to play a more important role in future data processing and physics analysis of particle physics experiments.

The emerging nonvolatile memory, three-dimensional vertical resistive random-access memory (VRRAM), inspired by the vertical NAND structure, has been proposed to replace NAND flash memory which has reached its integration limit. To improve the vertical ionic diffusion occurring in the conventional VRRAM structure, we propose a Pt/HfO₂/TiO₂/Ti self-aligned VRRAM with physically confined switching cells through sidewall thermal oxidation. We achieved stable bipolar switching, endurance (>10⁴ cycles), and retention (>10⁴ s) responses, and improved the interlayer leakage current issue through a distinctive self-aligned structure. Additionally, we elucidated the switching mechanism by analyzing current levels concerning ambient temperature. To utilize VRRAM for neuromorphic computing, the biological synaptic functions are emulated by applying pulse stimulation to the synaptic cell. The weight modulation of biological synapses is demonstrated based on potentiation, depression, spike-rate-dependent plasticity, and spike-timing-dependent plasticity. Additionally, we improve the pattern recognition rate by creating a linear conductance modulation with an incremental pulse train in pattern recognition simulations. The stable electrical characteristics and implementation of various synaptic functions demonstrate that self-aligned VRRAM is suitable for neuromorphic systems as a high-density synaptic device.

Localized surface plasmon resonance (LSPR) is an intriguing phenomenon that can break diffraction limitations and exhibit excellent light-confinement abilities, making it an attractive strategy for enhancing the light absorption capabilities of photodetectors. However, the complex mechanism behind this enhancement is still plaguing researchers, especially for hot-electron injection process, which inhibits further optimization and development. A clear guideline for basic physical model, enhancement mechanism, material selection and architectural design for LSPR photodetector are still required. This review firstly describes the mainstream understanding of fundamental physical modes of LSPR and related enhancement mechanism for LSPR photodetectors. Then, the universal strategies for tuning the LSPR frequency are introduced. Besides, the state-of-the-art progress in the development of LSPR photodetectors is briefly summarized. Finally, we highlight the remaining challenges and issues needed to be resolved in the future research.

We experimentally demonstrate the generation of customized Laguerre–Gaussian (LG) beams whose intensity maxima are localized around any desired curves. The principle is to act with appropriate algebraic functions on the angular spectra of LG beams. We characterize the propagation properties of these beams and compare them with non-diffraction caustic beams possessing the same intensity profiles. The results manifest that the customized-LG beams can maintain their profiles during propagation and suffer less energy loss than the non-diffraction caustic beams, and hence are able to propagate a longer distance. Moreover, the customized-LG beam exhibits self-healing ability when parts of their bodies are blocked. This new structure beam has potential applications in areas such as optical communication, soliton routing and steering, and optical tweezing.

Van der Waals epitaxy allows heterostructure formation without considering the lattice match requirement, thus is a promising method to form 2D/2D and 2D/3D heterojunction. Considering the unique optical properties of CsPbI₃ and transition metal dichalcogenides (TMDCs), their heterostructure presents potential applications in both photonics and optoelectronics fields. Here, we demonstrate selective growth of cubic phase CsPbI₃ nanofilm with thickness as thin as 4.0 nm and zigzag/armchair oriented nanowires (NWs) on monolayer WSe₂. Furthermore, we show growth of CsPbI₃ on both transferred WSe₂ on copper grid and WSe₂–based optoelectrical devices, providing a platform for structure analysis and device performance modification. Transmission electron microscopy (TEM) results reveal the epitaxial nature of cubic CsPbI₃ phase. The revealed growth fundamental of CsPbI₃ is universal valid for other two-dimensional substrates, offering a great advantage to fabricate CsPbI₃ based van der Waals heterostructures (vdWHs). X-ray photoelectron spectroscopy (XPS) and optical characterization confirm the type-II band alignment, resulting in a fast charge transfer process and the occurrence of a broad emission peak at lower energy. The formation of WSe₂/CsPbI₃ heterostructure largely enhances the photocurrent from 2.38 nA to 38.59 nA. These findings are vital for bottom-up epitaxy of inorganic semiconductor on atomic thin 2D substrates for optoelectronic applications.

Metasurfaces and metagratings offer new platforms for electromagnetic wave control with significant responses. However, metasurfaces based on abrupt phase change and resonant structures suffer from the drawback of high loss and face challenges when applied in water waves. Therefore, the application of metasurfaces in water wave control is not ideal due to the limitations associated with high loss and other challenges. We have discovered that non-resonant metagratings exhibit promising effects in water wave control. Leveraging the similarity between bridges and metagratings, we have successfully developed a water wave metagrating model inspired by the ancient Luoyang Bridge in China. We conduct theoretical calculations and simulations on the metagrating and derive the equivalent anisotropic model of the metagrating. This model provides evidence that the metagrating has the capability to control water waves and achieve unidirectional surface water wave. The accuracy of our theory is strongly supported by the clear observation of the unidirectional propagation phenomenon during simulation and experiments conducted using a reduced version of the metagrating. It is the first time that the unidirectional propagation of water waves has been seen in water wave metagrating experiment. Above all, we realize the water wave metagrating experiment for the first time. By combining complex gratings with real bridges, we explore the physics embedded in the ancient building — Luoyang Bridge, which are of great significance for the water wave metagrating design and provide a new method for analyzing the effects of water waves on bridges. At the same time, this discovery also provides a new idea for ocean cargo transportation, ocean garbage cleaning, and the development and protection of ancient bridges.