钨板轧制的轧制力模型研究

为了使钨板轧制过程中的各项轧制参数得到有效控制，对钨板轧制数学模型进行了研究。首先在Gleeble热模拟机上进行热压缩试验，研究了变形抗力与各种变形条件的关系，确定了变形抗力模型：通过550mm轧机轧制钨板时采集到的有关数据，建立了应力状态影响系数数学模型、变形区长度等模型：最终建立了550mm钨板轧机轧制力模型。利用模型计算值与实际测量参数进行了对比，结果比较满意。     

热带粗轧机组立轧稳定轧制变形规律的实验研究和有限元分析

本文采用铅作为模拟材料，对热带粗轧机组平辊立轧变形规律进行了实验研究，得到了表征立轧稳定轧制阶段时轧件断面特征的四个参量与侧压量、立辊直径、板坯来料厚度及宽度之间的关系。并首次提出用超薄单元近似处理奇异点的新方法，采用全三维刚塑性可压缩有限元法对立轧稳态过程进行了理论解析，所得结果和实验结果符合较好。     

THERMODYNAMICS AND PHASE EQUILIBRIUM OF Cu－Y－O，Cu－Y－S，Cu－Y－O－S LIQUID SOLUTIONS

ＴＨＥＲＭＯＤＹＮＡＭＩＣＳＡＮＤＰＨＡＳＥＥＱＵＩＬＩＢＲＩＵＭＯＦＣｕ－Ｙ－Ｏ，Ｃｕ－Ｙ－Ｓ，Ｃｕ－Ｙ－Ｏ－ＳＬＩＱＵＩＤＳＯＬＵＴＩＯＮＳ￥Ｄｕ，Ｔｉｎｇ；Ｌｉ，Ｇｕｏｄｏｎｇ（ＣｅｎｔｒａｌＩｒｏｎａｎｄＳｔｅｅｌＲｅｓｅａｒｃｈｉｎｓｔｉｔ...     

减沉桩与加筋土褥垫层联合作用减沉机理研究

针对采用减沉桩与加筋土褥垫层联合作用的某高填方区地基处理工程,监测了桩与桩间土的压力及沉降、加筋土褥垫层中土工格栅的变形和建筑物沉降,分析了桩和桩间土应力变化情况、土工格栅变形和桩与桩间土沉降差异,研究了减沉桩和加筋土褥垫层共同作用机理,可为类似工程地基处理参考。     

一种新型煤矿救援机器人履带行走机构设计

从履带机构的结构复杂度、越障性能、可操作性以及履带的接地比压4个方面分析了现有煤矿救援机器人履带行走机构的优缺点,针对现有履带结构的优缺点设计了一种新型履带行走机构的结构;结合煤矿救援机器人的相关要求,给出了该新型结构主要尺寸的优化计算公式;根据所提出的计算公式,设计了CUMT-5型煤矿救援机器人。CUMT-5机器人的实际运行结果表明,该新型履带行走机构结构简单,越障性能好,具有良好的可操作性。     

基于改进粒子群优化算法的火电厂机组负荷分配

以坑口电厂厂级监控信息系统的机组负荷在线优化分配功能模块为应用背景,针对模块所运用的基本粒子群优化算法在优化过程中容易陷入局部收敛、收敛速度慢的缺点,提出一种基于惯性权重非线性减小策略的改进粒子群优化算法,使惯性权重呈对数减小;测试函数仿真结果表明,改进粒子群优化算法在收敛速度和寻优精度方面,优化性能均优于基本粒子群优化算法;通过MATLAB与Visual C++混合编程,开发了机组负荷在线优化分配功能模块,提高了算法的计算效率和工程应用价值。     

Direct Growth of Uniform Bimetallic Core-Shell or Intermetallic Nanoparticles on Carbon via a Surface-Confinement Strategy for Electrochemical Hydrogen Evolution Reaction

Due to the surface inhomogeneity of the solid supports, direct growth of uniform bimetallic nanoparticles (NPs) with controllable structure and size thereon is particularly challenging. Herein, a surface-confinement strategy is reported to directly prepare ultrafine bimetallic Pt M NPs (MFe, Cu, and Co) with structure of core-shell or intermetallic compounds on an N functionalized carbon support (NC). It is found that the N species of NC support can atomically disperse metal cations of precursors, which largely renders uniform nucleation and growth of bimetallic NPs and fine structure modulation of them. In another regard, metal transfer is confined to a narrow region on NC via N-mediation, hence greatly favoring localized particle growth and formation of ultrafine bimetallic NPs. Remarkably, the ultrafine 3.1 ± 0.7 nm intermetallic Pt₃Fe NPs on NC displayed excellent catalytic activity and durability toward electrochemical hydrogen evolution reaction.     

Mitigating Surface Deficiencies of Perovskite Single Crystals Enables Efficient Solar Cells with Enhanced Moisture and Reverse-Bias Stability

Metal halide perovskite single crystals are promising for diverse optoelectronic applications due to their outstanding properties. In comparison to the bulk, the crystal surface suffers from high defect density and is moisture sensitive; however, surface modification strategies of perovskite single crystals are relatively deficient. Herein, solar cells based on methylammonium lead triiodide (MAPbI₃) thin single crystals are selected as a prototype to improve single-crystal perovskite devices by surface modification. The surface trap passivation and protection against moisture of MAPbI₃ thin single crystals are achieved by one bifunctional molecule 3-mercaptopropyl(dimethoxy)methylsilane (MDMS). The sulfur atom of MDMS can coordinate with bare Pb²⁺ of MAPbI₃ single crystals to reduce surface defect density and nonradiative recombination. As a result, the modified devices show a remarkable efficiency of 22.2%, which is the highest value for single-crystal MAPbI₃ solar cells. Moreover, MDMS modification mitigates surface ion migration, leading to enhanced reverse-bias stability. Finally, the cross-link of silane molecules forms a protective layer on the crystal surface, which results in enhanced moisture stability of both materials and devices. This work provides an effective way for surface modification of perovskite single crystals, which is important for improving the performance of single-crystal perovskite solar cells, photodetectors, X-ray detectors, etc.     

Functional Materials for Memristor-Based Reservoir Computing: Dynamics and Applications

The booming development of artificial intelligence (AI) requires faster physical processing units as well as more efficient algorithms. Recently, reservoir computing (RC) has emerged as an alternative brain-inspired framework for fast learning with low training cost, since only the weights associated with the output layers should be trained. Physical RC becomes one of the leading paradigms for computation using high-dimensional, nonlinear, dynamic substrates. Among them, memristor appears to be a simple, adaptable, and efficient framework for constructing physical RC since they exhibit nonlinear features and memory behavior, while memristor-implemented artificial neural networks display increasing popularity towards neuromorphic computing. In this review, the memristor-implemented RC systems from the following aspects: architectures, materials, and applications are summarized. It starts with an introduction to the RC structures that can be simulated with memristor blocks. Specific interest then focuses on the dynamic memory behaviors of memristors based on various material systems, optimizing the understanding of the relationship between the relaxation behaviors and materials, which provides guidance and references for building RC systems coped with on-demand application scenarios. Furthermore, recent advances in the application of memristor-based physical RC systems are surveyed. In the end, the further prospects of memristor-implemented RC system in a material view are envisaged.     

结合超混沌系统和Logistic映射的视频图像加密算法

对视频图像使用传统的单幅图像加密算法,容易出现算法耗时长、效率低等问题。为提高视频图像加密效率,通过使用细胞神经网络（CNN）超混沌系统和Logistic混沌映射,提出一种单帧逐一加密和多帧组合加密相结合的算法。根据视频帧使用SHA-256生成Logistic初值,经过Logistic映射迭代得到Logistic混沌序列,利用生成的混沌序列对视频帧逐帧扩散。将视频帧以二进制的形式组合成一个矩阵,把根据组合矩阵产生的初值代入CNN超混沌系统,利用得到的混沌序列对组合矩阵进行置乱,视频所有帧各像素点扩散、置乱一步完成,从而缩短加密时间。在此基础上,将组合矩阵重新分解为单帧图像,得到最终加密的视频图像。实验结果表明,在算法中使用高维超混沌系统安全性更高,能够有效缩短加密视频图像的耗时,且能抵抗统计攻击、差分攻击和暴力攻击,具有较好的安全性。