Carbon nanotubes (CNTs) have garnered significant attention due to their remarkable electronic and magnetic properties. In this research, we introduced multiwalled carbon nanotubes covered with tantalum (MWNTs/Ta) to systematically modulate the magnetoresistive properties of the MWNTs/Ta hybrid nanostructures. We observed distinct changes in both positive and negative magnetoresistances of MWNTs/Ta across a broad temperature range using a physical property measurement system and a four-terminal method. This study on temperature-dependent magnetoresistive behavior of the MWNTs/Ta sheds light on the fundamental properties of carbon-based materials and holds promise for practical applications in the field of spintronic devices.

Bilayer (BL) transition metal dichalcogenides (TMDs) are important materials in valleytronics and twistronics. Here we study terahertz (THz) magneto-optical (MO) properties of n-type 2H-stacking BL molybdenum sulfide (MoS₂) on sapphire substrate grown by chemical vapor deposition. The AFM, Raman spectroscopy and photoluminescence are used for characterization of the samples. Applying THz time-domain spectroscopy (TDS), in combination with polarization test and the presence of magnetic field in Faraday geometry, THz MO transmissions through the sample are measured from 0 to 8 T at 80 K. The complex right- and left-handed circular MO conductivities for 2H-stacking BL MoS₂ are obtained. Through fitting the experimental results with theoretical formula of MO conductivities for an electron gas, generalized by us previously through the inclusion of photon-induced electronic backscattering effect, we are able to determine magneto-optically the key electronic parameters of BL MoS₂, such as the electron density n_e, the electronic relaxation time \tau, the electronic localization factor c and, particularly, the effective electron mass m^{\ast } around Q-point in between the K- and \mathrm{\Gamma }-point in the electronic band structure. The dependence of these parameters upon magnetic field is examined and analyzed. This is a pioneering experimental work to measure m^{\ast } around the Q-point in 2H-stacking BL MoS₂ and the experimental value is very close to that obtained theoretically. We find that n_e/\tau /\mid c\mid /m^{\ast } in 2H-stacking BL MoS₂ decreases/increases/decreases/increases with increasing magnetic field. The results obtained from this study can be benefit to us in gaining an in-depth understanding of the electronic and optoelectronic properties of BL TMD systems.

Cobalt pnictides have been theoretically proposed to be attractive candidates for high-temperature superconductors. Additionally, monolayered CoX (X = As, Sb, Bi) on SrTiO₃ systems present a potential new platform for realizing topological superconductors in the two-dimensional limit, due to their nontrivial band topology. To this end, we have successfully fabricated high-quality CoBi nanoislands on SrTiO₃ (001) substrates by molecular beam epitaxy followed by an investigation of their atomic structure and electronic properties via in situ scanning tunneling microscopy/spectroscopy. Beyond the previously predicted lattice with a = b = 3.5 Å, 2 × 1 dimer row was observed in this study. Furthermore, our results reveal that the topography of CoBi islands is strongly influenced by various growth conditions, such as substrate temperature, the flux ratio between Co and Bi, and the annealing process. This study paves the way for further explorations of the superconductivity and topological properties of cobalt pnictide systems.

As the homologous compounds of MoSi₂N₄, the MoSi₂N₄(MoN)_n monolayers have been synthesized in a recent experiment. These systems consist of homogeneous metal nitride multilayers sandwiched between two SiN surfaces, which extends the septuple-atomic-layer MSi₂N₄ system to ultra-thick MSi₂N₄(MN)_n forms. In this paper, we perform a first-principles study on the MoSi₂N₄(FeN) monolayer, which is constructed by iron molybdenum nitride intercalated into the SiN layers. As a cousin of MoSi₂N₄(MoN), this double transition-metal system exhibits robust structural stability from the energetic, mechanical, dynamical and thermal perspectives. Different from the MoSi₂N₄(MoN) one, the MoSi₂N₄(FeN) monolayer possesses intrinsic ferromagnetism and presents a bipolar magnetic semiconducting behaviour. The ferromagnetism can be further enhanced by the surface hydrogenation, which raises the Curie temperature to 310 K around room temperature. More interestingly, the hydrogenated MoSi₂N₄(FeN) monolayer exhibits a quantum anomalous Hall (QAH) insulating behaviour with a sizeable nontrivial band gap of 0.23 eV. The nontrivial topological character can be well described by a two-band \mathit{k}\cdot \mathit{p} model, confirming a non-zero Chern number of C=1. Similar bipolar magnetic semiconducting feature and hydrogenation-induced QAH state are also present in the WSi₂N₄(FeN) monolayer. Our study demonstrates that the double transition-metal MSi₂N₄({\mathrm{M}}^{\prime }\mathrm{N}) system will be a fertile platform to achieve fascinating spintronic and topological properties.

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.

We investigate the magnetic excitations of the two-dimensional (2D) S = 1/2 trimerized Heisenberg models with intratrimer interaction J_1 and intertrimer interaction J_2 on four different lattices using a combination of stochastic series expansion quantum Monte Carlo (SSE QMC) and stochastic analytic continuation methods (SAC), complemented by cluster perturbation theory (CPT). These models exhibit quasi-particle-like excitations when g=J_2/J_1 is weak, characterized by low-energy magnons, intermediate-energy doublons, and high-energy quartons. The low-energy magnons are associated with the magnetic ground states. They can be described by the linear spin wave theory (LSWT) of the effective block spin model and the original spin model. Doublons and quartons emerge from the corresponding internal excitations of the trimers with distinct energy levels, which can be effectively analyzed using perturbative calculation when the ratio of exchange interactions g is weak. In this weak g regime, we observe a clear separation between the magnon and higher-energy spectra. As g increases, doublon and quarton gradually merge into the magnon modes or some continua. Notably, in the Collinear II and trimerized Hexagon lattice, a broad continuum emerges above the single-magnon spectrum, originating from the quasi-1D physics due to the dilute connections between chains. In addition, we also compare our numerical results to the experimental RIXS spectrum and analyze the difference. Our numerical analysis of these 2D trimers yields valuable theoretical predictions and explanations for the inelastic neutron scattering (INS) spectra of 2D magnetic materials featuring trimerized lattices.

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.

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.

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.

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.

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.