四磷酸钾铽能谱的晶场分析

采用不可约张量法,分析了KTbP₄O₁₂晶体荧光光谱,拟合了五个晶场参量和八个相对论参量,结果与实验吻合。     

甲烷催化部分氧化制合成气的反应机理

借助脉冲反应、质谱-程序升温表面反应（MS-TPSR）等技术研究了Ni／α-Al2O3催化剂上甲烷催化部分氧化制合成气（POM）的反应机理．结果表明,NiO上CH4不能解离产生H2只有当NiO被CH4还原为Ni0后,CH4才能解高产生H2,Ni0是CH4活化和POM反应的活性相;POM反应机理遵循直接氧化机理,CH4和O2均在Ni0上活化,活化过程形成的Ni…C和Niδ…Oδ物种是反应历程中的关键物种,Niδ …Oδ物种高选择性地与CH4解离产生的碳物种Ni…C反应生成CO．     

氰基衍生化制备胺的研究进展

胺是有机分子中最常见且重要的结构之一,广泛存在于天然产物分子、药物、染料、塑料等的分子结构中,开发合成胺的有效方法在化学工业中具有很高的需求但仍充满挑战。在诸多已知有机胺的合成方法中,以氰基为前体还原衍生化制备胺被认为是一条原子经济且绿色可行的方案。然而,氰基中存在稳定的碳氮三重键,还原过程涉及较多中间体,而部分中间体活性比氰基更高,因此反应受还原剂、催化剂、反应条件的影响很大,由氰基选择性制备目标胺结构仍充满挑战。本文从氰基的基本电子结构与反应活性出发,综述了近年来以氰基为原料的官能团胺基化反应,对部分重要反应的催化剂和反应机理做了简要讨论,为设计氰基制胺催化剂和应用工艺提供了新的视角。     

载体对Rh基催化剂上甲烷解离活性的影响

采用脉冲反应技术、原位CO吸附和吡啶吸附红外光谱,考察了Al2O3和SiO2负载的Rh基催化剂上Rh-CeO2相互作用和CH4解离活性.结果表明,载体酸性对Rh-CeO2相互作用有显著影响.Rh/Al2O3催化剂中添加CeO2增加了载体Al2O3的Lewis酸位,使Al2O3接受电子的能力增强,从而降低Rh的电子密度,有利于CH4解离活化.相反,Rh/SiO2催化剂中添加CeO2减少了载体SiO2的Lewis酸位和酸强度,使SiO2难于接受电子,导致Rh的电子密度增加,不利于CH4解离活化.     

Mg-Ni-Nd非晶电极合金充放电过程中的组织结构变化及对其放电容量的影响

采用熔体快淬法制备了(Mg70.6 Ni29.4)90Nd10的非晶贮氢合金带,用X射线衍射仪和高分辨电镜对该合金在充放电循环过程中的组织结构演变进行了动态跟踪.结果表明:(Mg70.6Ni29.4)90Nd10贮氢合金在充放电循环过程中由非晶态慢慢晶化为纳米晶,初生相NdMg2 Ni9在循环过程中逐渐转化为Mg2 Ni,α-Mg和Nd2H5相.电化学性能测试表明,由于微观结构的变化对其放电容量的影响过程分为3个阶段:首先是前两个循环的活化过程,在第3个循环达到放电容量最高值(580.5 mAh·g-1);接下来是放电容量显著降低的4～10个循环阶段;最后是放电容量保持稳定的11 ～20个循环.研究发现NdMg2 Ni9相的存在和保持合金的非晶结构是提高镁基电极合金循环稳定性的重要因素.     

Synthesis of ZnO Photocatalysts Using Various Surfactants

Russian Journal of Physical Chemistry A - Zinc oxide (ZnO) nanostructured materials have received significant attention because of their unique physicochemical and electronic properties. In...     

GIS Partial Discharge Pattern Recognition Based on a Novel Convolutional Neural Networks and Long Short-Term Memory

Distinguishing the types of partial discharge (PD) caused by different insulation defects in gas-insulated switchgear (GIS) is a great challenge in the power industry, and improving the recognition accuracy of the relevant models is one of the key problems. In this paper, a convolutional neural network and long short-term memory (CNN-LSTM) model is proposed, which can effectively extract and utilize the spatiotemporal characteristics of PD input signals. First, the spatial characteristics of higher-level PD signals can be obtained through the CNN network, but because CNN is a deep feedforward neural network, it does not have the ability to process time-series data. The PD voltage signal is related to the time dimension, so LSTM saves and analyzes the previous voltage signal information, realizes the modeling of the time dependence of the data, and improves the accuracy of the PD signal pattern recognition. Finally, the pattern recognition results based on CNN-LSTM are given and compared with those based on other traditional analysis methods. The results show that the pattern recognition rate of this method is the highest, with an average of 97.9%, and its overall accuracy is better than that of other traditional analysis methods. The CNN-LSTM model provides a reliable reference for GIS PD diagnosis.     

创造性优化教材 提高探究物理规律的有效性——对比同一教学内容不同教学设计方案有感

新课程改革为每个教师提供了足够的空间,使教师成为教材的生产者和主人,杜威认为:"所谓教材,就是在一个有目的的情境的发展过程中所观察的、回忆的、阅读的和谈论的种种事实,以及所提出的种种观念."     

Porcelain Insulator Crack Location and Surface States Pattern Recognition Based on Hyperspectral Technology

A porcelain insulator is an important part to ensure that the insulation requirements of power equipment can be met. Under the influence of their structure, porcelain insulators are prone to mechanical damage and cracks, which will reduce their insulation performance. After a long-term operation, crack expansion will eventually lead to breakdown and safety hazards. Therefore, it is of great significance to detect insulator cracks to ensure the safe and reliable operation of a power grid. However, most traditional methods of insulator crack detection involve offline detection or contact measurement, which is not conducive to the online monitoring of equipment. Hyperspectral imaging technology is a noncontact detection technology containing three-dimensional (3D) spatial spectral information, whereby the data provide more information and the measuring method has a higher safety than electric detection methods. Therefore, a model of positioning and state classification of porcelain insulators based on hyperspectral technology is proposed. In this model, image data were used to extract edges to locate cracks, and spectral information was used to classify the surface states of porcelain insulators with EfficientNet. Lastly, crack extraction was realized, and the recognition accuracy of cracks and normal states was 96.9%. Through an analysis of the results, it is proven that the crack detection method of a porcelain insulator based on hyperspectral technology is an effective non-contact online monitoring approach, which has broad application prospects in the era of the Internet of Things with the rapid development of electric power.     

提高综合滤波器鉴别率的一种有效方法

提出一种提高综合滤波器鉴别率的有效方法，其做法是：对样本集在等相关峰条件下求解综合滤波器的同时，使样本集的互补样本满足零件相关峰条件，此方法把训练模式类同所有其它模式类在映射空间的距离拉大，有效地提高了综合滤波器的鉴别率，以取自同一手指纹为样本集，求解综合鉴别函数后，建立了指纹的实时模式识别系统，实验结果表明本文提出的改进方法对提高综合滤波器的鉴别率是非常有效的。