Preparation of Silver Nanowires via a Rapid,Scalable and Green Pathway

Rapid synthesis of silver nanowires(Ag NWs) with high quality and a broad processing window is challenging because of the low selectivity of the formation of multiply twinned particles at the nucleation stage for subsequent Ag NWs growth.Herein we report a systematic study of the water-involved heterogeneous nucleation of Ag NWs with high rate(less than 20 min) in a simple and scalable preparation method.Using glycerol as a reducing agent and a solvent with a high boiling point,the reaction is rapidly heated to 210 ℃ in air to synthesize Ag NWs with a very high yield in gram level.It is noted that the addition of a small dose of water plays a key role for obtaining highly pure Ag NWs in high yield,and the optimal water/glycerol ratio is0.25%.After investigating a series of forming factors including reaction temperature and dose of catalysts,the formation kinetics and mechanism of the Ag NWs are proposed.Compared to other preparation methods,our strategy is simple and reproducible.These Ag NWs show a strong Raman enhancement effect for organic molecules on their surface.     

金属镱低压吸氘研究

在真空系统中的氘压低于0.1 MPa条件下研究了金属镱的吸氘性能,并对不同原子比的氘化物的物相进行了分析.在常压、300 ℃下,金属镱吸氘不明显;400 ℃时,金属镱经较长时间活化后吸附一定量的氘;500 ℃时,镱升华.400 ℃时的吸氘实验结果表明:从活化至开始吸氘直至吸附平衡需很长时间;氘/镱原子比的高低与吸氘时间有关,饱和吸氘时的原子比最大为2.00;金属镱为面心立方(fcc)结构,a0=0.549 2 nm.具有不同原子比的氘化镱的X射线衍射(XRD)分析结果显示:氘化镱有2种结构,即面心立方结构(a0=0.524 nm)和正交结构(a0=0.588 nm、b0=0.358 nm、c0=0.678 nm);金属镱吸氘后,立方结构氘化镱晶格常数及晶胞体积均发生收缩现象,收缩率分别约为4%和11%.正交结构氘化镱晶胞体积收缩约14%.     

Autocoro最新技术: e-save

能源成本上涨速度高于纱线价格上涨速度,Autocoro纺纱厂每年的能耗成本约占每年营业额的5％,主要能耗是电能.     

小眼井最优水力学设计及分析

在充分考虑小眼井钻井特点和合理确定环空压耗的基础上，将喷射钻井理论和环空携岩理论有机结合起来，导出了在两种工作方式下优化设计小眼井钻井水力参数模型，并开发了应用软件。通过实例计算，提出了在小眼井最优水力学设计中采用最大水功率工作方式的重要性，并建议在大眼井的水力参数设计中考虑钻柱的偏心、旋转和钻杆接头对环空压耗的影响。     

Exact solution of elasto-plastic stresses in a metal-matrix composite beam of arbitrary orientation subjected to transverse loads

An analytical elasto-plastic stress analysis is presented for a metal-matrix composite beam of arbitrary orientation subjected to a single transverse force applied to the free end of the beam and a uniformly distributed load. The material is assumed to be perfectly plastic in the elasto-plastic solution. A composite consisting of stainless-steel-reinforced aluminum was produced for this work. Sample problems are given for various orientation angles. Elastic, elastoplastic and residual normal and shear stresses are calculated. The location of the elasto-plastic boundary of the beam is obtained according to the x coordinates of the beam.     

热塑性塑料管材抗蠕变性能评价

描述了热塑性塑料管材的抗蠕变性及其有关的评价方法，介绍了几种标准测试方法。     

连锁快餐企业的顾客满意度评价模型

从品牌、产品、服务和环境等方面建立基于证据推理的连锁快餐企业顾客满意度评价模型。为反映不同店面顾客满意度的差异,依据营业额设定店面权重,将各店面的评价结果作为证据集结出总体满意度。抽样调查安徽省某知名连锁快餐企业的七家分店,获取其一周的问卷数据。通过仿真试验,验证了模型的有效性和实用性,对比两种模型的试验结果,并对企业经营提出了一些建议。     

一种电流变（ER）材料的研制与电流变性能测试

本文对一种电流变液体的颗粒材料和基础液的研制工艺进行探讨，并对其电流变性能进行了测试。     

Recognizing arabic handwritten characters using deep learning and genetic algorithms

Automated techniques for Arabic content recognition are at a beginning period contrasted with their partners for the Latin and Chinese contents recognition. There is a bulk of handwritten Arabic archives available in libraries, data centers, historical centers, and workplaces. Digitization of these documents facilitates (1) to preserve and transfer the country’s history electronically, (2) to save the physical storage space, (3) to proper handling of the documents, and (4) to enhance the retrieval of information through the Internet and other mediums. Arabic handwritten character recognition (AHCR) systems face several challenges including the unlimited variations in human handwriting and the leakage of large and public databases. In the current study, the segmentation and recognition phases are addressed. The text segmentation challenges and a set of solutions for each challenge are presented. The convolutional neural network (CNN), deep learning approach, is used in the recognition phase. The usage of CNN leads to significant improvements across different machine learning classification algorithms. It facilitates the automatic feature extraction of images. 14 different native CNN architectures are proposed after a set of try-and-error trials. They are trained and tested on the HMBD database that contains 54,115 of the handwritten Arabic characters. Experiments are performed on the native CNN architectures and the best-reported testing accuracy is 91.96%. A transfer learning (TF) and genetic algorithm (GA) approach named “HMB-AHCR-DLGA” is suggested to optimize the training parameters and hyperparameters in the recognition phase. The pre-trained CNN models (VGG16, VGG19, and MobileNetV2) are used in the later approach. Five optimization experiments are performed and the best combinations are reported. The highest reported testing accuracy is 92.88%.

     

Improvements of the structural,thermal, and mechanical properties of structural adhesive with functionalized boron nitride nanoparticles

Investigations on the production and development of nanoparticle-reinforced polymer materials have been attracted attention by researchers. Various nanoparticles have been used to improve the mechanical, chemical, thermal, and physical properties of polymer matrix composites. Boron compounds come to the fore to improve the mechanical and thermal properties of polymers. In this study, mechanical, thermal, and structural properties of structural adhesive have been examined by adding nano hexagonal boron nitride (h-BN) to epoxy matrix at different percentages (0.5, 1, 2, 3, 4, and 5%). For this purpose, nano h-BN particles were functionalized with 3-aminopropyltriethoxysilane (APTES) to disperse the h-BN nanoparticles homogeneously in epoxy matrix and to form a strong bond at the matrix interface. Two-component structural epoxy adhesive was modified by using functionalized h-BN nanoparticles. The structural and thermal properties of the modified adhesives were investigated by scanning electron microscopy and energy dispersion X-ray spectroscopy, Fourier transform infrared spectroscopy, differential scanning calorimetry, and thermogravimetric analysis techniques. Tensile test and dynamic mechanical analysis were performed to determine the mechanical properties of the adhesives. When the results obtained from analysis were examined, it was seen that the nano h-BN particles functionalized with APTES were homogeneously dispersed in the epoxy matrix and formed a strong bond. In addition that, it was concluded from the experimental results that the thermal and mechanical properties of adhesives were improved by adding functionalized nano h-BN particles into epoxy at different ratios.