Simulation of Field Coupled Computing Architectures Based on Magnetic Dot Arrays

In this paper, we demonstrate that field-coupled nanomagnets can be used for digital information processing. The operation of logic devices is based on a QCA-like architecture, where information propagates by magnetostatic interaction between individual magnetic dots. Micromagnetic simulations indicate that simple logic gates function properly. Efficient design tools, based on the single-domain approximation are developed.     

Simulation of Power Gain and Dissipation in Field-Coupled Nanomagnets

Coupled nanomagnetic dots were proposed as a promising way to realize computing devices. This paper investigates power flow phenomena in these structures. Using micromagnetic simulations we will demonstrate that the power dissipation of those devices is close to the theoretical lowest limit of any computation and that coupled nanomagnets exhibit power gain, i.e. they are active devices. These results suggest that magnetic computing could be a functionally equivalent replacement of transistor-based circuits in signal processing applications, where robust, low-power operation is crucial.     

Field-coupled computing in magnetic multilayers

This paper presents a computational study of ion-beam patterned cobalt-platinum multilayers, which could be used for field-coupled computing. We use micromagnetic simulations to reproduce measured hysteresis curves. This parameterized micromagnetic simulator then will be used for simulating interacting magnetic dots. We demonstrate how logic gates can be built from such coupled dots. We also show how electrical wires—placed beneath or above the magnetic dots—can provide a magnetic field, which propagates the magnetic signals.     

Contiguous clock lines for pipelined nanomagnet logic

In this paper we study pipelined nanomagnet logic by simulating and comparing varying adjacent clock line structures. Unlike previous simulations, a realistic clock line shape is used in simulations to obtain a more accurate idea of whether or not these clock lines function properly. First, we simulate individual clock lines using Ansys Maxwell 2D according to the parameters of the fabricated clock lines. Then, these clock lines are placed adjacent to one another to simulate how data can propagate from one clock zone to another. Adjusting the clock line layer structure minimizes a dip in the magnetic field at the clock zone boundaries from 35% minimum below the clocking field to a 16% dip. These magnetic field profiles are then used in the object-oriented micromagnetic framework (OOMMF) to simulate lines of nanomagnets. By reducing the gap between contiguous clock lines, we show error free data propagation in the form of a ferromagnetically coupled line of nanomagnets.     

From materials to systems: a multiscale analysis of nanomagnetic switching

With the increasing demand for low-power electronics, nanomagnetic devices have emerged as strong potential candidates to complement present day transistor technology. A variety of novel switching effects such as spin torque and giant spin Hall offer scalable ways to manipulate nanosized magnets. However, the low intrinsic energy cost of switching spins is often compromised by the energy consumed in the overhead circuitry in creating the necessary switching fields. Scaling brings in added concerns such as the ability to distinguish states (readability) and to write information without spontaneous backflips (reliability). A viable device must ultimately navigate a complex multi-dimensional material and design space defined by volume, energy budget, speed, and a target read–write–retention error. In this paper, we review the major challenges facing nanomagnetic devices and present a multiscale computational framework to explore possible innovations at different levels (material, device, or circuit), along with a holistic understanding of their overall energy delay–reliability trade-off.     

Physics-based modeling approaches of resistive switching devices for memory and in-memory computing applications

The semiconductor industry is currently challenged by the emergence of Internet of Things, Big data, and deep-learning techniques to enable object recognition and inference in portable computers. These revolutions demand new technologies for memory and computation going beyond the standard CMOS-based platform. In this scenario, resistive switching memory (RRAM) is extremely promising in the frame of storage technology, memory devices, and in-memory computing circuits, such as memristive logic or neuromorphic machines. To serve as enabling technology for these new fields, however, there is still a lack of industrial tools to predict the device behavior under certain operation schemes and to allow for optimization of the device properties based on materials and stack engineering. This work provides an overview of modeling approaches for RRAM simulation, at the level of technology computer aided design and high-level compact models for circuit simulations. Finite element method modeling, kinetic Monte Carlo models, and physics-based analytical models will be reviewed. The adaptation of modeling schemes to various RRAM concepts, such as filamentary switching and interface switching, will be discussed. Finally, application cases of compact modeling to simulate simple RRAM circuits for computing will be shown.     

Piecewise empirical model (PEM) of resistive memory for pulsed analog and neuromorphic applications

With the end of Dennard scaling and the ever-increasing need for more efficient, faster computation, resistive switching devices (ReRAM), often referred to as memristors, are a promising candidate for next generation computer hardware. These devices show particular promise for use in an analog neuromorphic computing accelerator as they can be tuned to multiple states and be updated like the weights in neuromorphic algorithms. Modeling a ReRAM-based neuromorphic computing accelerator requires a compact model capable of correctly simulating the small weight update behavior associated with neuromorphic training. These small updates have a nonlinear dependence on the initial state, which has a significant impact on neural network training. Consequently, we propose the piecewise empirical model (PEM), an empirically derived general purpose compact model that can accurately capture the nonlinearity of an arbitrary two-terminal device to match pulse measurements important for neuromorphic computing applications. By defining the state of the device to be proportional to its current, the model parameters can be extracted from a series of voltages pulses that mimic the behavior of a device in an analog neuromorphic computing accelerator. This allows for a general, accurate, and intuitive compact circuit model that is applicable to different resistance-switching device technologies. In this work, we explain the details of the model, implement the model in the circuit simulator Xyce, and give an example of its usage to model a specific \(\hbox {Ta}/\hbox {TaO}_{\mathrm{x}}\) device.     

Designing digital circuits using 3D nanomagnetic logic architectures

The approach to designing digital circuits using three-dimensional (3D) perpendicular nanomagnetic logic (pNML) is thoroughly investigated. Nanomagnetic logic (NML) technology eventually optimizes the circuit performance in comparison with conventional metal–oxide–semiconductor (MOS) technology, which suffers from the hot carrier, velocity saturation, and short-channel effects, which may considerably degrade device performance. In contrast, nanomagnetic logic is immune to radiation; it behaves as nonvolatile memory and shows zero leakage current, as required for use in high-speed and low-cost nanoelectronics applications. In this paper, novel and organized designs, e.g., for 3D Ex-OR, parity generator, parity checker, multiplexer, and arithmetic logic unit (ALU) functionality, are synthesized using pNML technology. Previous designs are not compact in terms of delay, layer count, or bounded area. To overcome this, new designs for the mentioned functionalities are proposed based on pNML with smaller area and lower latency compared with previous circuits.

     

基于矩形亥姆霍兹线圈的大均匀区改进型三维磁场发生器设计与特性

为了克服传统磁场发生器空间利用率低的缺陷,提出了改进的三维磁场发生器,具有结构紧凑、更大的均匀区。相比传统的亥姆霍兹线圈,每个维度引入了一双辅助线圈。要设计这紧凑场发生器,五个模型参数需要根据用户的要求对均匀性进行优化。最后,研发了一台磁场发生器,用于测试新型线圈的性能以验证其设计方法。实验结果表明,测试的磁场结果与设计值吻合得很好,最大的设计偏差仅为0.12%。更重要的是,产生相同体积的均匀区,这种磁场发生器的体积仅为传统亥姆霍兹线圈的1/13.6。     

永磁装置中磁场力的计算

提供力学服务是永磁装置重要的用途之一,因而磁场力的计算是磁力机械设计、应用的重要内容.磁场力的计算有公式法和数值算法,本文结合两个具体实例对这两种算法进行了介绍,给出了计算结果,并与实测值进行比较.结果表明公式算法简单、方便,但计算误差较大;数值算法虽计算复杂,但精确、可靠.同时,文中对实例中的有限元数值算法提供了源程序,可供参考.     

基于RTDS的快速投切电容器自动装置投切策略研究

为了充分利用系统备用无功资源来提高电网受端动态无功补偿能力,较好地提高电压稳定性,文中基于快速投切电容器自动装置提出了投切电容器的控制策略。投切控制策略设置有系统故障识别逻辑、低压投入电容器逻辑和过压切除电容器逻辑。仿真平台采用数字实时仿真(RTDS)搭建了220 kV及以上系统实时仿真模型,分别连接实际直流控制保护装置与快速投切电容器自动装置,构成了双闭环实时仿真系统。通过设置多种试验项目,开展了不同故障工况下自动装置基本投切策略的试验研究,检验了投切策略的正确性和有效性,为装置的工程实施与应用提供了重要的技术指导。     

基于时域有限元方法的配电房大电流母排涡流场分析

母排工作状况对整个配电系统的运行起着决定性的作用.针对配电房普遍使用的平板型空气绝缘母排结构,根据母排实际尺寸、位置等参数构建其工频磁场分布的计算模型.采用基于时域有限元的方法研究了矩形大电流母排满足的二维(2D)、三维(3D)涡流场问题.分析其磁感应强度变化,并与圆管型母排进行了比较,通过仿真验证,矩形母排磁感应强度与实测数据的最大误差小于5.79%,而圆管型母排磁感应强度与实测数据的误差较大.重点研究了不同工作电流对电磁力、磁场能量及功率损耗的影响.结果显示随电流增大,磁场能量、电磁力及功率损耗均呈增加趋势.当电流为2 400 A时,其三维涡流场的功率损耗高达114.462 W/m.     

基于蛙跳模糊算法的Jiles Atherton铁心磁滞模型参数确定

Jiles Atherton(JA)模型广泛应用于铁心磁滞建模领域,其参数确定精确与否直接影响铁心磁滞现象的表达,为此提出蛙跳模糊算法对JA模型参数进行辨识。为了防止蛙跳算法陷入局部最优解并加快收敛速度,根据特殊点(矫顽力、矫顽力点磁化率)处实测值与计算值的相对误差,采用模糊控制方法,得到动态反馈系数,修正蛙跳算法的步长调整公式。采用爱泼斯坦方圈搭建磁滞回线测量系统,测得铁心饱和磁滞回线与局部磁滞回线。采用蛙跳模糊算法、蛙跳算法、粒子群算法和遗传算法分别求解得到模型参数,并将计算的磁滞回线与实测磁滞回线进行比较,证明了所提出的蛙跳模糊算法不易陷入局部最优解且具有更快的收敛速度。根据蛙跳模糊算法得到的局部磁滞回线模型参数辨识结果,研究模型参数与磁通密度的关系并进行拟合,得到不同磁通密度下的局部磁滞回线参数拟合模型。     

密集型母线槽磁场-温度场综合有限元分析

利用ANSYS有限元软件建立了密集型母线槽的磁场-温度场耦合分析模型,在计算涡流场的基础上得到焦耳热损耗,随后将焦耳热作为体积热源,通过顺序耦合方法准确地计算了密集型母线槽的温度场。耦合过程中引入了预估-校正法,以确保预估的母排和外壳温升值的合理性,从而保证焦耳热损耗和外壳对流散热系数的准确性。母排和外壳温升的计算结果与实验结果吻合得很好,误差在1.2K之内。     

Molecular electronics: strategies and progress in China

The field of molecular electronics is being used to explore a new generation of electronic devices and bionic information processing systems in China. Molecular research in China covers three different levels: (1) nanotechnology for molecular assembly in both fundamental and practical applications; (2) molecular devices for sensing, memory, switching, and actuation; (3) and theoretical studies on novel computing principles. In this article the authors review the main achievements in molecular electronics, but due to space limitations, it is impossible to cover all important results     

基于混合算法改进的采煤机采高仿人智能控制模型设计

为解决基于仿人智能控制的采煤机采高控制系统在模态转换时易发生边界突变、稳定性差、模态参数不易确定等问题,提出一种基于模糊逻辑改进模态切换,利用粒子群算法优化参数的仿人智能控制模型。该模型将仿人智能控制误差相平面的特征模态扩展为模糊集合,通过模糊逻辑推理跟随误差和误差变化实时地选择最优的控制模态,通过粒子群算法跟随误差和误差变化实时地调整控制模态参量。以阶跃响应模拟在煤岩界面遇见断层的控制性能仿真实验表明,本文所提出的仿人智能控制模型相较于原始仿人智能控制算法稳定时间提高了4.71s、上升时间提高了0.345s、峰值时间提高了0.671s、超调量降低了5.458%。本文提出的模型在系统模态转换时的稳定性、快速性、鲁棒性及参数寻优方面均好于其他控制模型,具有优越性。     

Modeling and simulation of photon-coupled,fluorescent photoswitchable protein logic

Today's society has an ever-increasing demand for smaller-scale, lower-energy-consuming, cheaper, and faster computing and digital signal processing systems. Photon-coupled, fluorescent photoswitchable protein-based architectures are promising candidates for the fulfillment of these requirements. In order to properly design digital circuits based on the aforementioned building blocks, an efficient simulation procedure is needed. We present a simple, differential equation-based model, suitable for the design and simulation of such structures. It characterizes the radiation-induced switching, the form-dependent fluorescence, and the effect of photon coupling in a fast and efficient manner. The applicability of the model is demonstrated through simulations of the OR and NOR logic gates consisting of readily available, fluorescent photoswitchable proteins. It can be a potential design tool for future molecular logic circuitry based on such molecules.     

Modeling of dipole–dipole‐coupled,electric field‐driven,protein‐based computing architectures

In the present study, we propose a novel approach for the realization of protein‐based logic circuits potentially suitable for nanoscale digital signal processing and computing architectures. Electric field‐induced switching of Dronpa, an artificial protein, is demonstrated through simulations with the NAMD molecular dynamics simulation software, and a circuit model that describes such switching behavior is presented. Simulations suggest that digital signal propagation and the majority gate can be realized by the utilization of such proteins if they are dipole–dipole coupled and are driven by proper electric fields. Copyright © 2013 John Wiley & Sons, Ltd.     

开关磁阻电动机稳态特性的研究

用等效磁网络模型方法给出了开关磁阻电动机稳态特性的计算结果，结合系统的驱动电路和驱动逻辑建立了开关磁阻电动机稳态分析的实验模型，分析了开关磁阻电动机稳态运行过程中绕组电流、磁场储能和动态转矩的变化情况，尤其是对电机磁场储能的研究。详细的仿真分析证实了该方法的可行性，通过实验进一步证实了该方法的有效性。     

配电网开关优化配置的动态规划算法

开关优化配置模型属非线性、不可微的约束组合优化问题，文中提出该模型求解的动态规划算法。求解中，巧妙地选择开关配置位置及其类型作为动态规划的状态，配置开关设备台数为阶段数，实现动态规划计算。在模型中诠释了动态规划的基本概念，提出可行性准则、对称性准则、有效性准则、优胜劣汰准则、最优性准则等，利用上述准则可大大减少计算量。通过RBTS-BUS6及其他系统的开关优化配置及与免疫算法、遗传算法等的对比分析，验证了该算法的正确性、可行性，显示了算法的优越性。将该方法应用于工程实际，取得了较好的工程效果，为配电网规划和改造提供了有效的分析工具。