NH_3-OH体系中共沉淀法同时回收钕铁硼废料中Nd-Pr-Co-Fe

为了避免回收单一钕铁硼废料中有价元素带来的操作复杂和资源浪费等问题,本研究采用共沉淀法共沉淀出钕铁硼废料中的有价元素Me(Nd,Pr,Co,Fe),制备可用于生产再生钕铁硼的原料;根据质量守恒和同时平衡原理,采用MATLAB软件建立Me(Nd,Pr,Co,Fe)-OH--NH3热力学模型,绘制lg[Me]-p H曲线模拟共沉淀工艺,并根据模拟结果确立了共沉淀工艺;模拟和实验的结果表明:根据lg[Me]-p H模拟结果可以确立一步共沉淀法的p H:6~10,Fe3+比Fe2+更易于沉淀完全;在上述条件下获得的共沉淀粉末主相均为Nd,Pr,Co,Fe的化合物,且有价元素的百分比含量均大于99.4%;其中,当p H值在8左右时回收率最高,在该条件下金属元素Me(Nd,Pr,Co,Fe)的沉淀效率分别为:98.7%,99.9%,93.6%,99.9%。该结果也表明共沉淀法工艺不仅高效,而且所制备的共沉淀粉末可以满足制备二次钕铁硼的需要。     

Enhance cycling performance of LiMn2O4 cathode by Sr2+ and Cr3+ doping

Spinel LiSr_0·1Cr_0·1Mn_1·8O₄ was synthesised by high temperature solid state method in order to enhance the electrochemical performance. The LiSr_0·1Cr_0·1Mn_1·8O₄ (LSCMO) materials were characterised by X-ray diffraction (XRD), scanning electron microscopy (SEM) and electrochemical tests. The XRD and SEM studies confirm that LSCMO had spinel crystal structure with a space group of Fd3m, and the particle of LSCMO shows irregular shape. The cyclic voltammetry data illustrated that the heavy current charge–discharge performance of LMO was improved by Sr²⁺ and Cr³⁺ doping. The galvanostatic charge–discharge of LSCMO cathode materials was measured at 1, 5, 10 and 20 C. The results indicated that LSCMO improved the capacity retention.     

鸡西盆地太平普查区岩浆活动特征

通过对普查区喜山期玄武岩喷发分布范围、形态的分析,对燕山晚期闪长玢岩分布范围、与构造关系、对煤层的影响等方面的分析,阐述了太平普查区岩浆活动特征。     

A spatio-temporal fusion method for remote sensing data Using a linear injection model and local neighbourhood information

This paper presents a spatio-temporal fusion method for remote sensing images by using a linear injection model and local neighbourhood information. In this method, the linear injection model is first introduced to generate an initial fused image, the spatial details are extracted from the fine-resolution image at the base date, and are weighted by a proper injection gains. Then, the spatial details and the relative spectral information from the coarse-resolution images are blended to generate the fusion result. To further enhance its robustness to the noise, the local neighbourhood information, derived from the fine-resolution image and the fused result simultaneously, is introduced to refine the initial fused image to obtain a more accurate prediction result. The algorithm can effectively capture phenology change or land-cover-type change with minimum input data. Simulated data and two types of real satellite images with seasonal changes and land-cover-type changes are employed to test the performance of the proposed method. Compared with a spatial and temporal adaptive reflectance fusion model (STARFM) and a flexible spatio-temporal fusion algorithm (FSDAF), results show that the proposed approach improves the accuracy of fused images in phenology change area and effectively captures land-cover-type reflectance changes.     

Specific emitter identification for satellite communication using probabilistic neural networks

Electromagnetic signal emitted by satellite communication (satcom) transmitters are used to identify specific individual uplink satcom terminals sharing the common transponder in real environment, which is known as specific emitter identification (SEI) that allows for early indications and warning (I&W) of the targets carrying satcom furnishment and furthermore the real time electromagnetic situation awareness in military operations. In this paper, the authors are the first to propose the identification of specific transmitters of satcom by using probabilistic neural networks (PNN) to reach the goal of target recognition. We have been devoted to the examination by exploring the feasibility of utilizing the Hilbert transform to signal preprocessing, applying the discrete wavelet transform to feature extraction, and employing the PNN to perform the classification of stationary signals. There are a total of 1000 sampling time series with binary phase shift keying (BPSK) modulation originated by five types of satcom transmitters in the test. The established PNNs classifier implements the data testing and finally yields satisfactory accuracy at 8 dB(±1 dB) carrier to noise ratio, which indicates the feasibility of our method, and even the keen insight of its application in military.     

基于查询的新闻多文档自动摘要技术研究

针对新闻文本领域,该文提出一种基于查询的自动文本摘要技术,更加有针对性地满足用户信息需求。根据句子的TF-IDF、与查询句的相似度等要素,计算句子权重,并根据句子指示的时间给定不同的时序权重系数,使得最近发生的新闻内容具有更高的权重,最后使用最大边界相关的方法选择摘要句。通过与基于TF-IDF、Text-Rank、LDA等六种方法的对比,该摘要方法ROUGE评测指标上优于其他方法。从结合评测结果及摘要示例可以看出,该文提出的方法可以有效地从新闻文档集中摘取核心信息,满足用户查询内容的信息需求。