石灰石在煤气化过程中的催化和固硫作用

基于CaO在煤气化中的催化和固硫作用,以及石灰石加热分解的性质,石灰石有可能作为煤气化过程中的催化剂和固硫剂。本文根据国内外对石灰石在煤燃烧和煤气化中作用的研究,从石灰石结构、Ca/C,Ca/S,可能的反应机理等几个方面进行了介绍和分析,并指出需进一步研究的内容。     

Sparse Localized Decomposition of Deformation Gradients

Sparse localized decomposition is a useful technique to extract meaningful deformation components out of a training set of mesh data. However, existing methods cannot capture large rotational motion in the given mesh dataset. In this paper we present a new decomposition technique based on deformation gradients. Given a mesh dataset, the deformation gradient field is extracted, and decomposed into two groups: rotation field and stretching field, through polar decomposition. These two groups of deformation information are further processed through the sparse localized decomposition into the desired components. These sparse localized components can be linearly combined to form a meaningful deformation gradient field, and can be used to reconstruct the mesh through a least squares optimization step. Our experiments show that the proposed method addresses the rotation problem associated with traditional deformation decomposition techniques, making it suitable to handle not only stretched deformations, but also articulated motions that involve large rotations.     

透明香皂的研制

介绍了生产透明香皂的新配方和新工艺 ,提出了透明香皂的企业标准。新工艺用丙二醇取代传统工艺所用的乙醇做溶剂 ,生产周期大为缩短。采用速冻隧道设备 ,可方便地实现不同品种的切换 ,操作方便 ,设备投资少 ,产品综合成本低 ,具有较大的工业应用价值     

EWOD microfluidic systems for biomedical applications

As the technology advances, a growing number of biomedical microelectromechanical systems (bio-MEMS) research involves development of lab-on-a-chip devices and micrototal analysis systems. For example, a portable instrument capable of biomedical analyses (e.g., blood sample analysis) and immediate recording, whether the patients are in the hospital or home, would be a considerable benefit to human health with an excellent commercial viability. Digital microfluidic (DMF) system based on the electrowetting-on-dielectric (EWOD) mechanism is an especially promising candidate for such point-of-care systems. The EWOD-based DMF system processes droplets in a thin space or on an open surface, unlike the usual microfluidic systems that process liquids by pumping them in microchannels. Droplets can be generated and manipulated on EWOD chip only with electric signals without the use of pumps or valves, simplifying the chip fabrication and the system construction. Microfluidic operations by EWOD actuation feature precise droplet actuation, less contamination risk, reduced reagents volume, better reagents mixing efficiency, shorter reaction time, and flexibility for integration with other elements. In addition, the simplicity and portability make the EWOD-based DMF system widely popular in biomedical or chemical fields as a powerful sample preparation platform. Many chemical and biomedical researches, such as DNA assays, proteomics, cell assays, and immunoassays, have been reported using the technology. In this paper, we have reviewed the recent developments and studies of EWOD-based DMF systems for biomedical applications published mostly during the last 5 years.     

Investigation and improvement of reversible microfluidic devices based on glass–PDMS–glass sandwich configuration

Reversibly assembled microfluidic devices are dismountable and reusable, which is useful for a number of applications such as micro- and nano-device fabrication, surface functionalization, complex cell patterning, and other biological analysis by means of spatial–temporal pattern. However, reversible microfluidic devices fabricated with current standard procedures can only be used for low-pressure applications. Assembling technology based on glass–PDMS–glass sandwich configuration provides an alternative sealing method for reversible microfluidic devices, which can drastically increase the sealing strength of reversibly adhered devices. The improvement mechanism of sealing properties of microfluidic devices based on the sandwich technique has not been fully characterized, hindering further improvement and broad use of this technique. Here, we characterize, for the first time, the effect of various parameters on the sealing strength of reversible PDMS/glass hybrid microfluidic devices, including contact area, PDMS thickness, assembling mode, and external force. To further improve the reversible sealing of glass–PDMS–glass microfluidic devices, we propose a new scheme which exploits mechanical clamping elements to reinforce the sealing strength of glass–PDMS–glass sandwich structures. Using our scheme, the glass–PDMS–glass microchips can survive a pressure up to 400 kPa, which is comparable to the irreversibly bonded PDMS microdevices. We believe that this bonding method may find use in lab-on-a-chip devices, particularly in active high-pressure-driven microfluidic devices.     

捣固炼焦在中国焦化工业发展中的前景与展望

介绍了我国炼焦煤源的现状、捣固炼焦的理论依据,并将捣固炼焦技术与常规炼焦方法进行了比较,指出捣固炼焦应向大型化方向发展,并提高捣固和装煤的自动化水平,发展捣固炼焦可促进我国焦化工业的可持续发展。     

单幅图像多尺度小波深度提取算法

针对浅景深图像中平滑前景区域深度提取误差大的问题,基于像素点分类思想对深度值进行修正,提出一种基于多尺度小波线索的、可同时面向单幅浅景深图像和广角图像的深度图提取算法.首先使用小波分析法在多个尺度下提取图像深度信息;然后提出自适应分类法并根据尺度与深度变化规律对像素点做深度修正,得到深度图;最后结合区域生长与边缘分割算法对深度图进行区域优化.为了加快深度计算,还提出了快速zerocount法以及多尺度加速法来满足标清视频实时处理要求.实验结果证明,采用文中算法获得的深度图相对深度正确,前景和背景区域深度一致性好.     

基于WiFi无线通信的温湿度检测节点设计

基于AM2303温湿度传感器、STC15F104W单片机和WiFi模块设计了一种无线温湿度检测节点。介绍了AM2303及其通信协议、WiFi模块及其组网特性等,并且给出了读取AM2303数据的软件流程。经测试,该节点通信距离远,组网灵活,可很好地应用于粮库粮情检测等实际工作环境。     

Aromatization of n-butane over new LD-HBS catalysts. Effect of the gallium oxide support

It is shown that even pure quartz, other silicas or aluminas can enhance the aromatization activity of a ZSM-5 zeolite. Incorporation of gallium oxide onto these supports increases further the production of aromatics. The use of supported gallium oxide co-catalyst obtained by co-evaporation of a colloidal silica and a Ga salt has led to extremely high aromatization performance for the hybrid catalyst.     

A surrogate-based optimization method with RBF neural network enhanced by linear interpolation and hybrid infill strategy

In engineering, it is computationally prohibitive to directly employ costly models in optimization. Therefore, surrogate-based optimization is developed to replace the accurate models with cheap surrogates during optimization for efficiency. The two key issues of surrogate-based optimization are how to improve the surrogate accuracy by making the most of the available training samples, and how to sequentially augment the training set with certain infill strategy so as to gradually improve the surrogate accuracy and guarantee the convergence to the real global optimum of the accurate model. To address these two issues, a radial basis function neural network (RBFNN) based optimization method is proposed in this paper. First, a linear interpolation (LI) based RBFNN modelling method, LI-RBFNN, is developed, which can enhance the RBFNN accuracy by enforcing the gradient match between the surrogate and the trend observed from the training samples. Second, a hybrid infill strategy is proposed, which uses the surrogate prediction error based surrogate lower bound as the optimization objective to locate the promising region and meanwhile employs a linear interpolation-based sequential sampling approach to improve the surrogate accuracy globally. Finally, extensive tests are investigated and the effectiveness and efficiency of the proposed methods are demonstrated.