浅谈不同给液方式在铜电解车间的应用

不同给液方式对铜电解过程中有重要的影响,不同的循环方式会影响槽内温度分布、电解液成分及阳极泥沉降等,因此,根据铜电解生产不同情况的需要,分析对比了多种给液方式在贵冶电解车间的应用,总结了这几种给液方式的优缺点和适用条件。     

Remarkably enhanced energy storage properties of lead-free Ba0.53Sr0.47TiO3 thin films capacitors by optimizing bottom electrode thickness

The lead-free Ba_0.53Sr_0.47TiO₃ (BST) thin films buffered with La_0.67Sr_0.33MnO₃ (LSMO) bottom electrode of different thicknesses were fabricated by pulsed laser deposition method on a (001) SrTiO₃ substrate. It was found that the roughness of electrode decreases and substrate stress relaxes gradually with the increase of LSMO thickness, which is beneficial for weakening local high electric field and achieving higher E_b. Therefore, the recoverable energy density (W_rec) of BST films can be greatly improved up to 67.3 %, that is, from 30.6 J/cm³ for the LSMO thickness of 30 nm up to 51.2 J/cm³ for the LSMO thickness of 140 nm after optimizing the LSMO thickness. Furthermore, the thin film capacitor with a 140 nm LSMO bottom electrode shows an outstanding thermal stability from 20 °C to 160 °C and superior fatigue resistance after 10⁸ electrical cycles with only a slightly decrease of W_rec below 1.6 % and 3.7 %, respectively. Our work demonstrates that optimizing bottom electrodes thickness is a promising way for enhancing energy storage properties of thin-film capacitors.     

A Student's t-based density peaks clustering with superpixel segmentation (tDPCSS) method for image color clustering

Image color clustering is a basic technique in image processing and computer vision, which is often applied in image segmentation, color transfer, contrast enhancement, object detection, skin color capture, and so forth. Various clustering algorithms have been employed for image color clustering in recent years. However, most of the algorithms require a large amount of memory or a predetermined number of clusters. In addition, some of the existing algorithms are sensitive to the parameter configurations. In order to tackle the above problems, we propose an image color clustering method named Student's t-based density peaks clustering with superpixel segmentation (tDPCSS), which can automatically obtain clustering results, without requiring a large amount of memory, and is not dependent on the parameters of the algorithm or the number of clusters. In tDPCSS, superpixels are obtained based on automatic and constrained simple non-iterative clustering, to automatically decrease the image data volume. A Student's t kernel function and a cluster center selection method are adopted to eliminate the dependence of the density peak clustering on parameters and the number of clusters, respectively. The experiments undertaken in this study confirmed that the proposed approach outperforms k-means, fuzzy c-means, mean-shift clustering, and density peak clustering with superpixel segmentation in the accuracy of the cluster centers and the validity of the clustering results.     

Effect of 100 KeV Ar+ ion beam irradiation on ZnO thin films – Influence of morphology vis-a-vis electrode/electrolyte interface and its impact on photoelectrochemical water splitting

The present study attempts quantitative determination of changes in the morphological surface features viz. fractal dimension, lower and upper cut off length scale through Power Spectral Density analysis prior to and after irradiation of 100 KeV Ar⁺ ion beam at incidence angles of 0°, 40° and 60° on ZnO thin films. All the unirradiated and irradiated samples are subjected to photoelectrochemical characterization and a correlation between photoelectrochemical performance and morphological parameters is established. Sample irradiated at 40° angle at the fluence of 5 × 10¹⁶ ions/cm² is found to possess maximum fractal dimension of 2.72, lower and upper cut off length scale of 3.16 nm and 63.00 nm respectively. This sample exhibits maximum photocurrent density of 3.19 mA/cm² and applied bias photon-to-current efficiency of 1.12% at 1.23 V/RHE. Hydrogen gas collected for duration of 1 h for the same sample was ~4.83 mLcm^?2.     

Research on phase shift characteristics of electromagnetic wave in plasma

The phase shift characteristics reflect the state change of electromagnetic wave in plasma sheath and can be used to reveal deeply the action mechanism between electromagnetic wave and plasma sheath. In this paper, the phase shift characteristics of electromagnetic wave propagation in plasma were investigated. Firstly, the impact factors of phase shift including electron density,collision frequency and incident frequency were discussed. Then, the plasma with different electron density distribution profiles were employed to investigate the influence on the phase shift characteristics. In a real case, the plasma sheath around the hypersonic vehicle will affect and even break down the communication. Based on the hypersonic vehicle model, we studied the electromagnetic wave phase shift under different flight altitude, speed, and attack angle. The results indicate that the phase shift is inversely proportional to the flight altitude and positively proportional to the flight speed and attack angle. Our work provides a theoretical guidance for the further research of phase shift characteristics and parameters inversion in plasma.     

Contribution of metal vapor mass at periphery part of pulsed arc to electromagnetic force in weld pool

The arc welding has been used in various welding methods because it is inexpensive and high in strength after welding. However, it is a problem that accidents such as collapse of the bridge occur because of the welding defects. The welding of low cost and high productivity is required without the welding defects. The pulsed TIG welding is inexpensive and capable of high‐quality welding. The electromagnetic force contributing to penetration changes because the transient response of arc temperature and iron vapor generated from anode occurs. However, the analysis of pulsed TIG welding with metal vapor has been elucidated only metal vapor concentration near anode with transient phenomenon and heat flux. Thus, the theoretical elucidation of penetration depth with control factor has not been researched. In this paper, the contribution of metal vapor mass at the periphery part of pulsed arc to the electromagnetic force in the weld pool is elucidated. As a result, the iron vapor mass at periphery part decreased with increasing the frequency. The iron vapor was stagnated at axial center within one cycle. The electromagnetic force to the penetration depth direction in weld pool increased at axial center. Therefore, the metal vapor mass at periphery part plays an important role for the electromagnetic force increment at axial center.     

Improved energy storage density and energy efficiency of Samarium modified PMNT electroceramic

We report the improved energy storage density and efficiency after 2.5% of Samarium substitution in ferroelectric Pb[(Mg_1/3Nb_2/3)_0.80Ti_0.20]O₃ (PMNT) electroceramic. The microstructure and surface morphology were analyzed and correlated with various functional properties. The energy storage density, leakage current density, ferroelectric and dielectric properties were investigated thoroughly, indicating that Samarium's substitution significantly modified the microstructure, the dielectric strength, breakdown electric field, and turned ferroelectric PMNT to relaxor ferroelectrics. Due to the relaxor nature, the gap between remanent polarization and maximum polarization increases with the substitution of Samarium in PMNT matrix, which further increases the recoverable energy storage density and energy efficiency. A nearly 100% increase in recoverable energy density and efficiency was obtained at an electric field strength of 35 kV/cm at room temperature (～296 K). The electroceramic shows maximum energy density near the ferroelectric phase transition temperature (325 K–345 K) region and provides a moderate energy storage density for possible applications in power microelectronics.     

Effect of sintering conditions on structural and morphological properties of Y- and Co-doped BaZrO3 proton conductors

BaZrO₃-based materials doped with a trivalent cation have excellent chemical stability and relatively high proton conductivity which makes them potential proton conducting oxide materials for various electrochemical device applications such as hydrogen processing, high-temperature electrolysis, and solid electrolyte in fuel cells. However, BaZrO₃ showed poor sinterability, requiring high sintering temperatures (1700–2100 °C) with longtime sintering (20–100 h) to achieve the desired microstructure and grain growth. This sintering problem can be solved by slightly doping BaZrO₃ with a sintering aid element. Therefore, in this study, two different zirconate proton conductors: BaZr_0·9Y_0·1O_3-α (BZY) and BaZr_0·955Y_0·03Co_0·015O_3-α (BZYC) were sintered in an air atmosphere and an oxygen atmosphere for 20 h in the temperature range of 1500–1640 °C. The sinterability was evaluated by analyzing the XRD diffraction patterns, lattice constant, lattice strain, crystallite size, relative density, open porosity, closed porosity, surface morphology, grain size, and grain boundary distribution, using the XRD, SEM, EDX, and Archimedes density measurement methods. It is concluded that in an oxygen atmosphere, sintering aid Co not only improves the relative density but also produces highly dense fine particles with clear grain boundaries which are promising for electrochemical hydrogen device applications.     

基于模糊谱聚类的不确定蛋白质相互作用网络功能模块挖掘

针对谱聚类融合模糊C-means（FCM）聚类的蛋白质相互作用（PPI）网络功能模块挖掘方法准确率不高、执行效率较低和易受假阳性影响的问题，提出一种基于模糊谱聚类的不确定PPI网络功能模块挖掘（FSC-FM）方法。首先，构建一个不确定PPI网络模型，使用边聚集系数给每一条蛋白质交互作用赋予一个存在概率测度，克服假阳性对实验结果的影响；第二，利用基于边聚集系数流行距离（FEC）策略改进谱聚类中的相似度计算，解决谱聚类算法对尺度参数敏感的问题，进而利用谱聚类算法对不确定PPI网络数据进行预处理，降低数据的维数，提高聚类的准确率；第三，设计基于密度的概率中心选取策略（DPCS）解决模糊C-means算法对初始聚类中心和聚类数目敏感的问题，并对预处理后的PPI数据进行FCM聚类，提高聚类的执行效率以及灵敏度；最后，采用改进的边期望稠密度（EED）对挖掘出的蛋白质功能模块进行过滤。在酵母菌DIP数据集上运行各个算法可知，FSC-FM与基于不确定图模型的检测蛋白质复合物（DCU）算法相比，F-measure值提高了27.92%，执行效率提高了27.92%；与在动态蛋白质相互作用网络中识别复合物的方法（CDUN）、演化算法（EA）、医学基因或蛋白质预测算法（MGPPA）相比也有更高的F-measure值和执行效率。实验结果表明，在不确定PPI网络中，FSC-FM适合用于功能模块的挖掘。     

结合优化支持向量机与K-means++的工控系统入侵检测方法

针对工业控制系统传统单一检测算法模型对不同攻击类型检测率和检测速度不佳的问题，提出一种优化支持向量机和K-means++算法结合的入侵检测模型。首先利用主成分分析法（PCA）对原始数据集进行预处理，消除其相关性；其次在粒子群优化（PSO）算法的基础上加入自适应变异过程避免在训练的过程中陷入局部最优解；然后利用自适应变异粒子群优化（AMPSO）算法优化支持向量机的核函数和惩罚参数；最后利用密度中心法改进K-means算法与优化后的支持向量机组合成入侵检测模型，从而实现工业控制系统的异常检测。实验结果表明，所提方法在检测速度和对各类攻击的检测率上得到明显提升。