Fast Operation Speed Research Articles

Electrical Detection of Acoustic Antiferromagnetic Resonance in Compensated Synthetic Antiferromagnets.

Compensated synthetic antiferromagnets (SAFs) stand out as promising candidates to explore various spintronic applications, benefitting from high precession frequency and negligible stray field. High-frequency antiferromagnetic resonance in SAFs, especially the optic mode (OM), is highly desired to attain fast operation speed in antiferromagnetic spintronic devices. SAFs exhibit ferromagnetic configurations above saturation field; however in that case, the intensity of OM is theoretically zero and hard to be detected in well-established microwave resonance experiments. To expose the hidden OM, the exchange symmetry between magnetic layers must be broken, inevitably introducing remanent magnetization. Here, we experimentally demonstrate a feasible method to break the symmetry via surface acoustic waves with the maintenance of compensated SAF structure. By introducing an out-of-plane strain gradient inside the Ir-mediated SAFs, we successfully reveal the hidden OM. Remarkably, the OM intensity can be effectively modulated by controlling strain gradients in SAFs with different thicknesses, confirmed by finite-element simulations. Our findings provide a feasible scheme for detecting the concealed OM, which would trigger future discoveries in magnon-phonon coupling and hybrid quasiparticle systems.

Optimization of target detection model based on Yolov5 network with small samples

As an important part of automotive shock absorber, the columnar parts in automotive shock absorber will inevitably have machining defects during the process, which will not only degrade the performance of the parts, but also degrade or even fail the performance of the final shock absorber after assembly. Yolov5, as a target detection algorithm, has received much attention due to its high accuracy and fast operation speed. However, the algorithm faces some challenges when applied in a practical industrial environment. In this paper, improvement measures are proposed to address the limitations of sample collection and the high speed of pipeline recognition in industrial environments. The network model is optimized and designed. Firstly, the ASPP module is replaced by the SPP module thus improving the viewability throughout the process providing recognition accuracy. Secondly, the Conv and C3 layers of Yolov5s are replaced by Transformer to obtain higher recognition accuracy. By improving and optimizing the above methods, we can better cope with the improvement of detection accuracy under small sample conditions. Experiments show that the method can significantly improve the detection accuracy and operation speed of Yolov5s under the hardware condition of lower computing power, which is more suitable for industrial scenario application scenarios.

Investigation for AGZO RRAM using the RF Co-sputtering method

Recently, the Internet of Things (IOT) has rapidly developed, leading to the development of many smart devices. Moreover, artificial intelligence (AI) and 5G communication are successful, and the demand for high-performance memory is increasing. The emerging nonvolatile RRAM has many advantages, such as low power consumption, fast operation speed, simple structure and excellent scalability, compared with traditional memories; this is promising for complex computing and mass storage. Zinc oxide (ZnO) is a promising candidate for transparent conducting oxide (TCO) applications because of its abundance, high conductivity, low toxicity, and cost-effectiveness. It is currently used in various optoelectronic components including thin-film transistors (TFTs) and photodetectors. Notably, TCO has been increasingly used in the switching layers of random resistive access memory systems. In this paper, we intend to combine AGO with a large energy gap and ZnO with a high conductivity to prepare AGZO as a switching layer for RRAM by co-sputtering. By adjusting the oxygen flow ratio and power of co-sputtering, the AGZO RRAM exhibited high performance with more than 1400 switching cycles, 102–103 on/off ratio, and low operation voltage, and high- and low-resistance states could be maintained for more than 10,000[Formula: see text]s.

Multilevel resistive switching in hydrothermally synthesized FeWO4 thin film-based memristive device for non-volatile memory application

The memristors offer significant advantages as a key element in non-volatile and brain-inspired neuromorphic systems because of their salient features such as remarkable endurance, ability to store multiple bits, fast operation speed, and extremely low energy usage. This work reports the resistive switching (RS) characteristics of the hydrothermally synthesized iron tungstate (FeWO4) based thin film memristive device. The detailed physicochemical analysis was investigated using Rietveld’s refinement, X-ray photoelectron spectroscopy (XPS), field emission scanning electron microscopy (FE-SEM), and transmission electron microscopy (TEM) techniques. The fabricated Ag/FWO/FTO memristive device exhibits bipolar resistive switching (BRS) behavior. In addition, the devices exhibit negative differential resistance (NDR) at both positive and negative bias. The charge-flux relation portrayed the non-ideal or memristive nature of the devices. The reliability in the RS process was analyzed in detail using Weibull distribution and time series analysis techniques. The device exhibits stable and multilevel endurance and retention characteristics which demonstrates the suitability of the device for the high-density non-volatile memory application. The current conduction of the device was dominated by Ohmic and trap controlled-space charge limited current (TC-SCLC) mechanisms and filamentary RS process responsible for the BRS in the device. In a nutshell, the present investigations reveal the potential use of the iron tungstate for the fabrication of memristive devices for the non-volatile memory application.

High performance antimony-rich RexSb3Te for phase-change random access memory applications

Phase-change random access memory (PCRAM) demands for high-performance phase change materials, including operation speed, data retention, resistance drift etc. In this work, a high performance PCRAM device based on antimony-rich RexSb3Te material was put forward and studied. Excellent data retention, fast operation speed, low resistance drift, low power consumption and good cycle characteristics were achieved. The lattice information, bonding properties and surface morphology of the films were characterized by transmission electron microscopy, Raman spectroscopy and atomic force microscopy. Density functional theory calculations show that the Re dopant is more inclined to replace Sb and forms chemical bonds with Te, and the Re-Te bonds are more stable than the previous Sb-Te bonds, which is conducive to the formation of stable precursors to accelerate nucleation. The research shows that the antimony-rich Re0.18Sb3Te material has good overall performance, which provides a strategy for developing high-performance memory.

Gate-Tunable Multiband van der Waals Photodetector and Polarization Sensor.

A single photodetector with tunable detection wavelengths and polarization sensitivity can potentially be harnessed for diverse optical applications ranging from imaging and sensing to telecommunications. Such a device will require the combination of multiple material systems with different structures, band gaps, and photoelectrical responses, which is extremely difficult to engineer using traditional epitaxial films. Here, we develop a multifunctional and high-performance photosensor using all van der Waals materials. The device features a gate-tunable spectral response that is switchable between near-infrared/visible and short-/midwave infrared, as well as broad-band operation, at room temperature. The linear polarization sensitivity in the telecommunication O-band can also be directly modulated between horizontal, vertical, and nonpolarizing modes. These effects originate from the balance of photocurrent generation in two of the active layers that can be manipulated by an electric field. The photodetector features high detectivity (>109 cmHz1/2W-1) together with fast operation speed (∼1 MHz) and can be further exploited for dual visible and infrared imaging.

Fast-speed and low-power-consumption optical phased array based on lithium niobate waveguides

Abstract Fast scanning speed and low-power consumption are becoming progressively more and more important in realizing high-performance chiplet optical phased arrays (OPAs). Here, we successfully demonstrated integrated OPAs with multiple waveguides channels based on thin-film lithium niobate-on-insulator (LNOI) platform. Specifically, two lithium niobate (LN) OPA chips have been implemented with 32 and 48 channels LN waveguides, respectively, enabled by electro-optic modulations, which showcases the low power consumption (1.11 nJ/π) and fast operation speed (14.4 ns), showing obvious advantage of the LNOI platform over others. As results, we experimentally achieved a beam steering with a 62.2° × 8.8° field of view (FOV) and a beam divergence of 2.4° × 1.2° for 32 channels, and a FOV of 40° × 8.8° and a beam divergence of 0.33° × 1.8° for 48 channels. This work also demonstrates the feasibility of LNOI platform in scalable OPA chips.

Ferroelectric tunnel junctions: promise, achievements and challenges

Abstract Ferroelectric tunnel junctions (FTJs) have been the subject of ongoing research interest due to its fast operation based on the spontaneous polarization direction of ultrathin ferroelectrics and its simple two-terminal structure. Due to the advantages of FTJs, such as non-destructive readout, fast operation speed, low energy consumption, and high-density integration, they have recently been considered a promising candidate for non-volatile next-generation memory. These characteristics are essential to meet the increasing demand for high-performance memory in modern computing systems. In this review, we explore the basic principles and structures of FTJs and clarify the elements necessary for the successful fabrication and operation of FTJs. Then, we focus on the recent progress in perovskite oxide, fluorite, 2-dimensional van der Waals, and polymer-based FTJs and discuss ferroelectric materials expected to be available for FTJs use in the future. We highlight various functional device applications, including non-volatile memories, crossbar arrays, and synapses, utilizing the advantageous properties of ferroelectrics. Lastly, we address the challenges that FTJ devices currently face and propose a direction for moving forward.

A pilot protection based on low frequency component model for HVDC transmission lines

AbstractReliable and fast identification of high‐voltage direct current (HVDC) transmission line faults is important to the safety of power system. In traditional DC transmission line protection, differential protection is invulnerable to high fault resistance, but it needs long time delay for the influence of distributed capacitance current. In order to solve this problem, a novel pilot protection is proposed. The characteristics of the voltage and current processed by low‐pass filter under different fault conditions are analysed, and based on it the protection criteria is proposed. When external fault occurs, it reflects the line capacitance where the first forward fault traveling wave passes, which is increasing until equal to the whole line capacitance, then remains constant. However, when internal fault occurs, its value is negative in the initial stage, and after that its value is very different from the whole line capacitance. The analysis proves that this pilot protection method has fast operation speed, and can be applied for a relatively long period of time. What is more, the applicable time of superposition principle is considered in the analysis, which is not considered in many literatures. An UHVDC system is modelled for simulation in PSCAD/EMTDC, and the correctness and effectiveness of the proposed scheme is verified.

Highly reliable bipolar resistive switching of tantalum oxide-based memory using Al2O3 diffusion barrier layers

We present a novel bipolar resistive switching memory based on TaOx, featuring a Ru/Al2O3/Ta2O5/TaOx/Al2O3/W structure. Thin Al2O3 layers play a crucial role as diffusion barriers, preventing undesirable interfacial reactions at the top and bottom interfaces. They support the stable formation of the Schottky barrier near the Ru top electrode through redox reactions during operation, resulting in highly reliable bipolar resistive switching. The device exhibits excellent memory performance, including a fast operation speed (∼10 ns), good switching endurance (∼106 cycles), and robust data retention (>104 s at 200 °C).

Efficiency Improvement Mechanism of Smart Logistics Technology in Rural E-commerce Logistics and Distribution

Abstract This paper addresses the problems existing in the current two-way logistics and distribution model of rural e-commerce and proposes the study of rural e-commerce distribution efficiency with the technical support of intelligent logistics. Based on the knowledge of multi-objective optimization theory, the maximization of distribution efficiency of logistics enterprises and the maximization of demand coverage as the objective function, while the constraints are vehicle load, service time, path constraints, and finally, complete the construction of the multi-objective optimization model of rural e-commerce logistics and distribution efficiency. According to the NSGA-II algorithm with low computational complexity, fast operation speed, and good convergence, the NSGA-II algorithm is used to solve the constructed model, and then the optimal solution of rural e-commerce logistics distribution efficiency is derived. With regional logistics as the research subject, a multi-objective optimization model for rural e-commerce logistics distribution efficiency supported by intelligent logistics technology is simulated and analyzed. The data show that compared with other algorithms, the NSGAII algorithm has a smoother learning curve oscillation, while the final result of convergence (-1.473), the objective function is smaller (20.42), and the optimal total transportation time is smaller (609.22s). Finally, in order to solve the current rural e-commerce logistics and distribution problems in part, from the improvement of rural e-commerce logistics and distribution system, strengthen the rural logistics infrastructure construction of the two aspects of rural e-commerce logistics and distribution efficiency improvement strategy.

Chaotic time delay feature cancellation and bandwidth enhancement in cascaded-coupled nanolasers

As an important part of optical sources, nanolasers have a prominent influence in photonic circuit integration, and their nonlinear dynamics has become one of the research hotspots in recent years. In this work, we investigate the time-delay signature and bandwidth characteristics in a cascade-coupled nanolaser system, in which the master nanolaser is connected to an external feedback cavity and injected into the intermediate nanolaser and the slave nanolaser sequentially. The 0-1 chaos test is introduced to quantify the dynamics of the nanolaser, which can accurately distinguish whether the laser is in a chaotic state, and the autocorrelation function is used to analyze the time-delay characteristics in the laser output signal. This type of calculation has the advantages of fast operation speed, high accuracy and anti-noise robustness. The lower the autocorrelation value, the more difficult it is to extract useful information from the chaotic random sequence. The bandwidth is defined as a value where the range between DC and frequency contains 80% of the spectral power, a value that is only applicable to chaotic states. In the simulation, we compare and analyze the two cases of whether the intermediate nanolaser has a peak with obvious time-delay signature. The research results show that by selecting appropriate system parameters, the slave nanolaser can always output a broadband chaotic signal without obvious time-delay signature. Under the condition of a certain injection intensity, by changing the frequency detuning parameter, the intermediate nanolaser has an obvious time-delay signature, and then the slave nano-laser can output chaotic signals which can suppress time-delay signature and enhance bandwidth in a small parameter interval. When the time-delay signal of the intermediate nanolaser is completely hidden, the slave nanolaser can achieve the suppression of the time-delay signature in a larger parameter plane, meanwhile the bandwidth is significantly enhanced. In addition, by plotting the two-dimensional spatial distribution diagram and bandwidth line diagram of the output from the nanolaser under frequency detuning and injection intensity, it is determined that the nanolaser can simultaneously suppress the delay characteristics and enhance the bandwidth under chaotic signals. This provides an important theoretical basis for realizing the practical applications in secrecy-enhanced chaotic optical communication.

Giant Electroresistance in Ferroelectric Tunnel Junctions via High-Throughput Designs: Toward High-Performance Neuromorphic Computing.

Ferroelectric tunnel junctions (FTJs) have been regarded as one of the most promising candidates for next-generation devices for data storage and neuromorphic computing owing to their advantages such as fast operation speed, low energy consumption, convenient 3D stack ability, etc. Here, dramatically different from the conventional engineering approaches, we have developed a tunnel barrier decoration strategy to improve the ON/OFF ratio, where the ultrathin SrTiO3 (STO) dielectric layers are periodically mounted onto the BaTiO3 (BTO) ferroelectric tunnel layer using the high-throughput technique. The inserted STO enhances the local tetragonality of the BTO, resulting in a strengthened ferroelectricity in the tunnel layer, which greatly improves the OFF state and reduces the ON state. Combined with the optimized oxygen migration, which can further manipulate the tunneling barrier, a record-high ON/OFF ratio of ∼108 has been achieved. Furthermore, utilizing these FTJ-based artificial synapses, an artificial neural network has been simulated via back-propagation algorithms, and a classification accuracy as high as 92% has been achieved. This study screens out the prominent FTJ by the high-throughput technique, advancing the tunnel layer decoration at the atomic level in the FTJ design and offering a fundamental understanding of the multimechanisms in the tunnel barrier.

A Way to Optimize Delay of Carry-Skip Adders by Using Blocks of Variable Sizes

As one of the most common operational modules in computer processors, the optimization of the propagation delay of adders has attracted extensive attention of researchers. This article proposes a method of optimizing the delay of carry-skip adders by using blocks of variable sizes. By increasing the sizes of the bypass stages gradually and then decreasing it stage by stage, keeping the delay of the first and last stage short, the total propagation delay is optimized. Compared with fixed size carry-skip adders, the delay of variable sizes carry-skip adders has a square root relationship with the number of bits. Thus, when the number of bits is large, the propagation delay is significantly reduced. After calculation, when the number of bits is 16, the propagation delay decreases by 16.67%, and when the number of bits is 256, it decreases by 52.78%. Due to the shorter propagation delay, variable sizes carry-skip adders have faster operation speed and can be applied to improve the performance of computer processors.

High speed and high reliability phase transition via constrained crystallization in ultrathin a-C/Sb2Te multilayer nanostructures

Operation speed, data retention, thickness variation, and resistance drift are main shortages for conventional Ge2Sb2Te5 based phase change memory (PCM). In this Letter, we propose a type of ultrathin amorphous carbon (a-C)/Sb2Te multilayer nanostructures with semiconductor process compatibility, which has high speed and excellent reliability in terms of data retention (131 °C for 10-year), thickness variation (1.52%), and resistance drift (0.0095). The PCM devices based on [a-C (1 nm)/Sb2Te (7 nm)]5 multilayer nanostructures exhibit a fast operation speed of 5 ns. The SET/RESET resistance ratio remains constant over 105 cycles by more than two orders of magnitude. The excellent performance of a-C/Sb2Te multilayer nanostructures makes it a promising storage medium to expand the applications of PCM, such as automotive electronics.

On-chip wavefront shaping in spacing-varied waveguide arrays

Abstract The ability to manipulate light propagation sets the foundations for optical communication and information processing systems. With the ever-growing data capacity and data rate, photonic integrated circuits have attracted increasing attentions of researchers owing to their large-volume integration capacity and fast operation speed. In this work, we proposed and experimentally demonstrated a new wavefront shaping method using waveguide arrays with hyperbolic secant refractive index profiles. Through theoretically analyzing the diffraction and coherence properties, we found that a single waveguide array can perform both imaging and phase transformation, which are the two primary functions of optical lenses. We further expanded this function and fabricated the corresponding devices on a silicon nitride waveguide platform. Deterministic beam shaping, such as focusing, expansion, collimation, and steering, is successfully realized. This wavefront control method exhibits the potential for on-chip optical routing, ranging, sensing, etc., with high integration density and scalability.

Fast, Energy‐Efficient InGaAs Synaptic Phototransistors on Flexible Substrate

AbstractPhotodetectors sensing the short‐wave infrared (SWIR) region have great potential due to their significant advantages in a variety of applications because SWIR light possesses both characteristics of visible light and infrared light. Among them, devices using photodetectors to mimic synaptic dynamics and functions have received a great deal of attention due to their capabilities to implement simplified neural systems. However, it is essential to develop synaptic devices that can operate fast with low energy consumption for more efficient implementation of neural systems. Here, a flexible InGaAs synaptic phototransistor with a fast operation speed of under 1 ms and low energy consumption in the atto joule level is developed to femto joule level which is superior to biological synapses (50 ms, 1–100 fJ). By using InGaAs which has high carrier mobility as a channel layer, weak light, and short optical pulse width, fast operation speed in the SWIR region with low energy consumption is obtained. Moreover, the devices demonstrate synaptic behaviors such as “excitatory post synaptic current”, “paired‐pulse facilitation”, “short term plasticity”, “long term plasticity”, and “learning‐experience behavior” as neuro‐synaptic applications. These results provide the possibilities for implementation of complex synaptic functions with fast speed and low power SWIR synaptic phototransistors.

Performance optimization of Sn15Sb85 phase change material via introducing multilayer structure

The superlattice-like Sn15Sb85/Ti phase change films were fabricated by magnetron sputtering, and the effects of Ti layer on the phase change properties and crystal structure of the Sn15Sb85 films were systematically researched. With the addition of Ti layers, the crystallization temperature of the films increased, indicating their thermal stability and data retention were improved. X-ray diffraction results reflect that the presence of Ti layers restrains grain growth and refines grain size. X-ray photoelectron spectroscopy analysis reveals that the incorporation of Ti layers enhances the interatomic binding energy and improves the stability. X-ray reflectivity analysis and atomic force microscopy indicate that the Sn15Sb85/Ti films have smaller volume change and smoother surface than pure Sn15Sb85 films, implying the better interfacial property and reliability. The T-type phase change memory cell based on Sn15Sb85/Ti thin film has faster operation speed (100 ns) and lower power consumption (2.6 ×10−12 J) than the conventional Ge2Sb2Te5 material. The results show that the superlattice-like Sn15Sb85/Ti film will be a potential candidate with outstanding properties in thermostability and power consumption.

Non-volatile reconfigurable spin logic functions in a two-channel Hall bar by spin–orbit torque-based magnetic domains and directional read current

A long-standing goal of CMOS-based logic devices is to meet the needs of key markets, including ultralow-power operation and high operation speed, along with the continuing miniaturization of the architecture. However, despite significant progress in their development, conventional CMOS-based devices still suffer from drawbacks such as introducing large unintended leakage currents and volatile behavior. Thus, reconfigurable logic gates based on magnetic domain (MD) have emerged as a highly promising option because they offer fast operation speeds, nonvolatility, and diverse logic functions in a single-device configuration. Here, we address multiple reconfigurable MD logic gates in a single two-channel Hall bar device by varying the voltage-driven read-current directions and selecting a non-inverting or inverting comparator in W/CoFeB/MgO/Ta stacks. The non-volatile MD switching behavior induced by spin–orbit torque significantly affects our logic gate functions, which are not necessarily synchronized to a single clock. By adapting MD switching by spin-orbit torque and anomalous Hall effect voltage outputs, we identified eight reconfigurable logic gates, including AND, NAND, NOR, OR, INH, Converse INH, Converse IMP, and IMP, in a single device. These experimental findings represent a significant step forward in a wide range of MD-based logic applications in the near future.

Application of k-sigma Algorithm Based on Monte Carlo in Outlier Detection

Under the background of intelligent times based on information technology, the analysis and replacement of outliers become particularly critical for databases in the face of massive sequential data streams. In order to improve the effectiveness and practicability of the detection method, this paper determines the abnormal scores of data points in a specific data set by using the K-Sigma algorithm of the Monte Carlo method, adaptively adjusts the k value according to the abnormal scores, and marks the abnormal points.The advantages of the traditional k-sigma algorithm are fast operation speed and theoretical basis, while the disadvantages are that each index dimension is determined independently. However, in industrial production, due to the multi-index dimension of time series data, multiple size indicators of a data set are related to each other. Therefore, it is necessary to comprehensively consider whether an anomaly is abnormal by combining it with the data of other indicators. In addition, when there are no outliers in the data set, the traditional k-sigma algorithm is used to take the mean and variance of the data set as parameters. Due to the limitations of the data set itself, some data points will be mislabeled as outliers. Through the k-sigma algorithm based on the Monte Carlo method, we can effectively solve the above problems.The k-sigma algorithm based on the Monte Carlo method can generate a normal distribution according to the distribution of original data points, and extract a large quantity of data from the distribution to generate Monte Carlo data set. The Mahalanobis distance li from each sample point to the mean in the Monte Carlo data set is calculated and compared with the Mahalanobis distance lj from the samples to be detected to the mean in the original data set. According to the number of sample points satisfying li < lj in the Monte Carlo data set, the value of the parameter kj is determined adaptively, and thus the outliers are determined. We implemented the k-sigma algorithm based on the Monte Carlo method through python, evaluated the effectiveness of the algorithm by accuracy, recall rate, and F1 score, and compared it with some machine learning algorithms. The results verified the feasibility and effectiveness of the algorithm, which can be used for real-time anomaly detection in the energy management database.