Pressureless low temperature sintering of nanocrystalline zirconia ceramics via dry powder processing

Pressureless sintering approaches provide a simple avenue to manufacture dense ceramic parts with minimal processing equipment, but current pressureless sintering techniques have yet to demonstrate capabilities of producing dense ceramics while maintaining sub-50 nm grain sizes. Nanocrystalline yttria stablized zirconia ceramics were process from 4 mol% yttria stablized zirconia (4YSZ) nanopowders with a crystallite size of 7.5 nm using dry cold isostatic pressing (CIP) where powders are dried immediately prior to green compact formation and CIP vacuum bagging. It is shown that CIP pressures >75 000 psi (517 MPa) effectively remove pores larger than 100 nm and that pressureless sintering occurs at reduced temperatures for green densities ≥50%. Though the sintering kinetics are shown to be similar to other zirconia nanopowder sintering studies, the small initial crystallize size and reduced sintering temperature allowed densities as high as 97.2%, while retaining a ceramic grain size at or below 40 nm. Produced nanocrystalline 4YSZ ceramics with a grain size of 30.3 nm and a density of 96.3% had Vicker's hardnesses as high as 14.2 GPa and Vicker's indentation fracture resistance of 3.43 MPa·, demonstrating that simple processing approaches can be refined to fabricate nanocrystalline ceramics while maintaining high hardness and indentation fracture resistance.     

Effects of silicone oil and polymeric modifiers on the mechanical properties of highly filled LLDPE

The effects of coupling agents, silicone oil, and three types of polymeric modifiers on the mechanical properties of linear low density polyethylene (LLDPE) composites highly filled with aluminium hydroxide [Al(OH)₃] were studied. Polymeric modifiers that contain polar groups, such as silane‐grafted polyethylene (Si‐g‐PE) and acrylic‐acid‐grafted ethylene‐vinyl acetate copolymer (AA‐g‐EVA), improve the mechanical properties dramatically, while nonpolar modifiers improve them to some extent. When Al(OH)₃ was treated using a titanate coupling agent, the silicone oil increased the impact strength and elongation at break of the LLDPE/Al(OH)₃ composites. Introduction of a polymeric modifier containing polar groups destroys the beneficial effects of silicone oil on film mechanical properties, while the introduction of a nonpolar elastomeric polymeric modifier retains the high impact strength and elongation at break. SEM analyses provide the indirect evidence of the encapsulation of silicone oil around the filler. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 83: 121–128, 2002     

低速纺制8.3tex三角异形有光PET长丝——Ⅰ.前纺工艺研究

用VC403纺丝机纺制题示纤维。对设备及工艺进行了改进:在切片干燥前加入0.01%的硬酯酸钙,以增加切片的润滑性能;干燥升温阶段放慢升温速率,冷却阶段通入减湿空气。在切片含水率≤0.006%的情况下,纺丝温度应控制比同规格半消光PET高8—12℃;吹风温度为40—50℃,吹风速度0.2—0.3m/s;加强喷丝板保温;改进吹风窗结构及设计水字形喷丝孔形。     

基于边缘敏感的SLIC和二次密度聚类的GGO分割

针对磨玻璃肺结节(Ground Glass Opacity,GGO)边界对比度低、大小各异和灰度不均匀等造成分割准确率低的问题,提出一种基于边缘敏感的SLIC和二次密度聚类相结合的分割算法。将图像边缘检测结果与SLIC超像素算法相结合,并将其中含有边缘的超像素块用区域质心代替其原始聚类中心,改善SLIC边界黏连性较差的问题;针对密度聚类不能完整分割GGO的问题,提出二次密度聚类的方法,对密度聚类定位到的簇及其邻域簇进行二次密度聚类。实验结果表明,该算法分割GGO的平均准确率达90.17%,灵敏度达84%。     

基于自然最近邻的密度峰值聚类算法

针对密度峰值聚类算法(Density Peaks Clustering,DPC)需要人为指定截断距离d c,以及局部密度定义简单和一步分配策略导致算法在复杂数据集上表现不佳的问题,提出了一种基于自然最近邻的密度峰值聚类算法(Density Peaks Clustering based on Natural Nearest Neighbor,NNN-DPC)。该算法无需指定任何参数,是一种非参数的聚类方法。该算法首先根据自然最近邻的定义,给出新的局部密度计算方法来描述数据的分布,揭示内在的联系;然后设计了两步分配策略来进行样本点的划分。最后定义了簇间相似度并提出了新的簇合并规则进行簇的合并,从而得到最终聚类结果。实验结果表明,在无需参数的情况下,NNN-DPC算法在各类数据集上都有优秀的泛化能力,对于流形数据或簇间密度差异大的数据能更加准确地识别聚类数目和分配样本点。与DPC、FKNN-DPC(Fuzzy Weighted K-nearest Density Peak Clustering)以及其他3种经典聚类算法的性能指标相比,NNN-DPC算法更具优势。     

含氮、磷有机配体对(CdSe)_2量子点结构和电子性质的影响

使用密度泛函理论方法研究了量子点(CdSe)2与配体L(L=PH3、PH2Me、PHMe2、PMe3、NH3、NH2Me、NHMe2、NMe3)之间的相互作用及其产物的结构和性质。配体中的P或N原子与Cd原子上分别形成较强的Cd—P和Cd—N配位键,从而影响(CdSe)2的结构和电子性质。配体作用下,(CdSe)2的几何结构、电荷分布、轨道能级、吸收光谱等均发生变化,但2类配体的影响,尤其是甲基数目的影响,存在较大差异。     

正则化半监督判别分析方法

为了克服加权线性判别分析(WLDA)只利用有标签的训练样本而不能反映样本数据流形结构的缺点,提出一种正则化的半监督判别分析方法。首先构建所有样本的近邻图来估计数据的局部流形结构,然后将此作为正则项引入WLDA的准则函数中。该方法避免了类内散度矩阵奇异,同时保持了样本数据的判别结构和几何结构。在ORL和YALE人脸数据库上的实验结果证明了该算法的有效性。     

基于最大后验概率-马尔科夫随机场的二进制体数据优化

许多三维重建算法的结果以二进制体数据的形式给出,然而直接从中抽取等值面会造成阶梯化、锯齿化等走样现象.为此提出基于最大后验概率?马尔科夫随机场的二进制体数据优化方法.假设目标数据是随机变量并具有马尔科夫性,通过计算其最大后验概率推导了通用的优化公式,以及在常用模型下的优化公式;在此基础上,用户可选择不同的先验模型和观察模型来预测数据最有可能的取值,并将其作为优化结果.实验结果表明,文中方法可用于二进制体数据的可视化,光顺,去噪,修复等.     

基于QS-ML-PMHT的多目标无源协同定位方法

针对目标个数未知时无源协同定位系统低可观测目标的航迹起始及维持问题,提出一种基于拟蒙特卡罗模拟退火极大似然概率多假设的双基站多目标无源协同定位方法。首先,建立双基站无源协同定位系统数学模型。其次,提出基于极大似然概率多假设的多目标无源协同定位航迹起始算法,通过假设法确定目标个数,并首次利用拟蒙特卡罗模拟退火算法解决极大似然概率多假设中多目标的优化求解问题,以提高多目标检测跟踪性能。最后,通过滑窗法实现航迹维持。仿真结果表明,所提方法能够有效解决目标个数未知时双基站无源协同定位系统低可观测目标的航迹起始及维持问题。     

Agro-ecosystem modeling can aid in the optimization of biomass feedstock supply

Recent European Directives promoted the development of biofuels, requesting mandatory limits to their emissions ot greenhouse gases (GHG). Second-generation biofuels based on lignocellulosic biomass are prime candidates but their GHG emissions are variable and uncertain. Agro-ecosystem modeling can capture them and the performance of biofuel feedstocks.This study aimed at optimizing feedstock supply for a bioethanol unit in France, from agricultural residues, annual and perennial crops. Their productivity and environmental impacts were modelled on a regional scale using geo-referenced data on soil properties, crop management, land-use and future weather data. Several supply scenarios were tested. Cereal straw was the most efficient feedstock but had a low availability, and only miscanthus could meet the bioethanol plant's demand. Sorghum combined poor yields and high GHG emissions compared by miscanthus and triticale. A mix of three biomass sources used less than 3% of the regional agricultural land while abating GHG emissions by 60%.