Room-Temperature-Processable Highly Reliable Resistive Switching Memory with Reconfigurability for Neuromorphic Computing and Ultrasonic Tissue Classification

Reversible metal-filamentary mechanism has been widely investigated to design an analog resistive switching memory (RSM) for neuromorphic hardware-implementation. However, uncontrollable filament-formation, inducing its reliability issues, has been a fundamental challenge. Here, an analog RSM with 3D ion transport channels that can provide unprecedentedly high reliability and robustness is demonstrated. This architecture is realized by a laser-assisted photo-thermochemical process, compatible with the back-end-of-line process and even applicable to a flexible format. These superior characteristics also lead to the proposal of a practical adaptive learning rule for hardware neural networks that can significantly simplify the voltage pulse application methodology even with high computing accuracy. A neural network, which can perform the biological tissue classification task using the ultrasound signals, is designed, and the simulation results confirm that this practical adaptive learning rule is efficient enough to classify these weak and complicated signals with high accuracy (97%). Furthermore, the proposed RSM can work as a diffusive-memristor at the opposite voltage polarity, exhibiting extremely stable threshold switching characteristics. In this mode, several crucial operations in biological nervous systems, such as Ca²⁺ dynamics and nonlinear integrate-and-fire functions of neurons, are successfully emulated. This reconfigurability is also exceedingly beneficial for decreasing the complexity of systems—requiring both drift- and diffusive-memristors.     

Implementation and characterization of flash-based hardware security primitives for cryptographic key generation

Hardware security primitives, also known as physical unclonable functions (PUFs), perform innovative roles to extract the randomness unique to specific hardware. This paper proposes a novel hardware security primitive using a commercial off-the-shelf flash memory chip that is an intrinsic part of most commercial Internet of Things (IoT) devices. First, we define a hardware security source model to describe a hardware-based fixed random bit generator for use in security applications, such as cryptographic key generation. Then, we propose a hardware security primitive with flash memory by exploiting the variability of tunneling electrons in the floating gate. In accordance with the requirements for robustness against the environment, timing variations, and random errors, we developed an adaptive extraction algorithm for the flash PUF. Experimental results show that the proposed flash PUF successfully generates a fixed random response, where the uniqueness is 49.1%, steadiness is 3.8%, uniformity is 50.2%, and min-entropy per bit is 0.87. Thus, our approach can be applied to security applications with reliability and satisfy high-entropy requirements, such as cryptographic key generation for IoT devices.     

基于异构数据的电力短期负荷大数据预测方案

随着多种可再生能源电力的接入,电力系统正在向更智能、更灵活、交互性更高的系统过渡。负荷预测,特别是针对单个电力客户的短期负荷预测在未来电网规划和运行中发挥着越来越重要的作用。提出了一个基于异构数据的电力短期负荷大数据预测方案,该方案收集来自智能电表和天气预报的数据,预处理后将其加载到非关系型数据库中进行存储并做进一步的异构数据处理;设计并实现了一个长短期记忆递归神经网络模型,用于确定负荷分布并预测未来24 h的住宅小区用电量;最后利用一个住宅小区的智能电表数据集对提出的短期负荷预测框架进行了测试,并使用均方根误差和平均绝对百分比误差两个指标,对比了预测模型与两种经典算法的性能,验证了所提模型的有效性。     

通信波段稀土离子掺杂固态量子存储进展

量子互联网是实现多方量子通信、分布式量子计算等量子信息技术的重要基础,量子存储器作为实现互联网的重要部件,对量子信息技术的发展、应用具有举足轻重的作用。如今遍布全球的光纤网络已经是信息传输的有力载体,通信波段的量子存储器因容易嵌入到当前的光纤网络中而备受重视。聚焦于稀土离子掺杂固态体系的通信波段光量子存储,首先介绍稀土离子掺杂固态量子存储的基本原理,包括稀土掺杂材料特性以及存储协议等,然后介绍目前的研究现状,最后简要分析其未来的发展趋势,并对量子互联网的构建做出展望。     

SHAPE MEMORY EFFECT OF PU IONOMERS WITH IONIC GROUPS ON HARD-SEGMENTS

SMPU （shape memory polyurethane） non-ionomers and ionomers, synthesized with poly（c-caprolactone） （PCL）, 4, 4＇-diphenylmethane diisocyanate （MDI）, 1,4-butanediol （BDO）, dimethylolpropionic acid （DMPA） were measured with cyclic tensile test and strain recovery test. The relations between the structure and shape memory effect of these two series were studied with respect to the ionic group content and the effect of neutralization. The resulting data indicate that, with the introduction of asymmetrical extender, the stress at 100% elongation is decreased for PU non-ionomer and ionomer series, especially lowered sharply for non-ionomer series; the fixation ratio of ionomer series is not affected obviously by the ionic group content; the total recovery ratio of ionomer series is decreased greatly. After sufficient relaxation time for samples stretched beforehand, the switching temperature is raised slightly, whereas the recovery ratio measured with strain recovery test method is lowered with increased DMPA content. The characterization with FT-IR, DSC, DMA elucidated that, the ordered hard domain of the two series is disrupted with the introduction of DMPA which causes more hard segments to dissolve in soft phase; ionic groups on hard segment enhance the cohesion between hard segments especially at high ionic group content and significantly facilitate the phase separation compared with the corresponding non-ionomer at moderate ionic group content.     

Microstructure and ferroelectric properties of r.f. magnetron sputtering derived PZT thin films deposited on interlayer (PbO/TiO2)

Lead zirconate titanate (PZT) thin films were deposited on Pt/Ti/SiO₂/Si and interlayer/Pt/Ti/SiO₂/Si substrate by radio frequency (r.f.) magnetron sputtering with a Pb_1.1Zr_0.53Ti_0.47O₃ target. The crystallization of the PZT thin films was formed only by substrate temperature. When interlayer (PbO/TiO₂) was inserted between the PZT thin film and the Pt electrode, the grain growth and processing temperature of the PZT thin films were considerably improved. Compared to PZT/Pt structure, the dielectric constant and polarization properties of the PZT/interlayer/Pt structure were fairly improved. In particular, PZT/interlayer/Pt at the substrate temperature of 400 °C showed prevalent ferroelectric properties (_r=475.97, tanδ=0.0591, P_r=23 μC/cm²). As a result of an X-ray photoelectron spectroscopy (XPS) depth-profile analysis, it was found that PZT/interlayer/Pt deposited only by substrate temperature without the post-annealing process via r.f. magnetron sputtering method remained independent of each other regardless of substrate temperatures.     

POLYMER NETWORK-POLY(ETHYLENE GLYCOL)COMPLEXES WITH SHAPE MEMORY EFFECT

The complexes of poly(methacrylic acid-co-methyl methacrylate) network with poly(ethylene glycol) stabilized byhydrogen bonds were prepared. By introducing the poly(ethylene glycol), a large difference in storage modulus below andabove the glass transition temperature occurred and the complexes exhibited shape memory behaviors. The morphology ofcomplexes was studied by using DSC, WAXD, and DMA. The results indicate that the fixed phase of this kind of novelshape memory materials is the network, and the reversible phase is the amorphous state of PEG:PMAA complex phase. Theshape recoverability almost reaches 100%. This type of complexes can be regarded as a novel shape memory network.     

形状记忆高分子材料

作为一种新型的功能材料,形状记忆高分子不仅具有形变量大、赋形容易、形状恢复温度便于调整、加工方便的优点,而且种类丰富、质轻价廉.按形状记忆的方式,它可分为热致感应型、光致感应型和化学物质感应型等,能满足不同的应用需求.     

Rigorous bounds on the storage capacity of the dilute Hopfield model

We study a neural network model consisting ofN neurons where a dendritic connection between each pair of neurons exists with probabilityp and is absent with probability 1-p. For the Hopfield Hamiltonian on such a network, we prove that ifp c[(lnN)/N]^1/2, the model can store at leastm= _cpN patterns, where _c 0.027 ifc 3 and decreases proportional to 1/(–lnc) forc small. This generalizes the results of Newman for the standard Hopfield model.