无氰解吸工艺生产实践

结合生产实践讨论分析了影响载金炭解吸工艺指标的主要因素，介绍了无氰解吸工艺应用效果。     

D_2EHDTPA萃取铟的热力学研究

报道了用二 (2 乙基己基 )二硫代磷酸为萃取剂 ,以正庚烷为稀释剂萃取铟的热力学研究。在In2 (SO4 ) 3+Na2 SO4 +D2 EHDTPA +n C7H1 6 +H2 O体系中 ,在温度 2 78.15～ 3 0 3 .15K和离子强度 0 .1～ 2 .0mol·kg- 1 范围内 ,以Na2 SO4 为支持电解质 ,测定了萃取平衡水相中In3+浓度和pH值。计算了萃取反应的标准平衡常数K0 ,并得到经验公式logK0 =43 .93 -5 3 68.5 4 T -0 .0 699T ,同时计算了萃取反应的其他热力学量 ,并指出了焓和熵都是此萃取过程的推动力     

高温合金表面激光熔敷热障涂层组织结构与氧化性能

采用 5KW连续CO2 激光器对Ni基高温合金上二次重熔NiCoCrAlY和ZrO2 陶瓷层进行了研究。结果表明 :激光快速熔化和凝固获得定向外延生长、紧密堆积的柱状晶氧化锆陶瓷层。NiCoCrAlY结合层与柱状晶之间存在氧化铝层 ,保证了柱状晶与NiCoCrAlY层的联结。扫描电镜和电子探针联合分析发现 ,氧化锆层与NiCoCrAlY结合层、结合层与基体间均为冶金结合。采用化学改性氧化锆消除了涂层裂纹。高温氧化性能测试得出激光重熔试样氧化动力学近似地遵守抛物线速率方程。在 12 0 0℃ ,空气下激光熔敷TBCs 抗氧化性明显高于等离子喷涂TBCs。     

Comparison of physical characteristics and cell culture test of hydroxyapatite/collagen composite coating on NiTi SMA: electrochemical deposition and chemically biomimetic growth

A hydroxyapatite (HA)/collagen (COL) composite coating on NiTi shape memory alloy (SMA) was prepared by eletrochemical deposition (ELD) in modified simulated body fluid (MSBF). To draw comparisons of physical characteristics and bioactivity of the composite coating, the HA/COL composite coating was also prepared by chemically biomimetic growth (BG) and the ELD coating was re-soaked in MSBF again for further biomimetic growth (called EBG method in this paper). It was indicated that the c-axis of HA crystals was oriented parallel to the longitudinal direction of the COL fibril in BG and EBG coating, which could not found in ELD coating. The EBG method could induce a denser, thicker and better crystallized HA/COL coating. The cell culture test indicated that the BG coating presented better cell biocompatibility.     

中国古代金的分析技术

归纳总结了中国古代金分析技术的主要成果和与其相关的重要事件，对于认识金的分析技术的起源有一定的参考意义。     

基于XML的构件化企业模型描述及应用

当今世界Internet/Intranet技术的迅速发展，对企业建模也提出了网络化的要求。而当前众多的建模工具都还没能适应这一要求，或是才开始起步。鉴于这种状况，提出了基于XML技术的描述构件化模型的思想，以对当前已经比较成熟的建模技术进行XML的改造，讲述如何实现基于XML的构件化企业模型描述及应用。     

New Additive Watermark Detectors Based On A Hierarchical Spatially Adaptive Image Model

In this paper, we propose a new family of watermark detectors for additive watermarks in digital images. These detectors are based on a recently proposed hierarchical, two-level image model, which was found to be beneficial for image recovery problems. The top level of this model is defined to exploit the spatially varying local statistics of the image, while the bottom level is used to characterize the image variations along two principal directions. Based on this model, we derive a class of detectors for the additive watermark detection problem, which include a generalized likelihood ratio, Bayesian, and Rao test detectors. We also propose methods to estimate the necessary parameters for these detectors. Our numerical experiments demonstrate that these new detectors can lead to superior performance to several state-of-the-art detectors.