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.     

Monte Carlo modeling of X-valley leakage in quantum cascade lasers

This paper presents the first comprehensive Monte Carlo simulation of GaAs/AlGaAs quantum cascade lasers (QCLs) that takes both Γ- and X-valley transport into account and investigates the effect of X-valley leakage on the QCL performance. Excellent agreement with experimental data is obtained for the GaAs/Al_0.45Ga_0.55As QCL at cryogenic and room temperatures. The model reveals two carrier-loss mechanisms into the X valley: coupling of the Γ continuum-like states with the X states in the same stage, and coupling between the Γ localized states in the simulated stage with the X states in the next stage. Simulation results demonstrate that the 45% Al QCL has small X-valley leakage at both 77 K and 300 K, due to the very good confinement of the Γ states, stemming from the high Al content.     

Review of mechanisms proposed for redox based resistive switching structures

Mechanisms proposed for redox-based memristors are reviewed. Emphasis is given on MIM (metal/insulator/metal) devices of the type MOM where the insulator is an oxide. The oxide conducts oxygen via oxygen vacancies. MOM devices in which the insulator conducts intercalated cations are analogous to the ones with mobile oxygen vacancies. Switching, memory and short term hysteresis are three independent phenomena governed by different mechanisms. A necessary condition for memory is presented. Electroforming, filament formation and alteration and I-V curve crossing are discussed. A new mechanism for unipolar switching is suggested. The metal electrodes are sorted into four types according to the nature of their oxygen transfer. The effect of humidity in the ambient is discussed.     

基于Monte Carlo的电铁电能质量预测方法

针对电气化铁路牵引负荷具有的非线性、单相独立性和随机波动性的特点,提出一种基于Monte Carlo抽样的电铁电能质量预测方法,从而分析新建电气化铁路对电网电能质量的影响.对于新建的电铁牵引变电所,该方法在适当的边界条件下选取匹配的牵引变电所实测数据作为基础样本,在容量等效后建立其负荷电流的基波及各次谐波的概率分布模型,然后生成一组随机数,以前面得到的概率分布模型为对象,采用Monte Carlo方法进行基波及谐波的抽样,从而得到预测的新建变电所负荷数据,并可结合谐波、负序潮流程序研究其对电力系统可能产生电能质量影响.实例表明该方法能够真实地模拟牵引实际物理过程,故解决问题与实际较符合,在工程上具有可行性和实用性.     

Process modeling of stress and chemical effects in SiGe alloys using kinetic Monte Carlo

In state-of-the-art silicon based process technologies, strained and relaxed SiGe, strained-silicon layers, and process-induced stress are widely present. Based on a literature review, we developed and calibrated continuum and kinetic Monte Carlo process models for chemical and stress effects in SiGe (Zographos et al. in AIP Conf. Proc. 1496:212–216, 2012). In this paper, we explain in full detail the corresponding kinetic Monte Carlo models and calibration. The models take into account the effects on band gap, amorphization, recrystallization, point defect generation and diffusion, extended defect evolution, dopant diffusion and clustering, and dopant segregation. The influence of Ge concentration and strain profile on Si self-interstitials and vacancies properties are deducted from experimental data as well as from ab-initio studies. The {311} interstitial clusters are less stable in the presence of Ge or compressive hydrostatic pressure, and the transformation of {311} defects into dislocation loops is faster. The corresponding parameter adjustments have been calibrated based on experimental data generated within the ATOMICS research project. The effects of Ge and stress on dopant diffusion have been calibrated for boron, arsenic and phosphorus taking into account that in experiments using epitaxial layers of strained SiGe embedded in Si, or strained silicon embedded in relaxed SiGe, boron and phosphorus have been found to segregate at Si/SiGe interfaces.     

基于蒙特卡罗法的测量不确定度评定

当采用不确定度传递律进行测量不确定度评定（GUM方法）有困难或不方便时,蒙特卡罗法是实用的替代方法。在建立数学模型、设定输入量概率密度函数的基础上,通过对概率分布随机采样进行分布传递,确定输出量的概率密度函数,从而得到输出量的估计值、标准不确定度以及在指定包含概率下的包含区间,实现对测量不确定度的评定。通过小功率座校准因子测量不确定度评定示例,说明了采用蒙特卡罗法进行测量不确定度评定的实现方法,并与GUM方法进行了比较。     

Nanoscale characterization of resistive switching using advanced conductive atomic force microscopy based setups

Conductive atomic force microscopy (CAFM) is a powerful tool for studying resistive switching at the nanoscale. By applying sequences of I-V curves and biased scans the write, erase and read operations in a dielectric can be simulated in situ. CAFM can be used to monitor the inhomogeneities produced by a previous device level stress, for example conductive filaments formation and disruption. In this case the removal of the top electrode may be a problem. One attractive solution is to etch the top electrode using the CAFM tip for dielectric surface analysis, and one may also etch the dielectric to observe the shape of the filament in three dimensions. The genuine combination of electrical and mechanical stresses via CAFM tip can lead to additional setups, such as pressure modulated conductance microscopy. In the future, new experiments and CAFM related techniques may be designed to deep into the knowledge of resistive switching.     

Comprehensive reliability assessment of substation originated outages using the Monte Carlo simulation technique

Power system security and stability has become a major concern for electric power utilities, as power systems become more and more complex and are operated closer to transmission capacity limits. Substations and switching stations are pivotal parts of power systems. Failure events in substations often result in multiple outages of generators, lines, and/or loads in power systems, and affect the security and stability of power system dramatically. The reliability evaluation of substation originated outages is therefore of vital importance. This paper presents the application of a Monte Carlo simulation (MCS) method to the reliability evaluation of voltage step-up substations and switching stations (herein referred to only as substations) in transmission systems. The proposed approach is demonstrated by application to an educational test system designated as RBTS (R. Billinton, S. Kumar, L. Goel, et al., A reliability test system for educational purposes—basic data, IEEE Trans. Power Appar. Syst. 4 (3) (1989) 1238–1244) and some selected sensitivity studies are also presented in this paper. The results of studies provide valuable information for decision-making in power system planning and operation. A comparison between the reliability indices of two groups of overlapping failures obtained from both analytical method and MCS approach shows that the approximate equations of analytical methods have constraints when the component average repair time exceeds certain numerical range. The MCS approach is shown to be more accurate when dealing with the multiple order outages.     

基于Monte Carlo的主变压器全寿命周期成本研究

目前在变电工程领域中的主变压器选择方面,应用全寿命周期成本(LCC)理论已经研究出了许多成果,但未对成本计算中的不确定性做充分讨论。针对上述不足,运用LCC理论建立了变压器的全寿命周期成本模型,将其应用在变电站主变压器选择中,运用Monte Carlo方法针对成本的随机性进行了模拟,并对全寿命周期成本因子进行了敏感性分析,用实例验证了模型和模拟方法的实用性。结果表明,在负荷密集地区采用大容量变压器和控制运营成本是减少主变压器全寿命周期成本的有效措施。     

基于蒙特卡洛法的微波功率测量不确定度评定

利用蒙特卡洛法对微波功率测量不确定度进行评定。介绍了蒙特卡洛法评定测量不确定度的过程,给出了基于MATLAB 实现蒙特卡洛法评定的步骤。分别使用单批次蒙特卡洛法和自适应蒙特卡洛法评定给定频率下微波功率测量不确定度,并与 GUM 法结果进行比较和验证。结果表明除标准不确定度值蒙特卡洛法和 GUM 法相差5%外,其他结果几乎一致,蒙特卡洛法验证了 GUM 法,完全适合微波功率测量不确定度评定。蒙特卡洛法能处理线性模型,在各不确定度分量相差较大情况下优势明显,同时简单、方便,易于推广。     

基于蒙特卡洛模拟的发电边际成本分析

发电边际成本分析是市场参与者进行电价预测和确定报价策略的基础.考虑到发电机组的随机强迫停运和负荷预测等不确定性,任何时刻的发电边际成本都是一个随机变量.详细分析了电能生产中的各种随机因素,认为发电机的工作时间和修复时间服从指数分布,系统负荷服从正态分布,燃料价格服从某种概率分布.利用蒙特卡洛方法对电能生产过程进行模拟,并在此基础上对系统短期发电边际成本进行分析.算例分析表明,该方法物理概念清晰,且便于实现,易于收敛.而且与传统的基于随机生产模拟技术的方法相比,该方法易于考虑电能生产过程中的各种随机因素,且不需要过多的负荷资料.     

基于蒙特卡洛模拟的电力市场风险评估研究

电力市场中,市场参与者以自身利益最大化为行动导向。由于市场的不完善,市场参与者的逐利行为有可能会导致市场风险。为了规避市场风险,对其进行评估是十分必要的。基于风险经济学中的风险评估理论,以电价为切入点,将市场参与者的报价看成随机变量,利用蒙特卡洛法建立了一套市场风险评估模型。该模型不需要借助市场运行的历史数据,就可以快速、有效地评估出市场风险,为市场机制设计人员提供有益的参考。     

基于蒙特卡洛模拟的电力市场风险评估研究

电力市场中,市场参与者以自身利益最大化为行动导向.由于市场的不完善,市场参与者的逐利行为有可能会导致市场风险.为了规避市场风险,对其进行评估是十分必要的.基于风险经济学中的风险评估理论,以电价为切入点,将市场参与者的报价看成随机变量,利用蒙特卡洛法建立了一套市场风险评估模型.该模型不需要借助市场运行的历史数据,就可以快速、有效地评估出市场风险,为市场机制设计人员提供有益的参考.     

基于非序贯蒙特卡洛冰灾重现期线路经济性比较

提出一种比较不同重现期线路经济性的新算法,该算法建立关于结冰持续时间和线路分节数的失效率模型,用非序贯蒙特卡洛模拟冰灾发生与否、结冰持续时间长短和线路失效与否.通过最优潮流法计算求得线路在寿命期间的冰灾风险成本,综合初期成本和常规维修成本比较不同重现期线路的经济性.以修订的IEEE可靠性测试系统为物理模型、湖南省冰灾气候为参考气候的算例,验证了该算法的实用性及对于电力线路设计的指导意义.     

基于蒙特卡罗法的数字化电能表计量误差评估*

为了准确地评估数字化电能表的计量误差,对影响量误差和综合误差间的关系进行研究。由于数字化电能表计量模型的复杂性,无法直接给出综合误差的解析结果,为此,采用蒙特卡罗法,通过仿真计算和统计特性分析,得到了数字化电能表综合误差及影响量误差的分布特征,并验证了它们之间的函数关系。分析结论可为数字化电能表影响量误差限值的确定及等级划分提供参考。     

基于交叉熵的蒙特卡洛法在发电系统充裕度评估中的应用

针对传统蒙特卡洛法对稀有事件的敏感性等问题,提出了一种基于交叉熵的蒙特卡洛法,将其应用于发电系统充裕度评估中。基本思想是使用重要抽样密度函数,通过求解最优问题获得该函数的最优参数,从而提高传统蒙特卡洛法的抽样效率。最后使用可靠性测试系统IEEE-RTS以及修改后的测试系统对提出的方法进行验证,将仿真结果与使用传统蒙特卡洛法得到的结果进行比较,表明该方法在保证评估精度的基础上大大提高了计算速度。     

基于蒙特卡罗的电力市场双边交易竞价策略研究

在批发竞争市场环境下,研究双边交易市场中经纪人的交易策略.分析经纪人交易原理、类型、报价规则及社会效益.通过蒙特卡罗方法模拟研究买卖双方的最优报价策略,并用一个算例验证报价策略的有效性.     

蒙特卡罗方法在网损分摊中的应用

研究了计算网损分摊的方法,针对在实际生产运行中,特定时段的计算网损分摊电量的通常方法,提出采用蒙特卡罗方法计算得到的用户在一段时间的分摊电量的一种方法,通过在负荷功率概率模型基础上抽取负荷样本,并而根据该抽样数据计算出的结果,在一定程度弥补了计算量大、计算时间长的问题.