Neutral triple gauge couplings (nTGCs) are absent in the Standard Model (SM) and at the dimension-6 level in the Standard Model Effective Field Theory (SMEFT), arising first from dimension-8 operators. As such, they provide a unique window for probing new physics beyond the SM. These dimension-8 operators can be mapped to nTGC form factors whose structure is consistent with the spontaneously-broken electroweak gauge symmetry of the SM. In this work, we study the probes of nTGCs in the reaction
We review the physics of monolayer graphene in a strong magnetic field, with emphasis on highly collective states that emerge from the weakly interacting system because of correlations (emergent states). After reviewing the general properties of graphene and of electrons in a magnetic field, we give a brief introduction to the integer quantum Hall effect (IQHE) and the fractional quantum Hall effect (FQHE) in a 2D electron gas as foundation to show that monolayer graphene in a magnetic field exhibits both effects, but with properties modified by the influence of the graphene crystal. After giving an introduction to standard methods of dealing with emergent states for this system, we show that an SO(8) fermion dynamical symmetry governs the emergent degrees of freedom and that the algebraic and group properties of the dynamical symmetry provide a new view of strongly correlated states observed in monolayer graphene subject to a strong magnetic field.
Atomically thin two-dimensional (2D) semiconductors are attractive channel materials for next-generation field-effect transistors (FETs). The high-performance 2D electronics requires high-quality integration of high-
Efficiently and fast seeking specific lattices with targeted phonon thermal conductivity
MXenes have wide applications in energy storage devices because of their compositional diversity. Electronic and optical properties, Bader charge and quantum capacitance of Janus ScHfCO2 MXene under biaxial strain are studied by density functional theory (DFT). The substitution of Hf atoms induces the decrease of the band gap of ScHfCO2, which changes from direct semiconductor into indirect semiconductor. Band gap generally increases with the increase of the tensile strain because of the blueshift of Sc-d and Hf-d orbits, and ScHfCO2 changes to M→K indirect semiconductor at
The rational design of high-performance bifunctional electrocatalysts toward both oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) is critical for the development of high-efficiency zinc−air batteries (ZABs). Herein, we report a facile method to synthesize a bifunctional electrocatalyst (FeNC/LDHs), which consists of Fe-doped hollow carbon dodecahedron (FeNC) coupling with NiFe-layered double hydroxides (LDHs). The coupling integration of FeNC dodecahedra and LDH nanosheets enriches the electrochemically active surface area and modulates the electron redistribution via oxygen bridges between FeNC and LDHs, thus effectively improving electrocatalytic activity and exhibiting a small potential difference of ΔE = 0.68 V during the ORR and OER process. The optimized FeNC/LDH-21 as a cathode in zinc-air batteries demonstrates a specific capacity of 810 mAh·g−1 at 10 mA·cm−2 and a power density of 85 mW·cm−2, and stable operation over 160 h. Moreover, the as-assembled solid-state flexible ZAB reaches a power density of 32.4 mW·cm−2 and maintains a stable charge-discharge process at different bending or hammering states. This work opens an avenue for the facile and large-scale synthesis of bifunctional electrocatalysts and would propel the practical application of ZABs.
In materials science, data-driven methods accelerate material discovery and optimization while reducing costs and improving success rates. Symbolic regression is a key to extracting material descriptors from large datasets, in particular the Sure Independence Screening and Sparsifying Operator (SISSO) method. While SISSO needs to store the entire expression space to impose heavy memory demands, it limits the performance in complex problems. To address this issue, we propose a RF-SISSO algorithm by combining Random Forests (RF) with SISSO. In this algorithm, the Random Forests algorithm is used for prescreening, capturing non-linear relationships and improving feature selection, which may enhance the quality of the input data and boost the accuracy and efficiency on regression and classification tasks. For a testing on the SISSO’s verification problem for 299 materials, RF-SISSO demonstrates its robust performance and high accuracy. RF-SISSO can maintain the testing accuracy above 0.9 across all four training sample sizes and significantly enhancing regression efficiency, especially in training subsets with smaller sample sizes. For the training subset with 45 samples, the efficiency of RF-SISSO was 265 times higher than that of original SISSO. As collecting large datasets would be both costly and time-consuming in the practical experiments, it is thus believed that RF-SISSO may benefit scientific researches by offering a high predicting accuracy with limited data efficiently.
In this study, TiN/NbOx/Pt memristor devices with short-term memory (STM) and self-rectifying characteristics are used for reservoir computing. The STM characteristics of the device are detected using direct current sweep and pulse transients. The self-rectifying characteristics of the device can be explained by the work function differences between the TiN and Pt electrodes. Furthermore, neural network simulations were conducted for pattern recognition accuracy when the conductance was used as the synaptic weight. The emulation of synaptic memory and forgetfulness by short-term memory effects are demonstrated using paired-pulse facilitation and excitatory postsynaptic potential. The efficient training reservoir computing consisted of all 16 states (4-bit) in the memristor device as a physical reservoir and the artificial neural network simulation as a read-out layer and yielded a pattern recognition accuracy of 92.34% for the modified National Institute of Standards and Technology dataset. Finally, it is found that STM and long-term memory in the device coexist by adjusting the intensity of pulse stimulation.
Incorporating valley as a degree of freedom into quantum anomalous Hall systems offers a novel approach to manipulating valleytronics in electronic transport. Using the Kane−Mele monolayer as a concrete model, we comprehensively explore the various topological phases in the presence of inequivalent exchange fields and reveal the roles of the interfacial Rashba effect and external electric field in tuning topological valley-polarized states. We find that valley-polarized states can be realized by introducing Kane−Mele spin−orbit coupling and inequivalent exchange fields. Further introducing Rashba spin−orbit coupling and an electric field into the system can lead to diverse topological states, such as the valley-polarized quantum anomalous Hall effect with
Topologically protected states are important in realizing robust optical behaviors that are quite insensitive to local defects or perturbations, which provide a promising solution for robust photonic integrations. Here, we propose to implement fast topological beam splitters and routers via the adiabatic passage of edge and interface states in the cross-linking configuration of Su–Schrieffer–Heeger (SSH) chains with interface defects. The channel state does not immerse into the band continuum during the adiabatic cycle, making the adiabatic restriction less stringent and the transport process more efficient. Based on the accelerated topological pumping, the beam splitters and routers exhibit improved robustness against losses of the system yet degraded resilience to fluctuation of coupling strengths and on-site energies compared with the conventional topological splitting and routing schemes. In addition, we confirm that the model demonstrates good scalability when the system size is varied. The simulation results of topological beam splitting in coupled waveguide arrays are in good consistency with theoretical analysis. This topological design provides a robust way to control photons, which may suggest further application of topological devices with unique properties and functionalities for integrated photonics.
Superconducting critical temperature is the most attractive material property due to its impact on the applications of electricity transmission, railway transportation, strong magnetic fields for nuclear fusion and medical imaging, quantum computing, etc. The ability to predict its value is a constant pursuit for condensed matter physicists. We developed a new hierarchical neural network (HNN) AI algorithm to resolve the contradiction between the large number of descriptors and the small number of datasets always faced by neural network AI approaches to materials science. With this new HNN-based AI model, a much-increased number of 909 universal descriptors for inorganic compounds, and a dramatically cleaned database for conventional superconductors, we achieved high prediction accuracy with a test R2 score of 95.6%. The newly developed HNN model accurately predicted
Results of the Raman scattering experiments, heat capacity measurements, ab initio simulations of the Raman spectra and pressure-induced phase transition in UTe2 single crystal are reported. Assignment of symmetries to particular Raman-active phonons follows directly from a comparative analysis of the measured and calculated Raman spectra. Theoretically determined lattice contribution to the specific heat of UTe2 allows for better description of its heat capacity measured over the temperatures ranging from 30 to 400 K. The orthorhombic-to-tetragonal phase transition pressure of 3.8 GPa is predicted at room temperature in very good agreement with the recent experimental studies. The phase transition remains almost phonon-independent with the transition pressure weakly temperature-dependent below 500 K. The strong local Coulomb correlations between U-5f electrons and spin−orbit interaction are shown to be important for realistic theoretical description of phonons and pressure-induced phase transition in UTe2.
One of unique features of non-Hermitian systems is the extreme sensitive to their boundary conditions, e.g., the emergence of non-Hermitian skin effect (NHSE) under the open boundary conditions, where most of bulk states become localized at the boundaries. In the presence of impurities, the scale-free localization can appear, which is qualitatively distinct from the NHSE. Here, we experimentally design a disordered non-Hermitian electrical circuits in the presence of a single non-Hermitian impurity and the nonreciprocal hopping. We observe the anomalous scale-free accumulation of eigenstates, opposite to the bulk hopping direction. The experimental results open the door to further explore the anomalous skin effects in non-Hermitian electrical circuits.
Non-Hermitian properties play an important role in topological acoustic systems, which can not only change the band topology but may also lead to novel applications such as non-Hermitian skin effect (NHSE). However, non-Hermitian systems, which are more closely related to real-world systems due to inevitable losses or gains, present challenges to topological classifications and boundary correspondence. Here, we demonstrate a topological monomodes based on one-dimensional (1D) Su−Schrieffer−Heeger (SSH) chains subject to non-Hermitian loss influences, which is achieved through tuning and introducing loss in the coupled acoustic cavity system. Moreover, we have extended this phenomenon from low-dimensional to high-dimensional systems. Theoretical and simulation results indicate that monomode can still be observed in non-Hermitian acoustic high-dimensional models, challenging the notion that topological states can only occur in pairs. More importantly, we have simulated the acoustic topological monomodes under non-Hermitian high-dimensional systems using acoustic local density of states (LDOS). Theoretical and simulation results demonstrate that local density of states can be used to calculate fractional charge modes and characterize topological monomodes in non-Hermitian acoustic systems. Our findings may have significant implications for the characterization of topology in non-Hermitian acoustic systems. This discovery offers a new perspective and approach to the study of non-Hermitian acoustic topology.
In our study, we explore high-order exceptional points (EPs), which are crucial for enhancing the sensitivity of open physical systems to external changes. We utilize the Hilbert−Schmidt speed (HSS), a measure of quantum statistical speed, to accurately identify EPs in non-Hermitian systems. These points are characterized by the simultaneous coalescence of eigenvalues and their associated eigenstates. One of the main benefits of using HSS is that it eliminates the need to diagonalize the evolved density matrix, simplifying the identification process. Our method is shown to be effective even in complex, multi-dimensional and interacting Hamiltonian systems. In certain cases, a generalized evolved state may be employed over the conventional normalized state. This necessitates the use of a metric operator to define the inner product between states, thereby introducing additional complexity. Our research confirms that HSS is a reliable and practical tool for detecting EPs, even in these demanding situations.
Vibrational resonances are ubiquitous in various nonlinear systems and play crucial roles in detecting weak low-frequency signals and developing highly sensitive sensors. Here we demonstrate vibrational resonance, for the first time, utilizing a single-ion phonon laser system exhibiting Van der Pol-type nonlinearity. To enhance the response of the phonon laser system to weak signals, we experimentally realize continuously tunable symmetry of the bistability in the phonon laser system via optical modulation, and achieve the maximum vibrational resonance amplification of 23 dB. In particular, our single-ion phonon laser system relaxes the frequency separation condition and exhibits the potential of multi-frequency signal amplification using the vibrational resonance. Our study employs the phonon laser to study and optimize the vibrational resonance with simple and well-controllable optical technology, which holds potential applications in developing precision metrology and single-ion sensors with on-chip ion traps.
Dual-polarization (DP) vortex waves (VWs) are widely applied in optical, electromagnetic, and quantum science owing to their ability to simultaneously convey two distinct and non-interfering orbital angular momentums (OAMs). Here, we propose a lightweight levitated meta-atom to achieve 360° phase control with a difference of no more than 1° while maximizing the reflection efficiency. In combination with convergent phase modulation, a OAM metasurface array that facilitates the generation of DP VWs with high mode purity and low divergence angles was designed. The measured DP VW bearing mode l = 1 had only 4° divergence angle and 84% mode purity at 5.8 GHz. Furthermore, DP VWs with integer, fractional (l = 1.5) and higher order (l = 8) modes are discussed based on an OAM purity spectrum analysis. The experimental results were consistent with the simulation results, demonstrating the practicality of the proposed DP OAM metasurface and its potential applications in the field of multithreaded communication systems.
Laser has become a powerful tool to manipulate micro-particles and atoms by radiation pressure or photophoretic force, but its effectiveness for large objects is less noticeable. Here, we report the direct observation of unusual light-induced attractive forces that allow manipulating centimeter-sized curved absorbing objects by a light beam. This force is attributed to the radiometric effect caused by the curvature of the vane and its magnitude and temporal responses are directly measured with a pendulum. Simulations suggest that the force arises from the bending of the vane, which results in a temperature difference of gas molecules between the concave and convex sides due to unbalanced gas convection. This large force (~4.4 μN) is sufficient to rotate a motor with four curved vanes at speeds up to 600 r/min and even lifting a large vane. Manipulating macroscopic objects by light could have significant applications for solar radiation-powered near-space propulsion systems and for understanding the mechanisms of negative photophoretic forces.
Early studies on Rayleigh−Taylor instability (RTI) primarily relied on the Navier−Stokes (NS) model. As research progresses, it becomes increasingly evident that the kinetic information that the NS model failed to capture is of great value for identifying and even controlling the RTI process; simultaneously, the lack of analysis techniques for complex physical fields results in a significant waste of data information. In addition, early RTI studies mainly focused on the incompressible case and the weakly compressible case. In the case of strong compressibility, the density of the fluid from the upper layer (originally heavy fluid) may become smaller than that of the surrounding (originally light) fluid, thus invalidating the early method of distinguishing light and heavy fluids based on density. In this paper, tracer particles are incorporated into a single-fluid discrete Boltzmann method (DBM) model that considers the van der Waals potential. By using tracer particles to label the matter-particle sources, a careful study of the matter-mixing and energy-mixing processes of the RTI evolution is realized in the single-fluid framework. The effects of compressibility on the evolution of RTI are examined mainly through the analysis of bubble and spike velocities, the ratio of area occupied by heavy fluid, and various entropy generation rates of the system. It is demonstrated that: (i) compressibility has a suppressive effect on the spike velocity, and this suppressive impact diminishes as the Atwood number (
